Islamic Azad University, South Tehran Branch
Journal of Industrial Engineering, International
1735-5702
2251-712X
8
1
2012
01
01
An electromagnetism-like metaheuristic for open-shop problems with no buffer
EN
Bahman
Naderi
1Department of Industrial Engineering, Faculty of Engineering, University of
Kharazmi, Karaj, Iran
Esmaeil
Najafi
Department of Industrial Engineering, Science & Research Branch, Islamic Azad University, Tehran, Iran
Mehdi
Yazdani
Department of Industrial Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
This paper considers open-shop scheduling with no intermediate buffer to minimize total tardiness. This problem occurs in many production settings, in the plastic molding, chemical, and food processing industries. The paper mathematically formulates the problem by a mixed integer linear program. The problem can be optimally solved by the model. The paper also develops a novel metaheuristic based on an electromagnetism algorithm to solve the large-sized problems. The paper conducts two computational experiments. The first includes small-sized instances by which the mathematical model and general performance of the proposed metaheuristic are evaluated. The second evaluates the metaheuristic for its performance to solve some large-sized instances. The results show that the model and algorithm are effective to deal with the problem.
Scheduling,Open shop with no buffer,Mixed integer linear programming,Electromagnetism algorithm
http://jiei.azad.ac.ir/article_676417.html
http://jiei.azad.ac.ir/article_676417_e61782b4e29d7665a8090e58ac826671.pdf
Islamic Azad University, South Tehran Branch
Journal of Industrial Engineering, International
1735-5702
2251-712X
8
1
2012
01
01
A new binary model for university examination timetabling: a case study
EN
Alireza
Rashidi Komijan
Department of Industrial Engineering, Firoozkooh Branch, Islamic Azad
University, Firoozkooh, Iran
Mehrdad
Nouri Koupaei
Department of Management, Firoozkooh Branch, Islamic Azad University, Firoozkooh, Iran
mhrdd_nouri@yahoo.com
Examination timetabling problem (ETP) is one of the most important issues in universities. An improper timetable<br /> may result in students' dissatisfaction as it may not let them study enough between two sequential exams. In<br /> addition, the many exams to be scheduled, the large number of students who have taken different courses, the<br /> limited number of rooms, and some constraints such as no conflict in a single student's exams make it very difficult<br /> to schedule experimentally. A mathematical programming model is required to formulate such a sophisticated<br /> problem. In this paper, a new binary model is developed for ETP. The novelty of the paper can be discussed in two<br /> directions. The first one is that a course can be offered more than once in a semester. If a course is requested by a<br /> few students, then it is enough to be offered once. If the number of students requesting a course is more than the<br /> maximum number of students who are allowed to attend a single class, then the course is multi-offered. The<br /> second novelty is that sharing a room for two simultaneous exams is allowed. Also, the model considers some hard<br /> and soft constraints, and the objective function is set in such a way that soft constraints are satisfied as much as<br /> possible. Finally, the model is applied in a sample department and is solved by GAMS
Binary programming,Mathematical Modeling,Examination timetabling problem
http://jiei.azad.ac.ir/article_676418.html
http://jiei.azad.ac.ir/article_676418_f4d50d7a6139afed81f68bfc1347da9d.pdf
Islamic Azad University, South Tehran Branch
Journal of Industrial Engineering, International
1735-5702
2251-712X
8
1
2012
01
01
Retracted: Using genetic algorithm approach to solve a multi-product EPQ model with defective items, rework, and constrained space
EN
Kiamars
Fathi Hafshejani
Department of Industrial Management, Islamic Azad University, South
Tehran Branch, P.O. Box: 11365/4435, Tehran, Iran
Changiz
Valmohammadi
Department of Industrial Management, Islamic Azad University, South
Tehran Branch, P.O. Box: 11365/4435, Tehran, Iran
Alireza
Khakpoor
Department of Management/Accounting, Islamic Azad University, Qazvin Branch, P.O. Box: 34185–1416, Qazvin, Iran
The Economic Production Quantity (EPQ) model is often used in the manufacturing sector to assist firms in<br /> determining the optimal production lot size that minimizes overall production-inventory costs. There are some<br /> assumptions in the EPQ model that restrict this model for real-world applications. Some of these assumptions are<br /> (1) infinite space of warehouse, (2) all of the produced items are perfect, and (3) only one type of goods is<br /> produced. In this paper, we develop the EPQ model by assuming that each produced lot contains some imperfect<br /> items and scraps. In addition, we have more than one kind of products along with warehouse space limitations.<br /> Under these conditions, we formulate the problem as a non-linear programming model and propose a genetic<br /> algorithm to solve it. At the end, we present a numerical example to illustrate the applications of the proposed<br /> methodology and identify the optimal value of the parameters of the genetic algorithm.
EPQ,Multi-product,Perfect,Imperfect and scrap items,Constrained space,Genetic Algorithm
http://jiei.azad.ac.ir/article_676419.html
http://jiei.azad.ac.ir/article_676419_451a34f2dfc38a75ccd5a71fe0081503.pdf
Islamic Azad University, South Tehran Branch
Journal of Industrial Engineering, International
1735-5702
2251-712X
8
1
2012
01
01
A three-stage assembly flow shop scheduling problem with blocking and sequence-dependent set up times
EN
Aref
Maleki-Darounkolaei
Department of Management and Accounting, South Tehran Branch, Islamic
Azad University, Tehran, Iran
Mahmoud
Modiri
Department of Management and Accounting, South Tehran Branch, Islamic
Azad University, Tehran, Iran
Reza
Tavakkoli-Moghaddam
0000-0002-6757-926X
Department of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
tavakoli@ut.ac.ir
Iman
Seyyedi
Department of Industrial Engineering, Payame Noor University, Tehran, Iran
This paper considers a three-stage assembly flowshop scheduling problem with sequence-dependent setup < /div><br /> times at the first stage and blocking times between each stage in such a way that the weighted mean<br /> completion time and makespan are minimized. Obtaining an optimal solution for this type of complex,<br /> large-sized problem in reasonable computational time using traditional approaches or optimization tools is<br /> extremely difficult. Thus, this paper proposes a meta-heuristic method based on simulated annealing (SA) in<br /> order to solve the given problem. Finally, the computational results are shown and compared in order to show<br /> the efficiency of our proposed SA.
Assembly flowshop scheduling,Sequence-dependent setup times,Blocking times,Weighted mean completion time,makespan,Simulated Annealing
http://jiei.azad.ac.ir/article_676420.html
http://jiei.azad.ac.ir/article_676420_6b8d61b36569f289d0a45e9c29508480.pdf
Islamic Azad University, South Tehran Branch
Journal of Industrial Engineering, International
1735-5702
2251-712X
8
1
2012
01
01
Minimizing the total tardiness and makespan in an open shop scheduling problem with sequence-dependent setup times
EN
Samaneh
Noori-Darvish
Department of Industrial Engineering, Allame Mohades Noori University, PC: 46415-451, Noor, Iran
Reza
Tavakkoli-Moghaddam
0000-0002-6757-926X
Department of Industrial Engineering, College of Engineering, University of
Tehran, PC: 14399-57131, Tehran, Iran
tavakoli@ut.ac.ir
We consider an open shop scheduling problem with setup and processing times separately such that not only the<br /> setup times are dependent on the machines, but also they are dependent on the sequence of jobs that should be<br /> processed on a machine. A novel bi-objective mathematical programming is designed in order to minimize the<br /> total tardiness and the makespan. Among several multi-objective decision making (MODM) methods, an interactive<br /> one, called the TH method is applied for solving small-sized instances optimally and obtaining Pareto-optimal<br /> solutions by the Lingo software. To achieve Pareto-optimal sets for medium to large-sized problems, an improved<br /> non-dominated sorting genetic algorithm II (NSGA-II) is presented that consists of a heuristic method for obtaining<br /> a good initial population. In addition, by using the design of experiments (DOE), the efficiency of the proposed<br /> improved NSGA-II is compared with the efficiency of a well-known multi-objective genetic algorithm, namely SPEAII.<br /> Finally, the performance of the improved NSGA-II is examined in a comparison with the performance of the<br /> traditional NSGA-II.
Open shop scheduling,Total tardiness,makespan,Sequence-dependent setup times,NSGA-II,SPEA-II
http://jiei.azad.ac.ir/article_676421.html
http://jiei.azad.ac.ir/article_676421_dfbbf22cb1ae5db12de4447b9e87afa8.pdf
Islamic Azad University, South Tehran Branch
Journal of Industrial Engineering, International
1735-5702
2251-712X
8
1
2012
01
01
Solving an one-dimensional cutting stock problem by simulated annealing and tabu search
EN
Meghdad
HMA Jahromi
Department of Industrial Engineering, Khomein Branch, Islamic Azad
University, Khomein, Iran
Reza
Tavakkoli-Moghaddam
0000-0002-6757-926X
Department of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
tavakoli@ut.ac.ir
Ahmad
Makui
Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
Abbas
Shamsi
Department of Industrial Engineering, Khomein Branch, Islamic Azad
University, Khomein, Iran
A cutting stock problem is one of the main and classical problems in operations research that is modeled as Lp < /div><br /> problem. Because of its NP-hard nature, finding an optimal solution in reasonable time is extremely difficult and at<br /> least non-economical. In this paper, two meta-heuristic algorithms, namely simulated annealing (SA) and tabu<br /> search (TS), are proposed and developed for this type of the complex and large-sized problem. To evaluate the<br /> efficiency of these proposed approaches, several problems are solved using SA and TS, and then the related results<br /> are compared. The results show that the proposed SA gives good results in terms of objective function values<br /> rather than TS.
One-dimensional cutting stock problem,mathematical model,Simulated Annealing,Tabu search
http://jiei.azad.ac.ir/article_676422.html
http://jiei.azad.ac.ir/article_676422_e534bec099c565c9cba23817e1362905.pdf
Islamic Azad University, South Tehran Branch
Journal of Industrial Engineering, International
1735-5702
2251-712X
8
1
2012
01
01
An empirical study of innovation-performance linkage in the paper industry
EN
Parveen
Farooquie
Department of Mechanical Engineering, Aligarh Muslim University (AMU),
Aligarh, India
Abdul
Gani
Department of Mechanical Engineering, Aligarh Muslim University (AMU),
Aligarh, India
Arsalanullah
K Zuberi
Department of Mechanical Engineering, Aligarh Muslim University (AMU),
Aligarh, India
Imran
Hashmi
Department of Mechanical Engineering, Aligarh Muslim University (AMU),
Aligarh, India
To enter new markets and remain competitive in the existing markets, companies need to shift their focus from<br /> traditional means and ways to some innovative approaches. Though the paper industry in India has improved<br /> remarkably on its technological and environmental issues, yet it shows a low rate of innovation. The present paper<br /> attempts to review the industry in the perspective of technological innovations and investigates empirically the role<br /> of innovations in performance improvement and pollution control. Multivariate analysis of variance and discriminant<br /> function analysis are applied for data processing. The findings reveal that the mean scores on the factors, such as<br /> sales, quality, and flexibility, are higher for the good innovators than those for the poor innovators. Conversely, the<br /> factors which are likely to be reduced as a result of innovations, such as time, cost, emissions, and disposal of<br /> waste, have shown higher means for the poor innovators.
Discriminant function analysis,Paper industry,performance,Multivariate analysis of variance,Technological innovation
http://jiei.azad.ac.ir/article_676423.html
http://jiei.azad.ac.ir/article_676423_3261ed4ecf9e2a5e82b6343301d1054a.pdf
Islamic Azad University, South Tehran Branch
Journal of Industrial Engineering, International
1735-5702
2251-712X
8
1
2012
01
01
The investigation of supply chain's reliability measure: a case study
EN
Houshang
Taghizadeh
Department of Management, Tabriz Branch, Islamic Azad University, Tabriz,
Iran
Ehsan
Hafezi
Industrial Engineering - System Management and Productivity at the Non-Governmental and Private Higher Education Institution of ALGHADIR, Tabriz, Iran
In this paper, using supply chain operational reference, the reliability evaluation of available relationships in supply<br /> chain is investigated. For this purpose, in the first step, the chain under investigation is divided into several stages<br /> including first and second suppliers, initial and final customers, and the producing company. Based on the formed<br /> relationships between these stages, the supply chain system is then broken down into different subsystem parts.<br /> The formed relationships between the stages are based on the transportation of the orders between stages. Paying<br /> attention to the system elements' location, which can be in one of the five forms of series namely parallel, series/<br /> parallel, parallel/series, or their combinations, we determine the structure of relationships in the divided subsystems.<br /> According to reliability evaluation scales on the three levels of supply chain, the reliability of each chain is then<br /> calculated. Finally, using the formulas of calculating the reliability in combined systems, the reliability of each<br /> system and ultimately the whole system is investigated.
Supply Chain,reliability,Supply chain operational reference
http://jiei.azad.ac.ir/article_676424.html
http://jiei.azad.ac.ir/article_676424_c6e768593a94fa185bd76d4db7e93625.pdf
Islamic Azad University, South Tehran Branch
Journal of Industrial Engineering, International
1735-5702
2251-712X
8
1
2012
01
01
A simple approach to the two-dimensional guillotine cutting stock problem
EN
Mir-Bahador
Aryanezhad
Department of Industrial Engineering, Iran University of Science and
Technology, Tehran 16846-13114, Iran
Nima
Fakhim Hashemi
Department of Industrial Engineering, Iran University of Science and
Technology, Tehran 16846-13114, Iran
Ahmad
Makui
Department of Industrial Engineering, Iran University of Science and
Technology, Tehran 16846-13114, Iran
Hasan
Javanshir
Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, 11518-63411, Iran
Cutting stock problems are within knapsack optimization problems and are considered as a non-deterministic<br /> polynomial-time (NP)-hard problem. In this paper, two-dimensional cutting stock problems were presented in<br /> which items and stocks were rectangular and cuttings were guillotine. First, a new, practical, rapid, and heuristic<br /> method was proposed for such problems. Then, the software implementation and architecture specifications were<br /> explained in order to solve guillotine cutting stock problems. This software was implemented by C++ language in a<br /> way that, while running the program, the operation report of all the functions was recorded and, at the end, the<br /> user had access to all the information related to cutting which included order, dimension and number of cutting<br /> pieces, dimension and number of waste pieces, and waste percentage. Finally, the proposed method was evaluated<br /> using examples and methods available in the literature. The results showed that the calculation speed of the<br /> proposed method was better than that of the other methods and, in some cases, it was much faster. Moreover, it<br /> was observed that increasing the size of problems did not cause a considerable increase in calculation time.<br /> In another section of the paper, the matter of selecting the appropriate size of sheets was investigated; this subject<br /> has been less considered by far. In the solved example, it was observed that incorrect selection from among the<br /> available options increased the amount of waste by more than four times. Therefore, it can be concluded that<br /> correct selection of stocks for a set of received orders plays a significant role in reducing waste.
Cutting stock problem,Trim loss,Two-dimensional cutting,Guillotine cutting
http://jiei.azad.ac.ir/article_676425.html
http://jiei.azad.ac.ir/article_676425_01bce5e4eb2e5c3c4a068a4dca17da43.pdf
Islamic Azad University, South Tehran Branch
Journal of Industrial Engineering, International
1735-5702
2251-712X
8
1
2012
01
01
Forecasting time and place of earthquakes using a Semi-Markov model (with case study in Tehran province)
EN
Ramin
Sadeghian
Islamic Azad University, South Tehran Branch, Industrial Engineering Faculty,
Tehran, Iran
The paper examines the application of semi-Markov models to the phenomenon of earthquakes in Tehran<br /> province. Generally, earthquakes are not independent of each other, and time and place of earthquakes are related<br /> to previous earthquakes; moreover, the time between earthquakes affects the pattern of their occurrence; thus, this<br /> occurrence can be likened to semi-Markov models. In our work, we divided the province of Tehran into six regions<br /> and grouped the earthquakes regarding their magnitude into three classes. Using a semi-Markov model, it<br /> proceeds to predict the likelihood of the time and place of occurrence of earthquakes in the province.
Semi-Markov model,Earthquake occurrence,forecasting,Transition matrix
http://jiei.azad.ac.ir/article_676426.html
http://jiei.azad.ac.ir/article_676426_a69c2bfdf2a09768de1e6690592a8d52.pdf
Islamic Azad University, South Tehran Branch
Journal of Industrial Engineering, International
1735-5702
2251-712X
8
1
2012
01
01
Supply chain network design problem for a new market opportunity in an agile manufacturing system
EN
Reza
Babazadeh
Department of Industrial Engineering, College of Engineering, University of
Tehran, Tehran, Iran
Jafar
Razmi
Department of Industrial Engineering, College of Engineering, University of
Tehran, Tehran, Iran
Reza
Ghodsi
Department of Industrial Engineering, College of Engineering, University of
Tehran, Tehran, Iran
The characteristics of today's competitive environment, such as the speed with which products are designed,<br /> manufactured, and distributed, and the need for higher responsiveness and lower operational cost, are forcing<br /> companies to search for innovative ways to do business. The concept of agile manufacturing has been proposed<br /> in response to these challenges for companies. This paper copes with the strategic and tactical level decisions in<br /> agile supply chain network design. An efficient mixed-integer linear programming model that is able to consider<br /> the key characteristics of agile supply chain such as direct shipments, outsourcing, different transportation modes,<br /> discount, alliance (process and information integration) between opened facilities, and maximum waiting time of<br /> customers for deliveries is developed. In addition, in the proposed model, the capacity of facilities is determined as<br /> decision variables, which are often assumed to be fixed. Computational results illustrate that the proposed model<br /> can be applied as a power tool in agile supply chain network design as well as in the integration of strategic<br /> decisions with tactical decisions.
supply chain management,Agile supply chain network design,outsourcing,Responsiveness
http://jiei.azad.ac.ir/article_676427.html
http://jiei.azad.ac.ir/article_676427_19770de50a8d3e8302bff43156220e0f.pdf
Islamic Azad University, South Tehran Branch
Journal of Industrial Engineering, International
1735-5702
2251-712X
8
1
2012
01
01
Constrained consumable resource allocation in alternative stochastic networks via multi-objective decision making
EN
Seyed
Saeid Hashemin
Department of Industrial Engineering, Ardabil Branch, Islamic Azad
University, Ardabil, 56157-31567, Iran
Seyed Mohammad
Taghi Fatemi Ghomi
Department of Industrial Engineering, Amirkabir University of Technology, Tehran, 15988-46611, Iran
Many real projects complete through the realization of one and only one path of various possible network paths.<br /> Here, these networks are called alternative stochastic networks (ASNs). It is supposed that the nodes of considered<br /> network are probabilistic with exclusive-or receiver and exclusive-or emitter. First, an analytical approach is proposed<br /> to simplify the structure of the network. This approach transforms the network into a simpler equivalent one. This<br /> paper discusses the constrained consumable resource allocation problem in an ASN. Many recent researchers apply<br /> heuristic and simulation methods to solve the constrained resource allocation in these problems. In this paper, we<br /> propose an analytical approach based on multi-objective modeling. The objective functions of this model are the<br /> cumulative distribution function of the completion time of ASN paths. These functions must be maximized within<br /> the desired network completion time. Lexicographic method is used to solve the proposed multi-objective model.<br /> The proposed method is illustrated by an example.
stochastic network,Resource allocation,Multi-objective,decision making,Lexicographic Method,Gaussian quadrature formula,Conditional simulation
http://jiei.azad.ac.ir/article_676428.html
http://jiei.azad.ac.ir/article_676428_20324503bada011b1a3904ea740d3784.pdf
Islamic Azad University, South Tehran Branch
Journal of Industrial Engineering, International
1735-5702
2251-712X
8
1
2012
01
01
An L1-norm method for generating all of efficient solutions of multi-objective integer linear programming problem
EN
Ghasem
Tohidi
1Assistant professor Department of Mathematics, Islamic Azad University,
Central Tehran Branch, Tehran, Iran
Shabnam
Razavyan
Assistant professor Department of Mathematics, Islamic Azad University, South Tehran Branch, Tehran, Iran
This paper extends the proposed method by Jahanshahloo et al. (2004) (a method for generating all the efficient solutions of a 0–1 multi-objective linear programming problem, Asia-Pacific Journal of Operational Research). This paper considers the recession direction for a multi-objective integer linear programming (MOILP) problem and presents necessary and sufficient conditions to have unbounded feasible region and infinite optimal values for objective functions of MOILP problems. If the number of efficient solution is finite, the proposed method finds all of them without generating all feasible solutions of MOILP or concluding that there is no efficient solution. In any iteration of the proposed algorithm, a single objective integer linear programming problem, constrained problem, is solved. We will show that the optimal solutions of these single objective integer linear programming problems are efficient solutions of an MOILP problem. The algorithm can also give subsets of efficient solutions that can be useful for designing interactive procedures for large, real-life problems. The applicability of the proposed method is illustrated by using some numerical examples.
Multi-objective integer linear programming,Single objective integer linear programming,Recession direction,Efficient solution,L1-Norm
http://jiei.azad.ac.ir/article_676429.html
http://jiei.azad.ac.ir/article_676429_063a2b03b96f25544894c4b16deedc72.pdf
Islamic Azad University, South Tehran Branch
Journal of Industrial Engineering, International
1735-5702
2251-712X
8
1
2012
01
01
Mathematical solution of multilevel fractional programming problem with fuzzy goal programming approach
EN
Kailash
Lachhwani
Department of Mathematics, Government Engineering College, Bikaner
334004, India
Mahaveer
Prasad Poonia
Department of Mechanical Engineering, Government Engineering College, Bikaner, 334004, India
In this paper, we show a procedure for solving multilevel fractional programming problems in a large hierarchical decentralized organization using fuzzy goal programming approach. In the proposed method, the tolerance membership functions for the fuzzily described numerator and denominator part of the objective functions of all levels as well as the control vectors of the higher level decision makers are respectively defined by determining individual optimal solutions of each of the level decision makers. A possible relaxation of the higher level decision is considered for avoiding decision deadlock due to the conflicting nature of objective functions. Then, fuzzy goal programming approach is used for achieving the highest degree of each of the membership goal by minimizing negative deviational variables. We also provide sensitivity analysis with variation of tolerance values on decision vectors to show how the solution is sensitive to the change of tolerance values with the help of a numerical example.
Multilevel fractional programming,Fuzzy Goal Programming,Membership function,Tolerance values
http://jiei.azad.ac.ir/article_676430.html
http://jiei.azad.ac.ir/article_676430_0c74665cc1e82211ab8709895afb8321.pdf
Islamic Azad University, South Tehran Branch
Journal of Industrial Engineering, International
1735-5702
2251-712X
8
1
2012
01
01
Modeling the operational risk in Iranian commercial banks: case study of a private bank
EN
Omid
Momen
Karafarin Bank, Tehran, Iran
Alimohammad
Kimiagari
2Amirkabir University of Technology, Tehran, Iran
kimiagar@aut.ac.ir
Eaman
Noorbakhsh
Karafarin Bank, Tehran, Iran
The Basel Committee on Banking Supervision from the Bank for International Settlement classifies banking risks into<br /> three main categories including credit risk, market risk, and operational risk. The focus of this study is on the<br /> operational risk measurement in Iranian banks. Therefore, issues arising when trying to implement operational risk<br /> models in Iran are discussed, and then, some solutions are recommended. Moreover, all steps of operational risk<br /> measurement based on Loss Distribution Approach with Iran's specific modifications are presented. We employed<br /> the approach of this study to model the operational risk of an Iranian private bank. The results are quite reasonable,<br /> comparing the scale of bank and other risk categories.
Operational Risk,COPULA,Loss distribution approach,Bank
http://jiei.azad.ac.ir/article_676432.html
http://jiei.azad.ac.ir/article_676432_d305f9ba81a7a2f210598dca3f981495.pdf
Islamic Azad University, South Tehran Branch
Journal of Industrial Engineering, International
1735-5702
2251-712X
8
1
2012
01
01
Building a maintenance policy through a multi-criterion decision-making model
EN
Elahe
Faghihinia
Department of Industrial Engineering, Islamic Azad University of Najafabad,
Isfahan 8514143131, Iran
Naser
Mollaverdi
Department of Industrial Engineering, Isfahan University of Technology, Isfahan, 8415683111, Iran
A major competitive advantage of production and service systems is establishing a proper maintenance policy.<br /> Therefore, maintenance managers should make maintenance decisions that best fit their systems. Multi-criterion<br /> decision-making methods can take into account a number of aspects associated with the competitiveness factors<br /> of a system. This paper presents a multi-criterion decision-aided maintenance model with three criteria that have<br /> more influence on decision making: reliability, maintenance cost, and maintenance downtime. The Bayesian<br /> approach has been applied to confront maintenance failure data shortage. Therefore, the model seeks to make the<br /> best compromise between these three criteria and establish replacement intervals using Preference Ranking<br /> Organization Method for Enrichment Evaluation (PROMETHEE II), integrating the Bayesian approach with regard to<br /> the preference of the decision maker to the problem. Finally, using a numerical application, the model has been<br /> illustrated, and for a visual realization and an illustrative sensitivity analysis, PROMETHEE GAIA (the visual interactive<br /> module) has been used. Use of PROMETHEE II and PROMETHEE GAIA has been made with Decision Lab software. A<br /> sensitivity analysis has been made to verify the robustness of certain parameters of the model.
Preventive maintenance,Age-dependent PM policy,PROMETHEE II,bayesian approach,PROMETHEE GAIA
http://jiei.azad.ac.ir/article_676433.html
http://jiei.azad.ac.ir/article_676433_333636cab428db7acb0435ad85da1658.pdf
Islamic Azad University, South Tehran Branch
Journal of Industrial Engineering, International
1735-5702
2251-712X
8
1
2012
01
01
A seller-buyer supply chain model with exponential distribution lead time
EN
Mehrab
Bahri
Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, 14778, Iran
Mohammad
Jafar Tarokh
Department of Industrial Engineering, K.N. Toosi University of Technology,
Tehran 1439955471, Iran
Supply chain is an accepted way of remaining in the competition in today's rapidly changing market. This paper presents a coordinated seller-buyer supply chain model in two stages, which is called Joint Economic Lot Sizing (JELS) in literature. The delivery activities in the supply chain consist of a single raw material. We assume that the delivery lead time is stochastic and follows an exponential distribution. Also, the shortage during the lead time is permitted and completely back-ordered for the buyer. With these assumptions, the annual cost function of JELS is minimized. At the end, a numerical example is presented to show that the integrated approach considerably improves the costs in comparison with the independent decisions by seller and buyer.
Integrated inventory model,Stochastic lead time,Supply chain coordination,Cost,Optimization
http://jiei.azad.ac.ir/article_676434.html
http://jiei.azad.ac.ir/article_676434_5e550d340028c17ce645ab7a8827374e.pdf
Islamic Azad University, South Tehran Branch
Journal of Industrial Engineering, International
1735-5702
2251-712X
8
1
2012
01
01
Risk determinants of small and medium-sized manufacturing enterprises (SMEs) - an exploratory study in New Zealand
EN
Ariful
Islam
Department of Industrial and Production Engineering, Shahjalal University of
Science and Technology, Sylhet 3114, Bangladesh
Des
Tedford
Department of Mechanical Engineering, The University of Auckland, Auckland, 1142, New Zealand
The smooth running of small and medium-sized manufacturing enterprises (SMEs) presents a significant challenge irrespective of the technological and human resources they may have at their disposal. SMEs continuously encounter daily internal and external undesirable events and unwanted setbacks to their operations that detract from their business performance. These are referred to as ‘disturbances’ in our research study. Among the disturbances, some are likely to create risks to the enterprises in terms of loss of production, manufacturing capability, human resource, market share, and, of course, economic losses. These are finally referred to as ‘risk determinant’ on the basis of their correlation with some risk indicators, which are linked to operational, occupational, and economic risks. To deal with these risk determinants effectively, SMEs need a systematic method of approach to identify and treat their potential effects along with an appropriate set of tools. However, initially, a strategic approach is required to identify typical risk determinants and their linkage with potential business risks. In this connection, we conducted this study to explore the answer to the research question: what are the typical risk determinants encountered by SMEs? We carried out an empirical investigation with a multi-method research approach (a combination of a questionnaire-based mail survey involving 212 SMEs and five in-depth case studies) in New Zealand. This paper presents a set of typical internal and external risk determinants, which need special attention to be dealt with to minimize operational risks of an SME
SMEs,Disturbance,Risk,Risk determinants,Strategic risk management
http://jiei.azad.ac.ir/article_676435.html
http://jiei.azad.ac.ir/article_676435_f402bc9c05b61e7f69ac6fa10cb16eec.pdf
Islamic Azad University, South Tehran Branch
Journal of Industrial Engineering, International
1735-5702
2251-712X
8
1
2012
01
01
Solving the vehicle routing problem by a hybrid meta-heuristic algorithm
EN
Majid
Yousefikhoshbakht
Young Researchers Club, Hamedan Branch, Islamic Azad University,
Hamedan, Iran
Esmaile
Khorram
Faculty of Mathematics and Computer Science, Amirkabir University of Technology, Hafez Avenue, Tehran, Iran
The vehicle routing problem (VRP) is one of the most important combinational optimization problems that has nowadays received much attention because of its real application in industrial and service problems. The VRP involves routing a fleet of vehicles, each of them visiting a set of nodes such that every node is visited by exactly one vehicle only once. So, the objective is to minimize the total distance traveled by all the vehicles. This paper presents a hybrid two-phase algorithm called sweep algorithm (SW) + ant colony system (ACS) for the classical VRP. At the first stage, the VRP is solved by the SW, and at the second stage, the ACS and 3-opt local search are used for improving the solutions. Extensive computational tests on standard instances from the literature confirm the effectiveness of the presented approach.
Ant colony system,NP-hard Problems,Sweep Algorithm,Vehicle Routing Problem
http://jiei.azad.ac.ir/article_676436.html
http://jiei.azad.ac.ir/article_676436_a69cdc8e0fc7b15486ab43a3daed914f.pdf
Islamic Azad University, South Tehran Branch
Journal of Industrial Engineering, International
1735-5702
2251-712X
8
1
2012
01
01
Multi-objective design of fuzzy logic controller in supply chain
EN
Mahdi
Ghane
Mechatronics Department, K.N.Toosi University of Technology, Tehran, 19697 64499, Iran
Mohammad Jafar Tarokh
Jafar Tarokh
Industrial Engineering Department, K.N.Toosi University of Technology,
Tehran 19697 64499, Iran
Unlike commonly used methods, in this paper, we have introduced a new approach for designing fuzzy controllers. In<br /> this approach, we have simultaneously optimized both objective functions of a supply chain over a two-dimensional<br /> space. Then, we have obtained a spectrum of optimized points, each of which represents a set of optimal parameters<br /> which can be chosen by the manager according to the importance of objective functions. Our used supply chain model<br /> is a member of inventory and order-based production control system family, a generalization of the periodic review<br /> which is termed ‘Order-Up-To policy.’ An auto rule maker, based on non-dominated sorting genetic algorithm-II, has been<br /> applied to the experimental initial fuzzy rules. According to performance measurement, our results indicate the efficiency<br /> of the proposed approach.
Supply Chain,fuzzy logic controller,Multi-Objective Optimization
http://jiei.azad.ac.ir/article_676437.html
http://jiei.azad.ac.ir/article_676437_48fd4ccc7ef802d432c00fc32c620814.pdf
Islamic Azad University, South Tehran Branch
Journal of Industrial Engineering, International
1735-5702
2251-712X
8
1
2012
01
01
Locomotive assignment problem with train precedence using genetic algorithm
EN
Siamak
Noori
Department of Industrial Engineering, Iran University of Science and
Technology, Narmak, Tehran 16846-13114, Iran
Seyed Farid
Ghannadpour
Department of Industrial Engineering, Iran University of Science and Technology, Narmak, Tehran, 16846-13114, Iran
This paper aims to study the locomotive assignment problem which is very important for railway companies, in view of high cost of operating locomotives. This problem is to determine the minimum cost assignment of homogeneous locomotives located in some central depots to a set of pre-scheduled trains in order to provide sufficient power to pull the trains from their origins to their destinations. These trains have different degrees of priority for servicing, and the high class of trains should be serviced earlier than others. This problem is modeled using vehicle routing and scheduling problem where trains representing the customers are supposed to be serviced in pre-specified hard/soft fuzzy time windows.<br /> A two-phase approach is used which, in the first phase, the multi-depot locomotive assignment is converted to a set of single depot problems, and after that, each single depot problem is solved heuristically by a hybrid genetic algorithm. In the genetic algorithm, various heuristics and efficient operators are used in the evolutionary search. The suggested algorithm is applied to solve the medium sized numerical example to check capabilities of the model and algorithm. Moreover, some of the results are compared with those solutions produced by branch-and-bound technique to determine validity and quality of the model. Results show that suggested approach is rather effective in respect of quality and time.<br /> <br /> <br /> <br />
Locomotive assignment problem,Vehicle routing and scheduling,Fuzzy time windows,Genetic Algorithm
http://jiei.azad.ac.ir/article_676438.html
http://jiei.azad.ac.ir/article_676438_15e1707a3e2473ef01d8b51016776259.pdf
Islamic Azad University, South Tehran Branch
Journal of Industrial Engineering, International
1735-5702
2251-712X
8
1
2012
01
01
A population-based algorithm for the railroad blocking problem
EN
Masoud
Yaghini
School of Railway Engineering, Iran University of Science and Technology,
Tehran 16846-13114, Iran
Masoud
Seyedabadi
School of Railway Engineering, Iran University of Science and Technology, Tehran, 16846-13114, Iran
Mohamad M
Khoshraftar
School of Railway Engineering, Iran University of Science and Technology, Tehran, 16846-13114, Iran
Railroad blocking problem (RBP) is one of the problems that need an important decision in freight railroads. The objective of solving this problem is to minimize the costs of delivering all commodities by deciding which inter-terminal blocks to build and by specifying the assignment of commodities to these blocks, while observing limits on the number and cumulative volume of the blocks assembled at each terminal. RBP is an NP-hard combinatorial optimization problem with billions of decision variables. To solve the real-life RBP, developing a metaheuristic algorithm is necessary. In this paper, for the first time, a new genetic algorithm-based solution method, which is a population-based algorithm, is proposed to solve the RBP. To evaluate the efficiency and the quality of solutions of the proposed algorithm, several simulated test problems are used. The quality and computational time of the generated solutions for the test problems with the proposed genetic algorithm are compared with the solutions of the CPLEX software. The results show high efficiency and effectiveness of the proposed algorithm.
Railroad blocking problem,Genetic Algorithm,Budget design problem
http://jiei.azad.ac.ir/article_676439.html
http://jiei.azad.ac.ir/article_676439_1a9af61fdbbf472ddd7bb2de0c375321.pdf
Islamic Azad University, South Tehran Branch
Journal of Industrial Engineering, International
1735-5702
2251-712X
8
1
2012
01
01
Resource leveling scheduling by an ant colony-based model
EN
Mohsen
Garmsiri
MBA Program, Payame Noor University, Tehran, Iran
Mohammad Reza
Abassi
MBA Program, Payame Noor University, Tehran, Iran
In project scheduling, many problems can arise when resource fluctuations are beyond acceptable limits. To overcome this, mathematical techniques have been developed for leveling resources. However, these produce a hard and inflexible approach in scheduling projects. The authors propose a simple resource leveling approach that can be used in scheduling projects with multi-mode execution activities. In the mentioned approach, an ant algorithm determines the execution mode of each activity so that resource leveling index and project time become optimum. In the model, some visibility functions (defined in accordance with problem characteristics) are utilized, and the best, which return the best result, is selected for the model.
Ant colony optimization,Resource leveling,Visibility function
http://jiei.azad.ac.ir/article_676440.html
http://jiei.azad.ac.ir/article_676440_323d5e1dda35908e8d6f4df2157d7eae.pdf
Islamic Azad University, South Tehran Branch
Journal of Industrial Engineering, International
1735-5702
2251-712X
8
1
2012
01
01
Effective heuristics and meta-heuristics for the quadratic assignment problem with tuned parameters and analytical comparisons
EN
Mahdi
Bashiri
Department of Industrial Engineering, Shahed University, Tehran 3319118651,
Iran
Hossein
Karimi
Department of Industrial Engineering, Shahed University, Tehran, 3319118651, Iran
Quadratic assignment problem (QAP) is a well-known problem in the facility location and layout. It belongs to the<br /> NP-complete class. There are many heuristic and meta-heuristic methods, which are presented for QAP in the<br /> literature. In this paper, we applied 2-opt, greedy 2-opt, 3-opt, greedy 3-opt, and VNZ as heuristic methods and<br /> tabu search (TS), simulated annealing, and particle swarm optimization as meta-heuristic methods for the QAP. This<br /> research is dedicated to compare the relative percentage deviation of these solution qualities from the best known<br /> solution which is introduced in QAPLIB. Furthermore, a tuning method is applied for meta-heuristic parameters.<br /> Results indicate that TS is the best in 31% of QAPs, and the IFLS method, which is in the literature, is the best in 58<br /> % of QAPs; these two methods are the same in 11% of test problems. Also, TS has a better computational time<br /> among heuristic and meta-heuristic methods.
quadratic assignment problem,Heuristics,Meta-heuristics,Tuning method
http://jiei.azad.ac.ir/article_676441.html
http://jiei.azad.ac.ir/article_676441_3e4cf8fb85f693fc7267a69cf98012e1.pdf
Islamic Azad University, South Tehran Branch
Journal of Industrial Engineering, International
1735-5702
2251-712X
8
1
2012
01
01
An investigation of model selection criteria for technical analysis of moving average
EN
Milad
Jasemi
Department of Industrial Engineering, Islamic Azad University, Masjed
Soleyman Branch, Masjed Soleyman, 61649, Iran
Ali M
Kimiagari
Department of Industrial Engineering, Amirkabir University of Technology, Tehran, 15914, Iran
Moving averages are one of the most popular and easy-to-use tools available to a technical analyst, and they also<br /> form the building blocks for many other technical indicators and overlays. Building a moving average (MA) model<br /> needs determining four factors of (1) approach of issuing signals, (2) technique of calculating MA, (3) length of MA,<br /> and (4) band. After a literature review of technical analysis (TA) from the perspective of MA and some discussions<br /> about MA as a TA, this paper is structured to highlight the effects that each of the first three factors has on<br /> performance of MA as a TA. The results that based on some experiments with real data support the fact that<br /> deciding about the first and second factors is not much critical, and more attention should be paid to other factors.
moving average,Technical Analysis,Trend forecasting,Investment decision,Portfolio Selection
http://jiei.azad.ac.ir/article_676442.html
http://jiei.azad.ac.ir/article_676442_d5b15a59d09e030c88ab82ba0beab3cb.pdf
Islamic Azad University, South Tehran Branch
Journal of Industrial Engineering, International
1735-5702
2251-712X
8
1
2012
01
01
A hybrid meta-heuristic algorithm for the vehicle routing problem with stochastic travel times considering the driver's satisfaction
EN
Reza
Tavakkoli-Moghaddam
0000-0002-6757-926X
Department of Industrial Engineering, College of Engineering, University of
Tehran, Tehran, Iran
tavakoli@ut.ac.ir
Mehdi
Alinaghian
Department of Industrial and Systems Engineering, Isfahan University of Technology, Isfahan, Iran
Alireza
Salamat-Bakhsh
Department of Industrial Engineering, Tehran South Branch, Islamic Azad University Tehran, Iran
Narges
Norouzi
Department of Industrial Engineering, College of Engineering, University of
Tehran, Tehran, Iran
A vehicle routing problem is a significant problem that has attracted great attention from researchers in recent years. The main objectives of the vehicle routing problem are to minimize the traveled distance, total traveling time, number of vehicles and cost function of transportation. Reducing these variables leads to decreasing the total cost and increasing the driver's satisfaction level. On the other hand, this satisfaction, which will decrease by increasing the service time, is considered as an important logistic problem for a company. The stochastic time dominated by a probability variable leads to variation of the service time, while it is ignored in classical routing problems. This paper investigates the problem of the increasing service time by using the stochastic time for each tour such that the total traveling time of the vehicles is limited to a specific limit based on a defined probability. Since exact solutions of the vehicle routing problem that belong to the category of NP-hard problems are not practical in a large scale, a hybrid algorithm based on simulated annealing with genetic operators was proposed to obtain an efficient solution with reasonable computational cost and time. Finally, for some small cases, the related results of the proposed algorithm were compared with results obtained by the Lingo 8 software. The obtained results indicate the efficiency of the proposed hybrid simulated annealing algorithm.
Vehicle Routing Problem,Stochastic travel times,Driver's satisfaction,Simulated Annealing
http://jiei.azad.ac.ir/article_676443.html
http://jiei.azad.ac.ir/article_676443_6dccef14182b1f031bcc74875a959f07.pdf
Islamic Azad University, South Tehran Branch
Journal of Industrial Engineering, International
1735-5702
2251-712X
8
1
2012
01
01
A hybrid algorithm optimization approach for machine loading problem in flexible manufacturing system
EN
Vijay M
Kumar
Department of Mechanical Engineering, JSS Academy of Technical
Education, Bangalore, 560 060, India
ANN
Murthy
JSS Academy of Technical Education, Bangalore, 560 060, India
K
Chandrashekara
Sri Jayachamarajendra College of Engineering, Mysore, 570 006, India
The production planning problem of flexible manufacturing system (FMS) concerns with decisions that have to be made before an FMS begins to produce parts according to a given production plan during an upcoming planning horizon. The main aspect of production planning deals with machine loading problem in which selection of a subset of jobs to be manufactured and assignment of their operations to the relevant machines are made. Such problems are not only combinatorial optimization problems, but also happen to be non-deterministic polynomial-time-hard, making it difficult to obtain satisfactory solutions using traditional optimization techniques. In this paper, an attempt has been made to address the machine loading problem with objectives of minimization of system unbalance and maximization of throughput simultaneously while satisfying the system constraints related to available machining time and tool slot designing and using a meta-hybrid heuristic technique based on genetic algorithm and particle swarm optimization. The results reported in this paper demonstrate the model efficiency and examine the performance of the system with respect to measures such as throughput and system utilization.
Flexible manufacturing system,Production Planning,Loading,Hybrid algorithm optimization
http://jiei.azad.ac.ir/article_676444.html
http://jiei.azad.ac.ir/article_676444_db950a9019225e1471adbdc46cf0f1cc.pdf
Islamic Azad University, South Tehran Branch
Journal of Industrial Engineering, International
1735-5702
2251-712X
8
1
2012
01
01
Analysis of M/G/ 1 queueing model with state dependent arrival and vacation
EN
Charan
Jeet Singh
Department of Mathematics Guru Nanak Dev University, Amritsar, Punjab,
143005, India
Madhu
Jain
Department of Mathematics, Indian Institute of Technology, Roorkee, Roorkee, Uttarakhand, 247667, India
Binay
Kumar
Department of Mathematics, M.L.U. DAV College, Phagwara, Punjab, 144402, India
This investigation deals with single server queueing system wherein the arrival of the units follow Poisson process with varying arrival rates in different states and the service time of the units is arbitrary (general) distributed. The server may take a vacation of a fixed duration or may continue to be available in the system for next service. Using the probability argument, we construct the set of steady state equations by introducing the supplementary variable corresponding to elapsed service time. Then, we obtain the probability generating function of the units present in the system. Various performance indices, such as expected number of units in the queue and in the system, average waiting time, etc., are obtained explicitly. Some special cases are also deduced by setting the appropriate parameter values. The numerical illustrations are provided to carry out the sensitivity analysis in order to explore the effect of different parameters on the system performance measures.
State dependent,Queue,Arbitrary service time,Vacation,Supplementary variable,Average Queue Length
http://jiei.azad.ac.ir/article_676445.html
http://jiei.azad.ac.ir/article_676445_64a253f0b2cc55f8d7980f1fdbe29e9b.pdf
Islamic Azad University, South Tehran Branch
Journal of Industrial Engineering, International
1735-5702
2251-712X
8
1
2012
01
01
Performance enhancement for crystallization unit of a sugar plant using genetic algorithm technique
EN
P C
Tewari
Department of Mechanical Engineering, National Institute of Technology, Kurukshetra, Haryana, 136119, India
Rajiv
Khanduja
Department of Mechanical Engineering, Seth Jai Parkash Mukand Lal
Institute of Engineering and Technology (JMIT), Radaur, Yamuna Nagar,
Haryana135133, India
Mahesh
Gupta
Department of Mechanical Engineering, National Institute of Technology, Kurukshetra, Haryana, 136119, India
This paper deals with the performance enhancement for crystallization unit of a sugar plant using genetic<br /> algorithm. The crystallization unit of a sugar industry has three main subsystems arranged in series. Considering<br /> exponential distribution for the probable failures and repairs, the mathematical formulation of the problem is done<br /> using probabilistic approach, and differential equations are developed on the basis of Markov birth-death process.<br /> These equations are then solved using normalizing conditions so as to determine the steady-state availability of the<br /> crystallization unit. The performance of each subsystem of crystallization unit in a sugar plant has also been<br /> optimized using genetic algorithm. Thus, the findings of the present paper will be highly useful to the plant<br /> management for the timely execution of proper maintenance decisions and, hence, to enhance the system<br /> performance.
Performance Enhancement,Crystallization unit,Genetic Algorithm
http://jiei.azad.ac.ir/article_676446.html
http://jiei.azad.ac.ir/article_676446_444bfe5dd1d791fe25495d1283efbe84.pdf