Solving an one-dimensional cutting stock problem by simulated annealing and tabu search


1 Department of Industrial Engineering, Khomein Branch, Islamic Azad University, Khomein, Iran

2 Department of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran

3 Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran


A cutting stock problem is one of the main and classical problems in operations research that is modeled as Lp < /div>
problem. Because of its NP-hard nature, finding an optimal solution in reasonable time is extremely difficult and at
least non-economical. In this paper, two meta-heuristic algorithms, namely simulated annealing (SA) and tabu
search (TS), are proposed and developed for this type of the complex and large-sized problem. To evaluate the
efficiency of these proposed approaches, several problems are solved using SA and TS, and then the related results
are compared. The results show that the proposed SA gives good results in terms of objective function values
rather than TS.