An improved tabu search approach with mixed objective function for one-dimensional cutting stock problems

In this paper, a methodology with both efficiency and effectiveness of using improved tabu search approach is applied successfully to solve one-dimensional cutting stock problem (1D-CSP). By introducing a varying mixed objective function, the chance of obtaining optimum solution in solving 1D-CSP, which is treated as a sequence problem, has increased. The total incentive trim loss, which functions as an incentive term in this paper, makes it possible to obtain good 1D-CSP results through the use of the new proposed TS approach. After testing against actual sample cases from shipyards and literatures, the solutions obtained from the proposed algorithm are superior. Computational results indicate that the methodology proposed outperforms the ones from other meta-heuristic methods.