A hybrid ant colony algorithm for the Cutting Stock Problem

This study presents a new hybrid ant colony algorithm (HACO) to solve an in integer linear programming formulation of the Cutting Stock Problem(CSP). The CSP is an important class combinatorial problem. It is appropriate to minimize the raw material used by industries for fulfilling customer's demands. In such cases, classic models for solving the cutting stock problem are useless. HACO consists of GDCP procedure and modified ACO (MACO). GDCP procedure provides dominative cutting patterns as MACO solution components, in MACO the pheromone trail is put on cutting patterns instead of items. MACO preserves cutting patterns and frequencies information under ants building solution procedure. Results obtained from computational experiments for ten benchmarks demonstrate that the performance of MACO is compared to that obtained using existing mete-heuristic algorithm.