A Heuristic Based on PSO for Irregular Cutting Stock Problem

Cutting Stock Problems (CSP) arise in many production industries where large stock sheets must be cut into smaller pieces. An irregular-shaped nesting approach for two-dimensional cutting stock problem is constructed in this research. We present a heuristic based on Particle Swarm Optimization Algorithm (PSO) for irregular-shaped two-dimensional cutting stock problem, where PSO is utilized to search optimal solution. Furthermore, the proposed approach combines a grid approximation method with Bottom-Left-Fill heuristic placement strategy to allocate irregular items. We evaluate the proposed approach using 15 revised benchmark problems available from the EURO Special Interest Group on Cutting and Packing. The performance illustrates the effectiveness and efficiency of our approach in solving irregular cutting stock problems.