An improved metaheuristic approach for solving the machine loading problem in flexible manufacturing systems

Production planning in Flexible Manufacturing Systems (FMSs) requires several hierarchical issues to be resolved sequentially or simultaneously. Loading is one of the vital issues in FMS production planning. It deals with the assignment of the necessary operations and tools among various machines in an optimal manner to minimise system unbalance under technological constraints. Such a problem is combinatorial in nature and found to be NP‐complete; thus, finding the exact solutions is computationally intractable for large‐scale problems. Therefore, in this study, a metaheuristic approach based on Particle Swarm Optimisation (PSO) has been proposed to solve the machine loading problem. Mutation has been introduced in PSO in a novel way so that the trapping of solutions at local minima can be avoided. The comparative study of the proposed algorithm with existing methods for ten benchmark instances available in the literature suggests that the results obtained in the proposed algorithm are quite encouraging.