A Multi‐Objective Discrete Particle Swarm Optimisation Algorithm for supply chain network design

Strategic supply chain network optimisation is significant, as it involves long‐term decisions with conflicting goals. It is an NP‐hard problem and researchers are constantly attempting to use meta‐heuristics as a solution approach. In this paper, a Multi‐Objective Discrete Particle Swarm Algorithm (MODPSA) is proposed to optimise the supply chain network with the objectives of minimisation of supply chain cost, minimisation of demand fulfilment lead time and maximisation of volume flexibility. Two different global guide selection techniques are implemented in the proposed algorithm. Numerical tests are conducted using the real‐life data of a farm equipment manufacturer and the computational analyses are performed on two stages. In the first stage, the performance of two global guide selection techniques are evaluated and in the second stage the proposed MODPSA is compared with Non‐dominated Sorting Genetic Algorithm‐II (NSGA II). The results indicate that the proposed approach is effective in producing high‐quality Pareto‐optimal solutions.