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The distribution decision is a complicated constrained optimisation problem that plays a key role in the production planning and inventory scheduling at the current era of intelligent big data, since few studies have developed new models integrating intelligent supply chain management. With the aim at the limitation of traditional methods which are difficult to obtain feasible solutions in large-scale search space with limited time, a new swarm activity-based intelligent optimisation algorithm, called PSO-SAW, is reconstructed in this paper by improving the particle swarm optimisation (PSO). The methodology is validated through several benchmarks and experimental applications to some distribution decision problems adopted from the literatures. Empirical results have implied the feasibility, effectiveness and robustness of the proposed method. Moreover, the experimental results of the algorithm have also verified the promising performances and applicability to distribution decision problems by comparing with other considered stochastic algorithms.
International Journal of Automation and Control – Inderscience Publishers
Published: Jan 1, 2022
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