Evolutionary algorithms for optimal operating parameters of vendor managed inventory systems in a two-echelon supply chain

Authors:
Goh Sue-Ann;S. G. Ponnambalam;N. Jawahar
Affiliations:
School of Engineering, Monash University Sunway Campus, 46150 Bandar Sunway, Malaysia;School of Engineering, Monash University Sunway Campus, 46150 Bandar Sunway, Malaysia;Department of Mechanical Engineering, Thiagarajar College of Engineering, Madurai, India
Venue:
Advances in Engineering Software
Year:
2012

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Abstract

This paper focuses on the operational issues of a Two-echelon Single-Vendor-Multiple-Buyers Supply chain (TSVMBSC) under vendor managed inventory (VMI) mode of operation. The operational parameters for TSVMBSC model are: sales quantity and sales price that determine the channel profit of the supply chain, and contract price between the vendor and the buyer, which depends upon the understanding between the partners on their revenue sharing. The optimal sales quantity for each buyer in TSVMBC is determined using a mathematical model available in the literature. The optimal sales price, the optimal channel profit and contract price between the vendor and buyer are determined based on the optimal sales quantity determined. Particle Swarm Optimization (PSO) and a hybrid of Genetic Algorithm and Artificial Immune System (GA-AIS) are proposed to solve this TSVMBSC problem. These two algorithms are evaluated for their solution quality. The robustness of the algorithms with their parameters are also analyzed and presented.