MULTICRITERIA TRADEOFFS IN INVENTORY CONTROL USING MEMETIC PARTICLE SWARM OPTIMIZATION

作者：Hsu Chin Hsiung; Tsou Ching Shih^*; Yu Fong Jung

来源：International Journal of Innovative Computing Information and Control, 2009, 5(11A): 3755-3768.

• Inventory control
• Multicriteria optimization
• Particle swarm optimization
• Memetic algorithms

Inventory control is actually a multicriteria optimization problem. It needs to identify some tradeoff alternatives in which no one excels the others in all criteria related to operating cost and customer service. In this paper, we present a Pareto memetic algorithm based on Particle Swarm Optimization (PSO) to tackle a multicriteria (r, Q) system with lost sales. The approach proposed is intrinsically multicriteria, not only in its formulation but also in the computing method. It can simultaneously determine order quantity and safety stock without the need to estimate stockout cost or service level. The memetic design keeps the benefits of evolutionary algorithms and local search heuristics in a single optimization method. Experimental results show that the proposed method can generate more accurate and diverse nondominated control. policies than the Strength Pareto Evolutionary Algorithm (SPEA) and, in general, provide the entire picture of optimal cost-service tradeoff such that more information is disclosed to decision makers.

• 出版日期2009-11
• 单位苏州大学