Approximating Tradeoff Surfaces for Inventory Control through Evolutionary Multi-Objective Optimization

摘要

The optimal tradeoff surface in inventory control is useful in quantifying exactly what the firm must pay in terms of workload and investment to meet the customer service objective. Insight from the oldest inventory model, economic order quantity (EOQ), reveals that efficiency-service tradeoff should be recast into a multi-objective context In this paper, a nonredundant triobjective inventory control model and corresponding solution approach based on Lagrange method are presented to obtain nondominated control policies achieving tradeoffs among objectives. Evolutionary computation, NSGA-II, is also used to build the optimal tradeoff surface under stochastic demand. Results show that NSGA-II is highly competitive with the lengthy successive approximation in terms of accuracy and diversity. It can provide more tradeoff options to the decision makers.