Optimization for Intelligent Operation of Supply Chains

The schedule for manufacturing and its delivery should be strategically determined to maintain economic and sustainable management of a supply chain. However, most of existing design models for the supply chain assumes that it is known or pre-specified when products are manufactured and delivered, and therefore, only the amount of products and delivery are of interest to optimize within design frameworks. In order to provide high flexibility and cost-effectiveness in manufacturing and supply chain activities, both timing information (i.e., when to produce and deliver) and capacity (i.e., how much to produce and deliver) need to be considered simultaneously. New MILP (mixed integer linear programming) model for the design and optimization of the supply chain has been proposed, in which these two key decision variables are simultaneously optimized. For dealing with computational difficulties resulted from the large-size problem, a sequentially-updating procedure is also proposed. In this sequentially-updating procedure, the whole distribution network is divided into subsystems and optimized interactively within iterative procedure, where each subsystem is sequentially optimized until no profit improvement is observed. The enhanced flexibility of the supply chain can be obtained from this improved design philosophy. This also ensures reliable and robust responsiveness of the supply chain to customers' demand without sacrificing efficiency and/or cost-effectiveness of manufacturing and delivery activities. Illustrated case studies show that the proposed method is able to deal with large and complex supply chain problems with significant cost savings.