Logistics supply chain management based on multi-constrained combinatorial optimization and extended simulated annealing

Abstract

Logistics supply chain management has become more and more important for modern businesses. For the major retailing corporations, logistics supply chain management has become part of the senior management agenda in the manufacturing and retailing industries. One main issue of logistics supply chain management is to find suitable optimized design mechanisms when a corporation decides to open and operate its warehouses and cross-docks and expend huge financial sums to open its best set of cross-docks and warehouses. After the corporation has opened and operated its warehouses and cross-docks, the other main issue of logistics supply chain management is the effective operating management of the logistical supply chain processes that are controlled by various independent companies in order to achieve overall minimal cost. The model of such logistics supply chain optimized design and operating management mechanisms is established through the multi-constrained combinatorial optimization expression in this paper. Novel schemes based on multi-constrained combinatorial optimization and extended simulated annealing are proposed to efficiently solve the logistics supply chain management problem. Numerical examples are used to show the validity of the proposed schemes.