Integrated inventory-distribution planning in a (1:N) supply chain system with heterogeneous vehicles incorporated

Abstract

This thesis deals with an integrated inventory-distribution problem with a fleet of heterogeneous vehicles where a single warehouse distributes a single type of product to many spatially distributed retailers to meet their non-stationary deterministic demands. The problem is formulated as an MIP (Mixed Integer Programming) with the objective function which is to minimize the sum of inventory holding cost, transportation cost and ordering cost at the warehouse, subject to inventory-balancing constraints, ordering related constraints, vehicle capacity constraints and transportation time constraints. The problem is proven to be NP-hard so that the Lagrangean relaxation method is applied to propose a Lagrangean heuristic. To test the effectiveness and efficiency of the proposed algorithm, computational experiments are performed with some numerical instances. The experiment results show that the proposed algorithm give relatively good solutions within a reasonable time.