Integrated design and inventory control in a three-level supply chain network

Abstract

This thesis considers integrated network design and inventory control problems for a three-level supply chain network composed of multiple number of suppliers, distribution centers (DC`s), and retailers, where risk-pooling strategy is considered under random demand and random supply environment. Specifically, this thesis studies models and its solution algorithms for three kinds of the integrated location-inventory models with risk-pooling strategy subject to various conditions associated with capacity restriction and the variability of order lead time; and also investigates the cost-saving effects of the integrated network design and inventory control decisions compared with conventional separate decision approaches. Chapter 2 deals with an integrated decision problem for network design and inventory control in a three-level supply chain network, where the risk-pooling strategy is considered at DC’s but finite capacity restrictions are imposed on suppliers and DC’s. Order lead times between the DC`s and the suppliers are deterministic and identical for all DC-to-supplier pairs. The objective of the problem is to determine the number and locations of the suppliers and the DC`s, the amount of products delivered from the suppliers to the DC`s, and the assignment of each retailer to one of the DC`s. The problem is formulated as a nonlinear mixed-integer programming model, for which a two-phase heuristic solution algorithm is derived based on the Lagrangian relaxation (LR) approach. Numerical experiments show that the proposed solution algorithm is very effective and also efficient, and that significant saving can be made in total cost by integrating the network design and the inventory control decisions, especially under various situations including high holding costs, long order lead times, high service level, and highly variable customer demands. Chapter 3 deals with a three-level single-sourcing network design problem with the risk-pooling strategy at the D...