Some Models for Inbound Logistics and Supply Chain Management

This thesis consists of three models related to inbound logistics and supply chain management. The first model is one variation of the inbound logistics scheduling problem that was studied in the literature. In the problem, a workshop procures raw materials from one supplier to process a set of given jobs each having some amount of raw material requirement. The problem is unique in that raw material replenishment can only be done at some periodic time points. The workshop needs to make a sequencing decision to process the jobs together with a raw material replenishment decision to make sure raw material is available to process each job. The objective function is to minimize the total raw material holding cost and transportation setup cost of all jobs. We prove that the problems are NP-hard in the strong sense, even for some restrictive special cases. Then based on the classical LPT and WSPT policies, we develop efficient heuristics which have proven worst-case bounds and turn out to perform well in the computational study.;In the second problem, we reinvestigate the classical dynamic lot-sizing (DLS) model, under a new setting of decentralized decision making. Different from the traditional research focus which is on the optimal ordering policy for the manufacturer, we consider the optimal transportation pricing decision for the third-party logistics (3PL) that is in charge of the raw material transportation process in the supply chain. By separating the manufacturer's transportation cost from other costs, we are able to derive the manufacturer's optimal ordering policy, and hence the 3PL's profit, as direct functions of the 3PL's pricing decision. This leads to a Stackelberg game led by the 3PL. We show how the 3PL can maximize his profit by the pricing decision, and conduct numerical studies to explore the impact of such a game setting on the supply chain system.;The third model is about a DLS where the manufacturer has a capacity constraint. When the demand exceeds the capacity, the manufacturer also has an option of enhancing his inbound capacity by using a subcontractor. We focus on how the subcontractor can maximize his profit by an optimal pricing decision. This requires the subcontractor to know the best response of the manufacturer's subcontracting decision. We provide a pseudo-polynomial time algorithm to decide the optimal price by utilizing some properties and investigate conditions where a discount subcontracting price is more likely to benefit both sides simultaneously.