Logistics scheduling models in supply chain management

Abstract

This thesis considers logistics scheduling problems in supply chain management. They include logistics scheduling problems for coordination between job sequencing at a production stage and job delivery at its subsequent delivery stage under supply chain environment. In the analysis, the problem complexities are characterized. For example, if the problems are proved to be solvable in polynomial time, then the associated optimal polynomial algorithms are derived. Otherwise, if the problems are NP-hard, then the associated solution properties are characterized, based on which efficient heuristic algorithms are derived. Three logistics scheduling problems are considered in this thesis. The first problem is concerned with a logistics scheduling problem with stage-dependent inventory holding costs incorporated. In the problem, jobs are processed on a single machine and delivered by a capacitated vehicle to a single customer. The objective is to find a schedule to minimize the total weighted cost of the associated WIP inventory, finished product inventory and delivery, where inventory costs are characterized in terms of weighted flowtime and the delivery cost is proportional to the required number of delivery batches. It is proved that the problem is NP-hard in the strong sense and some solution properties are characterized. Thereupon, two heuristic algorithms are derived. To test the effectivenesses of the two derived heuristic algorithms, a lower bound based on the Lagrangian relaxation technique is derived. Numerical experiments are conducted to evaluate performance of the derived heuristic algorithms, which shows that the heuristic algorithms work quite well. The second and third problems are concerned with logistics scheduling problems with outsourcing allowed where each job can be either delivered via in-house vehicles or outsourced through outside delivery. They are concerned with due date related measures and inventory holding costs, respectively. The objec...