Increasing global competition in the business world and heightened expectations of customers have forced companies to consider not only the pricing or product quality, but reliability and timeliness of the deliveries as well. In manufacturing-centric industries such as automotive and electronics, distribution and inventory costs constitute the second and third largest cost components following the production costs. Therefore, industrial and logistics companies need to continuously search for ways to lower the inventory level and distribution cost. This trend has created a closer interaction between the different stages of a supply chain, and increased the practical usefulness of the integrated models.This thesis considers two categories of integrated scheduling problems. One is Integrated Scheduling of Production-Distribution-Inventory problems (ISPDI problems) and the other is Integrated Scheduling of Production-Inventory-Distribution-Inventory problems (ISPIDI problems). Jobs are first processed on a single machine in the production stage, and then delivered to a pre-specified customer by a capacitated transporter. Each job has a distinct due date, and must be delivered to customer before this due date. Each production batch requires a setup cost and a setup time before the first job of this batch is processed. Each round trip between the factory and customer requires a delivery cost as well as a delivery time. Moreover, it is assumed that a job which is completed before its departure date or delivered to the customer before its due date will incur a corresponding inventory cost. Our objective is to minimize the total cost involving setup, inventory and delivery costs while guaranteeing a certain customer service level.For ISPDI problems, we firstly provide a mixed integer programming model for the case of multi-product, single-stage situation, and develop an improved Genetic algorithm (GA) for solving it. Then, we extend this model to a single-product, multi-stage model, and provide two methods, dominance-related greedy algorithm and GA, for solving it. For ISPIDI problems, we establish a general non-linear model for the case of single-product situation and devise a special case from the general model. Then we provide an optimality property between the production and delivery schedules for the special case. Finally, a heuristic approach is developed for solving it. For each problem under study, in order to evaluate the performance of the proposed algorithms, some interesting lower bounds on the corresponding objective functions are established according to different methods such as Lagrangian relaxation method, classical bin-packing based method. Computational results show the efficiency of the proposed models and algorithms in terms of solution quality and running time.
| Identifer | oai:union.ndltd.org:CCSD/oai:tel.archives-ouvertes.fr:tel-00720660 |
| Date | 26 April 2012 |
| Creators | Wang, Deyun |
| Publisher | Université de Technologie de Belfort-Montbeliard |
| Source Sets | CCSD theses-EN-ligne, France |
| Language | French |
| Detected Language | English |
| Type | PhD thesis |
Page generated in 0.0016 seconds