Scheduling in assembly type job-shops

Assembly type job-shop scheduling is a generalization of the job-shop scheduling problem to include assembly operations. In the assembly type job-shops scheduling problem, there are n jobs which are to be processed on in workstations and each job has a due date. Each job visits one or more workstations in a predetermined route. The primary difference between this new problem and the classical job-shop problem is that two or more jobs can merge to foul\u27 a new job at a specified workstation, that is job convergence is permitted. This feature cannot be modeled by existing job-shop techniques. In this dissertation, we develop scheduling procedures for the assembly type job-shop with the objective of minimizing total weighted tardiness. Three types of workstations are modeled: single machine, parallel machine, and batch machine. We label this new scheduling procedure as SB. The SB procedure is heuristic in nature and is derived from the shifting bottleneck concept. SB decomposes the assembly type job-shop scheduling problem into several workstation scheduling sub-problems. Various types of techniques are used in developing the scheduling heuristics for these sub-problems including the greedy method, beam search, critical path analysis, local search, and dynamic programming. The performance of SB is validated on a set of test problems and compared with priority rules that are normally used in practice. The results show that SB outperforms the priority rules by an average of 19% - 36% for the test problems. SB is extended to solve scheduling problems with other objectives including minimizing the maximum completion time, minimizing weighted flow time and minimizing maximum weighted lateness. Comparisons with the test problems, indicate that SB outperforms the priority rules for these objectives as well. The SB procedure and its accompanying logic is programmed into an object oriented scheduling system labeled as LEKIN. The LEKIN program includes a standard library of scheduling rules and hence can be used as a platform for the development of new scheduling heuristics. In industrial applications LEKIN allows schedulers to obtain effective machine schedules rapidly. The results from this research allow us to increase shop utilization, improve customer satisfaction, and lower work-in-process inventory without a major capital investment

ORDONNANCEMENT EN TEMPS REEL DANS LES PROBLEMES A EN-COURS LIMITES

In this thesis, a production system with two characteristic is considered. First, the processing time of an operation to be performed in a given time interval can be selected. Such a production system is said to have controllable processing times. Second, the operations of a product follow each other without waiting. A production system having this characteristic is said to be no-wait. The two characteristics are key in scheduling of many different types of industrial systems. The proposed methodology allows one to control the work-in-process and production cycle time. The system productivity is optimised with original algorithms developed in this research. The analysis of computational complexity of the seventeen algorithms shows that they can be used for on-line scheduling.Dans cette thèse, nous montrons l'intérêt d'étudier des systèmes de production présentant les deux caractéristiques suivantes. Tout d'abord, les durées des opérations à réaliser sont choisies dans des intervalles donnés -de tels systèmes de gestion de fabrication sont dits à temps opératoires contrôlables-. De plus, les opérations successives réalisées sur chaque produit se suivent sans temps d'attente -de tels systèmes sont dits sans attente-.Ces deux caractéristiques permettent de gérer en temps réel un large éventail de systèmes de fabrication. En outre, cette approche permet le contrôle des en-cours et des temps de fabrication.La production du système de fabrication est optimisée grâce à des algorithmes originaux. L'analyse de la complexité des dix-sept algorithmes proposés prouvent leur compatibilité avec leur utilisation en temps réel