Author: Nutthapol Asadathorn Publisher: ISBN: Category : Production control Languages : en Pages : 454
Book Description
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' 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.
Author: Tse-Chiu Wong Publisher: Open Dissertation Press ISBN: 9781361476055 Category : Languages : en Pages :
Book Description
This dissertation, "An Evolutionary Algorithm Approach for Assembly Job Shop Scheduling With Lot Streaming Technique" by Tse-chiu, Wong, 黃資超, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Abstract of thesis entitled "An Evolutionary Algorithm Approach for Assembly Job Shop Scheduling with Lot Streaming Technique" Submitted by Wong Tse Chiu for the degree of Doctor of Philosophy at The University of Hong Kong in December 2007 Considerable efforts have been made by many manufacturing practitioners and researchers in recent years to solve Production and Scheduling Problems (PSPs). To solve PSPs, decision makers need to optimize the system objectives and satisfy the system constraints within a practical time limit. In this connection, a number of evolutionary approaches have been developed in this field. The Job Shop Scheduling Problem (JSSP) is one of the better-known PSPs, in which jobs are processed on machines in distinct orders. To solve a JSSP, the job processing sequence on each machine should be determined with respect to the objective functions. In fact, the classical JSSP is simplified by a number of system assumptions. One assumption is ii that a job cannot be split. Generally, a job is defined as a batch of identical items and it can only be transferred to the next machine once the whole batch has been processed. If a job is not allowed to be split, its next operation cannot be started even some items of the batch have already been processed. To relax this assumption, decision makers eventually need to decide for each job: (1) Whether the job will be split; (2) the sub-job number; and (3) the size of each sub-job. This technique is called Lot Streaming (LS). LS is defined as the process of splitting jobs into smaller sub-jobs so that successive operations of the same job can be overlapped on different machines. Nevertheless, insufficient LS models have been dedicated to JSSP. Another assumption of the classical JSSP is that there is no assembly stage. In other words, each job in JSSP is independent. If an assembly stage is appended to JSSP, the problem then becomes the Assembly Job Shop Scheduling Problem (AJSSP). In this study, the application of LS is for the first time extended to the AJSSP. As the potential of employing LS to the AJSSP has not been fully studied, an intelligent evolutionary algorithm is proposed and examined. The application of LS to JSSP is investigated first. Accordingly, an evolutionary algorithm is proposed. The research problem is divided into Sub-Problem One (SP1) and Sub-Problem Two (SP2). SP1 is defined as the determination of three LS conditions and SP2 is defined as JSSP after LS conditions have been determined. Different system parameters such as 3-level processing time range, 5-level setup time range, and 4-level system congestion index are examined. The computational results are obtained and discussed. Next, the application of LS is extended to the AJSSP. In iii this connection, the problem is considered in three parts: (a) Part I, on a simplified AJSSP; (b) Part II, on an AJSSP with 4-level part sharing; and (c) Part III, on an AJSSP with 4-level part sharing, 4-level system congestion index, and 2-level resource constraints. Correspondingly, the evolutionary algorithm is modified and improved in terms of optimization powers and computational effort. The computational results are obtained and discussed. ____________________________________________________________________ iv DOI: 10.5353/th_b3963446 Subjects: Genetic algorithms
Author: Kenneth R. Baker Publisher: John Wiley & Sons ISBN: 1118626257 Category : Business & Economics Languages : en Pages : 407
Book Description
An up-to-date and comprehensive treatment of the fundamentals of scheduling theory, including recent advances and state-of-the-art topics Principles of Sequencing and Scheduling strikes a unique balance between theory and practice, providing an accessible introduction to the concepts, methods, and results of scheduling theory and its core topics. With real-world examples and up-to-date modeling techniques, the book equips readers with the basic knowledge needed for understanding scheduling theory and delving into its applications. The authors begin with an introduction and overview of sequencing and scheduling, including single-machine sequencing, optimization and heuristic solution methods, and models with earliness and tardiness penalties. The most current material on stochastic scheduling, including correct scheduling of safety time and the use of simulation for optimization, is then presented and integrated with deterministic models. Additional topical coverage includes: Extensions of the basic model Parallel-machine models Flow shop scheduling Scheduling groups of jobs The job shop problem Simulation models for the dynamic job shop Network methods for project scheduling Resource-constrained project scheduling Stochastic and safe scheduling Extensive end-of-chapter exercises are provided, some of which are spreadsheet-oriented, and link scheduling theory to the most popular analytic platform among today's students and practitioners—the Microsoft Office Excel® spreadsheet. Extensive references direct readers to additional literature, and the book's related Web site houses material that reinforces the book's concepts, including research notes, data sets, and examples from the text. Principles of Sequencing and Scheduling is an excellent book for courses on sequencing and scheduling at the upper-undergraduate and graduate levels. It is also a valuable reference for researchers and practitioners in the fields of statistics, computer science, operations research, and engineering.
Author: Haili Lu Publisher: Open Dissertation Press ISBN: 9781361266595 Category : Languages : en Pages :
Book Description
This dissertation, "A Comparative Study of Assembly Job Shop Scheduling Using Simulation, Heuristics and Meta-heuristics" by Haili, Lu, 吕海利, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. DOI: 10.5353/th_b4702901 Subjects: Genetic algorithms Heuristic programming Production scheduling
Author: Michael L. Pinedo Publisher: Springer Science & Business Media ISBN: 0387273999 Category : Business & Economics Languages : en Pages : 500
Book Description
Pinedo is a major figure in the scheduling area (well versed in both stochastics and combinatorics) , and knows both the academic and practitioner side of the discipline. This book includes the integration of case studies into the text. It will appeal to engineering and business students interested in operations research.
Author: Nutthapol Asadathorn
Author: Samuel Bistra Liron
Author: Tse-Chiu Wong
Author: Kenneth R. Baker
Author: Haili Lu
Author: Michael L. Pinedo
Author: Manmohan Mehra
Author: Roger Vivian Johnson
Author: Lynwood A. Johnson
Author: Yeong-Dae Kim