Author: Lay Eng TeohPublisher:
ISBN:
Category : Algorithms
Languages : en
Pages :
Book Description
Minimizing Makespan and Total Weighted Tardiness for Job Shop Scheduling Problem Using Shifting Bottleneck Heuristic
Author: Lay Eng TeohMinimization of Weighted Tardiness in Job Shops Using Shifting Bottleneck and Tabu Search Procedures
Author: Planning and Scheduling in Manufacturing and Services
Author: Michael PinedoPublisher: Springer Science & Business Media
ISBN: 9780387221984
Category : Business & Economics
Languages : en
Pages : 542
Book Description
This book focuses on planning and scheduling applications. Planning and scheduling are forms of decision-making that play an important role in most manufacturing and services industries. The planning and scheduling functions in a company typically use analytical techniques and heuristic methods to allocate its limited resources to the activities that have to be done. The application areas considered in this book are divided into manufacturing applications and services applications. The book covers five areas in manufacturing: project scheduling, job shop scheduling, scheduling of flexible assembly systems, economic lot scheduling, and planning and scheduling in supply chains. It covers four areas in services: reservations and timetabling, tournament scheduling, planning and scheduling in transportation, and workforce scheduling. At the end of each chapter, a case study or a system implementation is described in detail. Numerous examples and exercises throughout the book illustrate the material presented. The fundamentals concerning the methodologies used in the application chapters are covered in the appendices. The book comes with a CD-ROM that contains various sets of powerpoint slides. The CD also contains several planning and scheduling systems that have been developed in academia as well as generic optimization software that has been developed in industry. This book is suitable for more advanced students in industrial engineering and operations research as well as graduate students in business. Michael Pinedo is the Julius Schlesinger Professor of Operations Management in the Stern School of Business at New York University. His research interests lie in the theoretical and applied aspects of planning and scheduling. He has written numerous papers on the theory of deterministic and stochastic scheduling and has also consulted extensively in industry. He has been actively involved in the development of several large industrial planning and scheduling systems.
Scheduling in Assembly Type Job-shops
Author: Nutthapol AsadathornPublisher:
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.
Heuristics, Metaheuristics and Approximate Methods in Planning and Scheduling
Author: Ghaith RabadiPublisher: Springer
ISBN: 3319260243
Category : Business & Economics
Languages : en
Pages : 271
Book Description
The scope of this book is limited to heuristics, metaheuristics, and approximate methods and algorithms as applied to planning and scheduling problems. While it is not possible to give a comprehensive treatment of this topic in one book, the aim of this work is to provide the reader with a diverse set of planning and scheduling problems and different heuristic approaches to solve them. The problems range from traditional single stage and parallel machine problems to more modern settings such as robotic cells and flexible job shop networks. Furthermore, some chapters deal with deterministic problems while some others treat stochastic versions of the problems. Unlike most of the literature that deals with planning and scheduling problems in the manufacturing and production environments, in this book the environments were extended to nontraditional applications such as spatial scheduling (optimizing space over time), runway scheduling, and surgical scheduling. The solution methods used in the different chapters of the book also spread from well-established heuristics and metaheuristics such as Genetic Algorithms and Ant Colony Optimization to more recent ones such as Meta-RaPS.
Exact and Heuristic Scheduling Algorithms
Author: Frank WernerPublisher: MDPI
ISBN: 3039284681
Category : Technology & Engineering
Languages : en
Pages : 200
Book Description
This edited book presents new results in the area of the development of exact and heuristic scheduling algorithms. It contains eight articles accepted for publication for a Special Issue in the journal Algorithms. The book presents new algorithms, e.g., for flow shop, job shop, and parallel machine scheduling problems. The particular articles address subjects such as a heuristic for the routing and scheduling problem with time windows, applied to the automotive industry in Mexico, a heuristic for the blocking job shop problem with tardiness minimization based on new neighborhood structures, fast heuristics for the Euclidean traveling salesman problem or a new mathematical model for the period-aggregated resource leveling problem with variable job duration, and several others.
Planning and Scheduling in Manufacturing and Services
Author: Michael L. PinedoPublisher: Springer Science & Business Media
ISBN: 1441909109
Category : Business & Economics
Languages : en
Pages : 537
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.
Minimization of Makespan and Total Tardiness in a Flow Shop Scheduling Using Artificial Neural Network
Author: Ashwani K DhingraPublisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
The paper makes an attempt to minimize the makespan and total tardiness in the flow shop scheduling using Artificial Neural Network (ANN). A feed forward back propagation neural network is implemented for the optimal solution of the problem. The network has been trained with the optimal sequences for different jobs on five machines problem. The trained network is further considered for solving the problem of flow shop scheduling. The analysis of all the algorithms that are implemented is carried out using Nawaz, Enscore and Ham (NEH) heuristic for 5 to 10 jobs with 5 machines under Sequence Dependent Set-up Time (SDST) environment with due dates and weights allotted to each job. With the help of NEH heuristic, different sequences have been generated for the considered problem. The number of sequences obtained is assembled in 270 × 10 matrix for the input of neural network. The network is trained with Baygon regression training algorithm and finally the results obtained from the neural network are found to be 93% accurate.
A Modified Shifting Bottleneck Approach to Job Shop Scheduling with Sequence Dependent Setups (MSBSS)
Author: Xiaoqing SunPublisher:
ISBN:
Category : Production scheduling
Languages : en
Pages : 270
Book Description
This research addresses the NP-Hard, practical problem of scheduling jobs with release dates, due dates and sequence dependent setups where the scheduling objective is to minimize the weighted sum of squared tardiness. Such a problem is practically relevant due to the fact that there are numerous industrial settings that involve sequence dependent setups. A shifting bottleneck based method (MSBSS) is developed for job shop scheduling with sequence dependent setups, which balances both efficiency and optimality. As a key component of MSBSS, a Lagrangian relaxation based approach (LRSSS) is also developed for single-machine scheduling with sequence dependent setups. Sequence dependent setups are formulated into capacity constraints, then the capacity constraints are relaxed using a Lagrangian multiplier. The primal problem is decomposed into job-level subproblems which are solved optimally and an approximation dual problem is then solved using a sub-gradient technique. The result of the relaxation is a list of jobs sequenced by beginning times that is then improved via a three-way enumeration. Experimental results are compared with EDD (earliest due date), ATCS (apparent tardiness cost with sequence dependent setups), dispatching rules, a 4-way enumeration local search, tabu search, and simulated annealing. The LRSSS approach results in superior solution quality with respect to EDD, ATCS, 4-way enumeration and tabu search results. It has comparable solution quality to the simulated annealing results, but is substantially more efficient. The LRSSS is then extended to job shop scheduling with sequence dependent setups, due dates and release dates. The resulting MSBSS procedure decomposes the job shop scheduling problem into a series of single-machine scheduling problems. Machines are scheduled in order of criticality defined as the marginal contribution of a machine to the objective function. The MSBSS approach is compared with EDD, ATCS, and SIMSET (similar setup times) dispatching rules. The MSBSS approach results in superior solution quality to the results of other dispatching rules. Overall the research has resulted in two efficient scheduling procedures (LRSSS and MSBSS) that fill an important gap in algorithm design dealing with practical, realistically sized scheduling problems.
Author: Suresh Chand