Topic
Disjunctive graph
About: Disjunctive graph is a research topic. Over the lifetime, 220 publications have been published within this topic receiving 18494 citations.
Papers published on a yearly basis
Papers
Book•
15 Jul 1994
TL;DR: Scheduling will serve as an essential reference for professionals working on scheduling problems in manufacturing and computing environments and Graduate students in operations management, operations research, industrial engineering and computer science will find the book to be an accessible and invaluable resource.
Abstract: This book on scheduling covers theoretical models as well as scheduling problems in the real world. Author Michael Pinedo also includes a CD that contains slide-shows from industry and movies dealing with implementations of scheduling systems. The book consists of three parts. The first part focuses on deterministic scheduling with the associated combinatorial problems. The second part covers probabilistic scheduling models. In this part it is assumed that processing times and other problem data are not known in advance. The third part deals with scheduling in practice. It covers heuristics that are popular with practitioners and discusses system design and development issues. Each chapter contains a series of computational and theoretical exercises. This book is of interest to theoreticians and practitioners alike. Graduate students in operations management, operations research, industrial engineering and computer science will find the book to be an accessible and invaluable resource. Scheduling will serve as an essential reference for professionals working on scheduling problems in manufacturing and computing environments. Michael Pinedo is the Julius Schlesinger Professor of Operations Management at New York University.
7,277 citations
TL;DR: An approximation method for solving the minimum makespan problem of job shop scheduling by sequences the machines one by one, successively, taking each time the machine identified as a bottleneck among the machines not yet sequenced.
Abstract: We describe an approximation method for solving the minimum makespan problem of job shop scheduling. It sequences the machines one by one, successively, taking each time the machine identified as a bottleneck among the machines not yet sequenced. Every time after a new machine is sequenced, all previously established sequences are locally reoptimized. Both the bottleneck identification and the local reoptimization procedures are based on repeatedly solving certain one-machine scheduling problems. Besides this straight version of the Shifting Bottleneck Procedure, we have also implemented a version that applies the procedure to the nodes of a partial search tree. Computational testing shows that our approach yields consistently better results than other procedures discussed in the literature. A high point of our computational testing occurred when the enumerative version of the Shifting Bottleneck Procedure found in a little over five minutes an optimal schedule to a notorious ten machines/ten jobs problem on which many algorithms have been run for hours without finding an optimal solution.
1,700 citations
TL;DR: In this article, an approximation algorithm for the problem of finding the minimum makespan in a job shop is presented, which is based on simulated annealing, a generalization of the well known iterative improvement approach to combinatorial optimization problems.
Abstract: We describe an approximation algorithm for the problem of finding the minimum makespan in a job shop. The algorithm is based on simulated annealing, a generalization of the well known iterative improvement approach to combinatorial optimization problems. The generalization involves the acceptance of cost-increasing transitions with a nonzero probability to avoid getting stuck in local minima. We prove that our algorithm asymptotically converges in probability to a globally minimal solution, despite the fact that the Markov chains generated by the algorithm are generally not irreducible. Computational experiments show that our algorithm can find shorter makespans than two recent approximation approaches that are more tailored to the job shop scheduling problem. This is, however, at the cost of large running times.
1,169 citations
TL;DR: A fast and easily implementable approximation algorithm for the problem of finding a minimum makespan in a job shop is presented, based on a taboo search technique with a specific neighborhood definition which employs a critical path and blocks of operations notions.
Abstract: A fast and easily implementable approximation algorithm for the problem of finding a minimum makespan in a job shop is presented. The algorithm is based on a taboo search technique with a specific neighborhood definition which employs a critical path and blocks of operations notions. Computational experiments up to 2,000 operations show that the algorithm not only finds shorter makespans than the best approximation approaches but also runs in shorter time. It solves the well-known 10 × 10 hard benchmark problem within 30 seconds on a personal computer.
1,041 citations
TL;DR: In this paper, a branch and bound method for solving the job-shop problem is proposed, which is based on one-machine scheduling problems and is made more efficient by several propositions which limit the search tree by using immediate selections.
Abstract: In this paper, we propose a branch and bound method for solving the job-shop problem. It is based on one-machine scheduling problems and is made more efficient by several propositions which limit the search tree by using immediate selections.
It solved for the first time the famous 10 × 10 job-shop problem proposed by Muth and Thompson in 1963.
896 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2021 | 1 |
| 2020 | 8 |
| 2019 | 5 |
| 2018 | 9 |
| 2017 | 4 |
| 2016 | 16 |