Open Access
Sequencing and scheduling : algorithms and complexity
Eugene L. Lawler,Jan Karel Lenstra,Ahg Alexander Rinnooy Kan,David B. Shmoys +3 more
- Vol. 4, pp 445
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TLDR
A survey of deterministic machine scheduling can be found in this article, where complexity results and optimization and approximation algorithms for problems involving a single machine, parallel machines, open shops, flow shops and job shops are presented.Abstract:
Sequencing and scheduling as a research area is motivated by questions that arise in production planning, in computer control, and generally in all situations in which scarce resources have to be allocated to activities over time. In this survey, we concentrate on the area of deterministic machine scheduling. We review complexity results and optimization and approximation algorithms for problems involving a single machine, parallel machines, open shops, flow shops and job shops. We also pay attention to two extensions of this area: resource-constrained project scheduling and stochastic machine scheduling.read more
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Journal ArticleDOI
Minimizing Makespan and Preemption Costs on a System of Uniform Machines
TL;DR: This paper derives matching lower and upper bounds on the number of preemptions required by any optimal schedule, and develops polynomial time approximation schemes for generalized multiprocessor scheduling and minimum preemptions scheduling.
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A heuristic algorithm for two-machine re-entrant shop scheduling
TL;DR: In this paper, the authors considered the problem of sequencing n jobs in a two-machine re-entrant shop with the objective of minimizing the maximum completion time, and presented an O(n log n)time heuristic which generated a schedule with length at most 4/3 times that ofan optimal schedule.
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Randomized algorithms for on-line scheduling problems: how low can't you go?
TL;DR: Chekuri et al. as mentioned in this paper proved lower bounds on the competitive ratio of randomized algorithms for several on-line scheduling problems and showed that Chekuri's algorithm is the best possible randomized algorithm for this problem.
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A three-layer chromosome genetic algorithm for multi-cell scheduling with flexible routes and machine sharing
Yanling Feng,Guo Li,Suresh Sethi +2 more
TL;DR: This paper considers a dynamic cellular scheduling problem with flexible routes and machine sharing with a three-layer chromosome genetic algorithm (TCGA) and proposes a mixed integer programming scheduling model to minimize both the makespan and the total workload.