Journal Article10.1287/IJOC.3.2.149
A Computational Study of the Job-Shop Scheduling Problem
David Applegate,William J. Cook +1 more
894
TL;DR: The optimization procedure, combining the heuristic method and the combinatorial branch and bound algorithm, solved the well-known 10×10 problem of J. F. Thomson in under 7 minutes of computation time on a Sun Sparcstation 1.
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Abstract: The job-shop scheduling problem is a notoriously difficult problem in combinatorial optimization. Although even modest sized instances remain computationally intractable, a number of important algorithmic advances have been made in recent years by J. Adams, E. Balas and D. Zawack; J. Carlier and E. Pinson; B. J. Lageweg, J. K. Lenstra and A. H. G. Rinnooy Kan; and others. Making use of a number of these advances, we have designed and implemented a new heuristic procedure for finding schedules, a cutting-plane method for obtaining lower bounds, and a combinatorial branch and bound algorithm. Our optimization procedure, combining the heuristic method and the combinatorial branch and bound algorithm, solved the well-known 10×10 problem of J. F. Muth and G. L. Thomson in under 7 minutes of computation time on a Sun Sparcstation 1. INFORMS Journal on Computing, ISSN 1091-9856, was published as ORSA Journal on Computing from 1989 to 1995 under ISSN 0899-1499.
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Citations
A very fast TS/SA algorithm for the job shop scheduling problem
TL;DR: The heuristics search approach combining simulated annealing (SA) and TS strategy is developed, where SA is used to find the elite solutions inside big valley (BV) so that TS can re-intensify search from the promising solutions.
Short Shop Schedules
David P. Williamson,Leslie A. Hall,Johannes Hoogeveen,Cor A. J. Hurkens,Jan Karel Lenstra,S. V. Sevast'janov,David B. Shmoys +6 more
TL;DR: This work constitutes the first nontrivial theoretical evidence that shop scheduling problems are hard to solve even approximately.
Energy-Aware Scheduling of Distributed Systems
Pragati Agrawal,Shrisha Rao +1 more
TL;DR: This work proposes a new formulation and shows that energy-aware scheduling is a generalization of the minimum makespan scheduling problem and gives insight into the time-energy trade-offs in scheduling.
•Proceedings Article
Randomized large neighborhood search for cumulative scheduling
Daniel Godard,Philippe Laborie,Wim Nuijten +2 more
- 05 Jun 2005
TL;DR: The described approach obtains the best known performance reported to date on the CJSSP, and not only finds better solutions than ever reported before for 33 out of 36 open instances, it also proves to be very robust on the complete set of test instances.
Local Search and Constraint Programming
Filippo Focacci,François Laburthe,Andrea Lodi +2 more
- 01 Jan 2003
TL;DR: Real-world combinatorial optimization problems have two main characteristics: they are usually large, and they are not pure, i.e., they involve a heterogeneous set of side constraints, so the algorithmic approach requires flexibility, and this flexibility can be guaranteed by Constraint Programming.