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 heuristic for job shop scheduling to minimize total weighted tardiness
Makoto Asano,Hiroshi Ohta +1 more
- 01 Jun 2002
TL;DR: In this paper, the authors considered the job shop scheduling problem to minimize the total weighted tardiness with job-specific due dates and delay penalties, and a heuristic algorithm based on the tree search procedure was developed for solving the problem.
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A Very Fast Tabu Search Algorithm for Job Shop Problem
Józef Grabowskil,Mieczysław Wodecki +1 more
- 01 Jan 2005
TL;DR: This paper deals with the classic job-shop scheduling problem with makespan criterion with some new properties of the problem associated with blocks, and proposes a new, very fast local search procedure based on a tabu search approach.
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Production scheduling in ERP systems: An AI‐based approach to face the gap
TL;DR: A knowledge‐based system for production‐scheduling that could be incorporated as a custom module in an ERP system that uses the prevailing conditions in the industrial environment in order to select dynamically and propose the most appropriate scheduling algorithm from a library of many candidate algorithms.
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A Unified Taxonomy of Hybrid Metaheuristics with Mathematical Programming, Constraint Programming and Machine Learning
El-Ghazali Talbi
- 01 Jan 2013
TL;DR: Over the last years, interest on hybrid metaheuristics has risen considerably in the field of optimization, and four different types of combinations are considered in this chapter.
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