JOURNAL ARTICLE

Makespan minimization form parallel identical processors

Johnny C. HoJohnny S. Wong

Year: 1995 Journal:   Naval Research Logistics (NRL) Vol: 42 (6)Pages: 935-948   Publisher: Wiley

Abstract

We introduce an algorithm, called TMO (Two-Machine Optimal Scheduling) which minimizes the makespan for two identical processors. TMO employs lexicographic search in conjunction with the longest-processing time sequence to derive an optimal schedule. For the m identical parallel processors problem, we propose an improvement algorithm, which improves the seed solution obtained by any existing heuristic. The improvement algorithm, called Extended TMO, breaks the original m-machine problem into a set of two-machine problems and solves them repeatedly by the TMO. A simulation study is performed to evaluate the effectiveness of the proposed algorithms by comparing it against three existing heuristics: LPT (Graham, [11]), MULTIFIT (Coffman, Garey, and Johnson, [6]), and RMG (Lee and Massey, [17]). The simulation results show that: for the two processors case, the TMO performs significantly better than LPT, MULTIFIT, and RMG, and it generally takes considerably less CPU time than MULTIFIT and RMG. For the general parallel processors case, the Extended TMO algorithm is shown to be capable of greatly improving any seed solution. © 1995 John Wiley & Sons, Inc.

Keywords:
Computer science Job shop scheduling Heuristics Parallel computing Minification Scheduling (production processes) Schedule Lexicographical order Sequence (biology) Algorithm Set (abstract data type) Heuristic Mathematical optimization Mathematics Combinatorics Artificial intelligence

Metrics

41
Cited By
0.00
FWCI (Field Weighted Citation Impact)
22
Refs
0.28
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Scheduling and Optimization Algorithms
Physical Sciences →  Engineering →  Industrial and Manufacturing Engineering
Optimization and Packing Problems
Physical Sciences →  Engineering →  Industrial and Manufacturing Engineering
Optimization and Search Problems
Physical Sciences →  Computer Science →  Computer Networks and Communications

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