Abstract
This research compares the performance of various heuristics and one metaheuristic for unrelated parallel machine scheduling problems. The objective functions to be minimized are makespan, total weighted completion time, and total weighted tardiness. We use the least significant difference (LSD) test to identify robust heuristics that perform significantly better than others for a variety of parallel machine environments with these three performance measures. Computational results show that the proposed metaheuristic outperforms other existing heuristics for each of the three objectives when run with a parameter setting appropriate for the objective.
Original language | English (US) |
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Pages (from-to) | 901-916 |
Number of pages | 16 |
Journal | Computers and Operations Research |
Volume | 38 |
Issue number | 6 |
DOIs | |
State | Published - Jun 2011 |
Keywords
- Genetic algorithm
- Heuristic
- Unrelated parallel machine scheduling
ASJC Scopus subject areas
- Computer Science(all)
- Modeling and Simulation
- Management Science and Operations Research