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A genetic algorithm for energy-efficiency in job-shop scheduling.
- Source :
-
International Journal of Advanced Manufacturing Technology . Jul2016, Vol. 85 Issue 5-8, p1303-1314. 12p. 4 Diagrams, 4 Charts, 5 Graphs. - Publication Year :
- 2016
-
Abstract
- Many real-world scheduling problems are solved to obtain optimal solutions in term of processing time, cost, and quality as optimization objectives. Currently, energy-efficiency is also taken into consideration in these problems. However, this problem is NP-hard, so many search techniques are not able to obtain a solution in a reasonable time. In this paper, a genetic algorithm is developed to solve an extended version of the Job-shop Scheduling Problem in which machines can consume different amounts of energy to process tasks at different rates (speed scaling). This problem represents an extension of the classical job-shop scheduling problem, where each operation has to be executed by one machine and this machine can work at different speeds. The evaluation section shows that a powerful commercial tool for solving scheduling problems was not able to solve large instances in a reasonable time, meanwhile our genetic algorithm was able to solve all instances with a good solution quality. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 02683768
- Volume :
- 85
- Issue :
- 5-8
- Database :
- Academic Search Index
- Journal :
- International Journal of Advanced Manufacturing Technology
- Publication Type :
- Academic Journal
- Accession number :
- 116328299
- Full Text :
- https://doi.org/10.1007/s00170-015-7987-0