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The Application of a Parallel Genetic Algorithm to the n/m/P/C max Flowshop Problem
| Content Provider | Semantic Scholar |
|---|---|
| Author | Stöppler, S. Bierwirth, Christian |
| Copyright Year | 1992 |
| Abstract | Hard combinatorial problems in sequencing and scheduling led recently into further research of genetic algorithms. Canonical coding of the symmetric TSP can be modified into a coding of the n-job m-machine flowshop problem, which configurates the solution space in a different way. We show that well known genetic operators act intelligently on this coding scheme. They implecitely prefer a subset of solutions which contain the probably best solutions with respect to an objective. We conjecture that every new problem needs a determination of this necessary condition for a genetic algorithm to work, i. e. a proof by experiment. We implemented an asynchronous parallel genetic algorithm on a UNIX-based computer network. Computational results of the new heuristic are discussed. |
| Starting Page | 161 |
| Ending Page | 175 |
| Page Count | 15 |
| File Format | PDF HTM / HTML |
| DOI | 10.1007/978-3-642-77537-6_10 |
| Alternate Webpage(s) | http://medusa.logistik.uni-bremen.de/Papers/fsp.ps |
| Alternate Webpage(s) | https://doi.org/10.1007/978-3-642-77537-6_10 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
