A computational method using genetic algorithms for obtaining Stackelberg solutions to two-level linear programming problems
Stackelberg solutions have been derived for two‐level linear programming problems using genetic algorithms which in recent years have shown their efficacy in optimization problems having discrete variables. Two‐level linear programming problems are converted into single‐level programming problems by...
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| Published in: | Electronics & communications in Japan. Part 3, Fundamental electronic science Vol. 85; no. 6; pp. 55 - 62 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
New York
John Wiley & Sons, Inc
01.06.2002
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| Subjects: | |
| ISSN: | 1042-0967, 1520-6440 |
| Online Access: | Get full text |
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| Summary: | Stackelberg solutions have been derived for two‐level linear programming problems using genetic algorithms which in recent years have shown their efficacy in optimization problems having discrete variables. Two‐level linear programming problems are converted into single‐level programming problems by including the optimal conditions of lower‐level problems in the conditions of higher‐level problems. The obtained one‐level programming problems become 0–1 mixed programming problems. A computational method for obtaining Stackelberg solutions by generating initial population and using corresponding genetic operators based on the characteristics of the problems by expressing the 0–1 variables as individuals of the genetic algorithms is proposed. The efficacy of the proposed method is shown in computational experiments by comparing it with the variable elimination method. © 2002 Scripta Technica, Electron Comm Jpn Pt 3, 85(6): 55–62, 2002 |
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| Bibliography: | ArticleID:ECJC1101 istex:236CD6D47727C8EC52FD1BCAF934AB69873532BF ark:/67375/WNG-QDJ78CMW-9 ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 |
| ISSN: | 1042-0967 1520-6440 |
| DOI: | 10.1002/ecjc.1101 |