Solving Fuzzy Multiobjective Linear Programming Problems Based on Evolutionary Computation
碩士 === 國立暨南國際大學 === 資訊管理學系 === 91 === Evolutionary computation has been proposed to solve optimization problems for around 40 years. Many new algorithms have been introduced and many new operators including crossover, mutation, or selection operators have been also developed. Initially, they were de...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2003
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| Online Access: | http://ndltd.ncl.edu.tw/handle/11019920232259671484 |
| Summary: | 碩士 === 國立暨南國際大學 === 資訊管理學系 === 91 === Evolutionary computation has been proposed to solve optimization problems for around 40 years. Many new algorithms have been introduced and many new operators including crossover, mutation, or selection operators have been also developed. Initially, they were developed for some specific problems. Nobody knows whether they still have perfect efficiency for other problems. Based on this reason, we invoke five different evolutionary algorithms that were proposed by some researchers to solve the fuzzy multiobjective linear programming problems. We plan to investigate and compare their efficiency. Furthermore, we also provide another effective method to evaluate the fuzzy multiobjective linear programming problems.
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