DEVELOPMENT OF A HYBRID FUZZY GENETIC ALGORITHM MODEL FOR SOLVING TRANSPORTATION SCHEDULING PROBLEM
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| Formato: | Artículo científico |
| Lenguaje: | en |
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Universidade de São Paulo
2015
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| _version_ | 1876455602405769216 |
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| author | H.C.W. Lau |
| author_facet | H.C.W. Lau |
| contents | DEVELOPMENT OF A HYBRID FUZZY GENETIC ALGORITHM MODEL FOR SOLVING TRANSPORTATION SCHEDULING PROBLEM H.C.W. Lau Dilupa Nakandala Li Zhao Ingeniería genetic algorithm fuzzy logic approach Passenger railway scheduling customer service optimization There has been an increasing public demand for passenger rail service in the recent times leading to a strong focus on the need for effective and efficient use of resources and managing the increasing passenger requirements, s ervice reliability and variability by the railway management. Whilst shortening the passengers’ waiting and travelling time is important for commuter satisfaction, lowering operational cost s is equally important for railway management. Hence, effective and cost optimised train scheduling based on the dynamic passenger demand is one of the main issues for passenger railway management. Although the passenger railway scheduling problem has received attention in operations research in recent years, there is lim ited literature investigating the adoption of practical approaches that capitalize on the merits of mathematical modeling and search algorithms for effective cost optimization. This paper develops a hybrid fuzzy logic based genetic algorithm model to solve the multi - objective passenger railway scheduling problem aiming to optimize total operational cost s at a satisfactory level of customer service. This hybrid approach integrates genetic algorithm with the fuzzy logic approach which uses the fuzzy controlle r to determine the crossover rate and mutation rate in genetic algorithm approach in the optimization process. The numerical study demonstrates the improvement of the proposed hybrid approach, and the fuzzy genetic algorithm has demonstrated its effective ness to generate better results than standard genetic algorithm and other traditional heuristic approaches, such as simulated annealing. 2015 artículo científico 1807-1775 https://www.redalyc.org/articulo.oa?id=203243872001 en http://www.redalyc.org/revista.oa?id=2032 JISTEM: Journal of Information Systems and Technology Management application/pdf Universidade de São Paulo JISTEM: Journal of Information Systems and Technology Management (Brasil) Num.3 Vol.12 |
| format | Artículo científico |
| id | redalyc_203243872001 |
| institution | Redalyc |
| language | en |
| publishDate | 2015 |
| publisher | Universidade de São Paulo |
| spellingShingle | DEVELOPMENT OF A HYBRID FUZZY GENETIC ALGORITHM MODEL FOR SOLVING TRANSPORTATION SCHEDULING PROBLEM H.C.W. Lau Ingeniería genetic algorithm fuzzy logic approach Passenger railway scheduling customer service optimization DEVELOPMENT OF A HYBRID FUZZY GENETIC ALGORITHM MODEL FOR SOLVING TRANSPORTATION SCHEDULING PROBLEM H.C.W. Lau Dilupa Nakandala Li Zhao Ingeniería genetic algorithm fuzzy logic approach Passenger railway scheduling customer service optimization There has been an increasing public demand for passenger rail service in the recent times leading to a strong focus on the need for effective and efficient use of resources and managing the increasing passenger requirements, s ervice reliability and variability by the railway management. Whilst shortening the passengers’ waiting and travelling time is important for commuter satisfaction, lowering operational cost s is equally important for railway management. Hence, effective and cost optimised train scheduling based on the dynamic passenger demand is one of the main issues for passenger railway management. Although the passenger railway scheduling problem has received attention in operations research in recent years, there is lim ited literature investigating the adoption of practical approaches that capitalize on the merits of mathematical modeling and search algorithms for effective cost optimization. This paper develops a hybrid fuzzy logic based genetic algorithm model to solve the multi - objective passenger railway scheduling problem aiming to optimize total operational cost s at a satisfactory level of customer service. This hybrid approach integrates genetic algorithm with the fuzzy logic approach which uses the fuzzy controlle r to determine the crossover rate and mutation rate in genetic algorithm approach in the optimization process. The numerical study demonstrates the improvement of the proposed hybrid approach, and the fuzzy genetic algorithm has demonstrated its effective ness to generate better results than standard genetic algorithm and other traditional heuristic approaches, such as simulated annealing. 2015 artículo científico 1807-1775 https://www.redalyc.org/articulo.oa?id=203243872001 en http://www.redalyc.org/revista.oa?id=2032 JISTEM: Journal of Information Systems and Technology Management application/pdf Universidade de São Paulo JISTEM: Journal of Information Systems and Technology Management (Brasil) Num.3 Vol.12 |
| title | DEVELOPMENT OF A HYBRID FUZZY GENETIC ALGORITHM MODEL FOR SOLVING TRANSPORTATION SCHEDULING PROBLEM |
| topic | Ingeniería genetic algorithm fuzzy logic approach Passenger railway scheduling customer service optimization |
| url | https://www.redalyc.org/articulo.oa?id=203243872001 |