Pareto Optimal Multiobjective Optimization for Robust Transportation Network Design Problem
DSpace at IIT Bombay
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Title |
Pareto Optimal Multiobjective Optimization for Robust Transportation Network Design Problem
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Creator |
SHARMA, S
UKKUSURI, SV MATHEW, TV |
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Subject |
genetic algorithm
programming approach demand uncertainty capacity models flows cost user |
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Description |
A study was done to formulate and solve the multiobjective network design problem with uncertain demand. Various samples of demand are realized for optimal improvements in the network while the objectives of the expected total system travel time and the higher moment for total system travel time are minimized. A formulation is proposed for multiobjective robust network design, and a solution methodology is developed on the basis, of a revised fast and elitist nondominated sorting genetic algorithm. The developed methodology has been tested on the Nguyen-Dupuis network, and various Pareto optimal solutions are compared with earlier work on the single-objective robust network design problem. A real medium-size network was solved to prove efficacy of the model. The results show better solutions for the multiobjective robust network design problem with relatively less computational effort.
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Publisher |
NATL ACAD SCIENCES
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Date |
2011-08-19T01:00:53Z
2011-12-26T12:55:58Z 2011-12-27T05:43:46Z 2011-08-19T01:00:53Z 2011-12-26T12:55:58Z 2011-12-27T05:43:46Z 2009 |
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Type |
Article
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Identifier |
TRANSPORTATION RESEARCH RECORD, (2090), 95-104
0361-1981 http://dx.doi.org/10.3141/2090-11 http://dspace.library.iitb.ac.in/xmlui/handle/10054/10172 http://hdl.handle.net/10054/10172 |
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Language |
en
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