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Please use this identifier to cite or link to this item: http://dspace.library.iitb.ac.in/jspui/handle/10054/10172

Title: Pareto Optimal Multiobjective Optimization for Robust Transportation Network Design Problem
Authors: SHARMA, S
UKKUSURI, SV
MATHEW, TV
Keywords: genetic algorithm
programming approach
demand uncertainty
capacity
models
flows
cost
user
Issue Date: 2009
Publisher: NATL ACAD SCIENCES
Citation: TRANSPORTATION RESEARCH RECORD, (2090), 95-104
Abstract: 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.
URI: http://dx.doi.org/10.3141/2090-11
http://dspace.library.iitb.ac.in/xmlui/handle/10054/10172
http://hdl.handle.net/10054/10172
ISSN: 0361-1981
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