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Stochastic multi-objective models for network design problem
- Source :
-
Expert Systems with Applications . Mar2010, Vol. 37 Issue 2, p1608-1619. 12p. - Publication Year :
- 2010
-
Abstract
- Abstract: Transportation network design problem (NDP) is inherently multi-objective in nature, because it involves a number of stakeholders with different needs. In addition, the decision-making process sometimes has to be made under uncertainty where certain inputs are not known exactly. In this paper, we develop three stochastic multi-objective models for designing transportation network under demand uncertainty. These three stochastic multi-objective NDP models are formulated as the expected value multi-objective programming (EVMOP) model, chance constrained multi-objective programming (CCMOP) model, and dependent chance multi-objective programming (DCMOP) model in a bi-level programming framework using different criteria to hedge against demand uncertainty. To solve these stochastic multi-objective NDP models, we develop a solution approach that explicitly optimizes all objectives under demand uncertainty by simultaneously generating a family of optimal solutions known as the Pareto optimal solution set. Numerical examples are also presented to illustrate the concept of the three stochastic multi-objective NDP models as well as the effectiveness of the solution approach. [Copyright &y& Elsevier]
Details
- Language :
- English
- ISSN :
- 09574174
- Volume :
- 37
- Issue :
- 2
- Database :
- Academic Search Index
- Journal :
- Expert Systems with Applications
- Publication Type :
- Academic Journal
- Accession number :
- 45068599
- Full Text :
- https://doi.org/10.1016/j.eswa.2009.06.048