Mutiobjective Optimization Strategy for Solving Interval-valued Fuzzy Constrained Shortest Path Problems
Subject Areas : Fuzzy Optimization and Modeling Journal
1 - Department of Mathematics,
Payame Noor University,
P.O.Box 19395-3697, Tehran,
Iran.
Keywords: Constrainted Shortest Path, Interval-valued Fuzzy Number, Multiobjective Optimization,
Abstract :
The constrained shortest path (CSP) problem is one of the most used and tangible applications of network flow problems that aside from its straightforward application is arised as auxiliary problems in flight planning, tail assignment problem in aircraft scheduling and crew rostering problems, among others. The objective of the CSP problem is to determine a minimum cost path between two specified nodes that the traversal time of the path does not exceed from a specified time. Conventional CSP problem generally assumes that the weights of arc costs and times are defined by real variables, though these values are unpredictable due to some uncontrollable factors. The present study formulates a CSP problem when values of arc costs and times are interval-valued triangular fuzzy numbers and proposes a multi-objective optimization strategy to obtain the efficient solution of the resulting problem. The applicability of the proposed approach is illustrated through an example dealing with wireless sensor networks
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