Document Type : Research Paper
Authors
1 Department of Industrial Engineering, Birjand University of Technology, Birjand, Iran.
2 Department of Mathematics and Computer Science, Transilvania University, Brasov, 500091, Romania.
3 Department of Mathematics, Kosar University of Bojnord, Bojnord, Iran.
4 Department of Industrial Engineering, Arak University, Arak, Iran.
Abstract
The maximum capacity path problem (MCPP) is a classical combinatorial optimization
problem that seeks to find a path with the maximum capacity in a network. In
this paper, we consider a fuzzy extension of the MCPP, where the capacities are given
as arbitrary fuzzy numbers. Unlike previous approaches that rely on ranking functions
or specific orderings, we formulate the fuzzy MCPP as a bi-objective path-finding
problem, where one objective is to maximize the nominal capacity and the other is to
optimize the reliability value of the path. We propose an efficient algorithm that can
find a Pareto optimal path for any aggregation function between the two objectives.
We also analyze the special case where the network is acyclic and show that the algorithm
can be specialized to run in strongly polynomial time. Furthermore, we present
an application of the fuzzy MCPP to the field of optimal control, where we use a discretization
algorithm to transform a continuous routing problem into a discrete one and
solve it using the proposed algorithm as a subroutine. To implement this application
in practice, we run the algorithm on an old real-world project in Iran called Iranrud.
Moreover, we report some computational results on grid networks with different sizes
that illustrate the performance of the proposed algorithm.
Keywords
Main Subjects
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