Admi Syarif, AS and Muludi, Kurnia and Gen, Mitsuo (2014) Peer Review: Implementation of Hybridized Genetic Algorithm for Fuzzy Traveling Salesman Problem. International Association for Information and Management Sciences.

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Abstract

The Traveling Salesman Problem (TSP) is known as one of NP-complete optimization problems that has taken great interest of the researchers. The common objective is to determine route through some cities facilities in order to minimize travel distance. The classic TSP usually assumes that the travel costs are deterministic. In the real- world applications, due to the complexity of social and economic factors, it is often difficult to have deterministic value of travel costs (i.e. travel time). One way of handling such uncertainty in decision making is by introducing fuzzy programming approach. Since TSP is also usually very large, huge research efforts have been devoted to develop heuristic algorithms for solving TSP. It has also been reported that Genetic Algorithm could give a good solution of TSP within reasonable time. In this paper, we consider a more realistic model called fuzzy TSP. By assuming that the travel costs between cities are represented by triangular fuzzy number, we examine how the route should be designed. We develop a GA hybridized with local approach to solve the problem. Several numerical experiments are done to show the effectiveness of the proposed method.

Item Type:	Other
Subjects:	T Technology > T Technology (General)
Divisions:	Fakultas Matematika dan Ilmu Pengetahuan Alam (FMIPA) > Prodi Ilmu Komputer
Depositing User:	DR Admi Syarif
Date Deposited:	01 Apr 2021 01:47
Last Modified:	01 Apr 2021 01:47
URI:	http://repository.lppm.unila.ac.id/id/eprint/28376

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