{"title":"A Novel Pareto-Based Meta-Heuristic Algorithm to Optimize Multi-Facility Location-Allocation Problem","authors":"Vahid Hajipour, Samira V. Noshafagh, Reza Tavakkoli-Moghaddam","volume":79,"journal":"International Journal of Industrial and Manufacturing Engineering","pagesStart":1442,"pagesEnd":1446,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/16407","abstract":"
This article proposes a novel Pareto-based multiobjective
\r\nmeta-heuristic algorithm named non-dominated ranking
\r\ngenetic algorithm (NRGA) to solve multi-facility location-allocation
\r\nproblem. In NRGA, a fitness value representing rank is assigned to
\r\neach individual of the population. Moreover, two features ranked
\r\nbased roulette wheel selection including select the fronts and choose
\r\nsolutions from the fronts, are utilized. The proposed solving
\r\nmethodology is validated using several examples taken from the
\r\nspecialized literature. The performance of our approach shows that
\r\nNRGA algorithm is able to generate true and well distributed Pareto
\r\noptimal solutions.<\/p>\r\n","references":"
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