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A bi-objective multi-facility location-allocation problem with probabilistic customer locations and arrivals: two meta-heuristics using discrete approximation

Mohammadivojdan, R ; Sharif University of Technology | 2018

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  1. Type of Document: Article
  2. Publisher: World Academic Union , 2018
  3. Abstract:
  4. In this work, a bi-objective multi-facility location-allocation problem is investigated, in which the locations of the customers and their arrivals are stochastic. We first formulate the problem as a continuous location-allocation model with no constraints on the capacity of the facilities. Then, we develop an approximated discrete model in which the facilities with limited capacities can be located on a set of candidate points. The proposed model has two objective functions that are evaluated using discrete event system simulation. The first objective is to minimize the expected total time the customers spend in the system until their services begin. The time that each customer spends in the system includes the customer's travel time as well as his/her waiting time in the facility until he/she receives service. The second objective is to minimize the sum of the expected queue lengths. Considering the NP-hardness of the problem and the unique properties of the objective functions, a Non-dominated Sorting Genetic Algorithm (NSGA-II) is developed to obtain a Pareto optimal front. We have proposed a heuristic approach for generating feasible solutions to initiate NSGA-II. Since there is no benchmark available in the literature, in order to evaluate the obtained results, we have utilized another multi-objective meta-heuristic approach called Non-dominated Ranked Genetic Algorithm (NRGA). For further validation, we have also employed a genetic algorithm to solve two single-objective problems separately. © 2018 World Academic Press, UK. All rights reserved
  5. Keywords:
  6. Genetic algorithm ; Multi-facility location-allocation ; NSGA-II
  7. Source: Journal of Uncertain Systems ; Volume 12, Issue 2 , 2018 , Pages 123-140 ; 17528909 (ISSN)
  8. URL: http://www.worldacademicunion.com/journal/jus/jusVol12No2paper04.pdf