Selecting a location has great influence on production cost or service units and also accessibility of production resources such as facilities transportation raw material and labour. In today's competitive environment, selecting a proper location to establish different locations such as banks branches, delivering services to enhance customer satisfaction and absorbing more demand into the market is very crucial for organisations. In this research, a multi objective hybrid model was developed for selecting optimum locations. The main objective was to maximise convergence of the demand points as well as maximising distance of the selected locations. To meet these objectives, local reliability-based maximum expected covering location problem (LR-MEXCLP) was employed. Moreover, maximising efficiency of the selected locations was also considered accordingly. In this context, data envelopment analysis (DEA) was benefited. As in real environment, the exact data for location problem usually are not available; to solve this problem, a fuzzy number was used for the model parameter and consequently, a non-dominated sorting genetic algorithm II (NSGA-II) was applied.
|Number of pages||31|
|Journal||International Journal of Industrial and Systems Engineering|
|Early online date||25 Jul 2016|
|Publication status||Published - 2016|
- location selection
- facility location
- data coverage
- maximum coverage
- maximum dispersion
- fuzzy DEA
- data envelopment analysis
- genetic algorithms
- multi-objective optimisation.