Minimal covering unrestricted location of obnoxious facilities: bi-objective formulation and a case study

Kayhan Alamatsaz (), S. M. T. Fatemi Ghomi () and Mehdi Iranpoor ()
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Kayhan Alamatsaz: Amirkabir University of Technology
S. M. T. Fatemi Ghomi: Amirkabir University of Technology
Mehdi Iranpoor: Isfahan University of Technology

OPSEARCH, 2021, vol. 58, issue 2, No 4, 373 pages

Abstract: Abstract This paper addresses the problem of locating obnoxious facilities aiming to mitigate the adverse effects of such facilities by minimizing the total covered demand and reducing the harmful effects of multiple-coverage by placing the facilities far from each other. Unlike the classical approaches, it is assumed that the facilities can be located not only on the nodes but also on the network’s edges. Additionally, demands are not restricted to reside on the nodes but are distributed along the edges. In such a condition, the problem of locating obnoxious facilities is much closer to the real-world. A bi-objective mixed-integer linear programming formulation is developed for this novel problem. This bi-objective problem is solved using the ε-constraint method and NSGA-II. The ε-constraint method can be used to solve the small and medium-sized problems optimally in a reasonable time. As a realistic example, this approach is implemented in a case study in Isfahan for a particular urban planning problem. The case is locating obnoxious solid waste disposal facilities that should be located as far away as possible and simultaneously cover the least demands. Large scale problems cannot be solved efficiently using the ε-constraint method. However, the numerical analysis showed the efficiency and effectiveness of the NSGA-II approach for these problems. Finally, sensitivity analysis is applied to evaluate the effect of changes in coverage distance and the number of facilities on the conflicting objective functions.

Keywords: Obnoxious facility; Minimal covering; p-Dispersion; Bi-objective optimization; NSGA-II; Case study (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s12597-020-00487-0

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