# On the fuzzy maximal covering location problem

## TL;DR

This paper addresses the fuzzy maximal covering location problem by developing a fuzzy model and an algorithm that guarantees Pareto optimal solutions, validated through computational experiments.

## Contribution

It introduces a fuzzy perspective to the maximal covering location problem and proposes a novel solution algorithm with proven Pareto optimality.

## Key findings

- Algorithm produces Pareto optimal solutions.
- Fuzzy model validated through properties and experiments.
- Computational results demonstrate effectiveness.

## Abstract

In this paper studies the maximal covering location problem, assuming imprecise knowledge of all data involved. The considered problem is modeled from a fuzzy perspective producing suitable fuzzy Pareto solutions. Some properties of the fuzzy model are studied, which validate the equivalent mixed-binary linear multiobjective formulation proposed. A solution algorithm is developed, based on the augmented weighted Tchebycheff method, which produces solutions of guaranteed Pareto optimality. The effectiveness of the algorithm has been tested with a series of computational experiments, whose numerical results are presented and analyzed