Article2012

An Efficient Genetic Algorithm for Solving the Multi-Level Uncapacitated Facility Location Problem

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Facility Location and Emergency Management Metaheuristic Optimization Algorithms Research Optimization and Mathematical Programming

Abstract

In this paper a new evolutionary approach for solving the multi-level uncapacitated facility location problem (MLUFLP) is presented. Binary encoding scheme is used with appropriate objective function containing dynamic programming approach for finding sequence of located facilities on each level to satisfy clients' demands. The experiments were carried out on the modified standard single level facility location problem instances. Genetic algorithm (GA) reaches all known optimal solutions for smaller dimension instances, obtained by total enumeration and CPLEX solver. Moreover, all optimal/best known solutions were reached by genetic algorithm for a single-level variant of the problem.

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2018A novel metaheuristic approach for collaborative learning group formation 2012Metaheuristic methods for solving the Bilevel Uncapacitated Facility Location Problem with Clients' Preferences 2024Vertiport Infrastructure Location Optimization for Equitable Access to Urban Air Mobility 2011Exactly solving a two‐level location problem with modular node capacities

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