A multi-objective genetic algorithm for a bi-objective facility location problem with partial coverage

DOI10.1007/s11750-015-0386-8zbMath1338.90373OpenAlexW563863936MaRDI QIDQ286207

Ahmet Silav, Esra Köktener Karasakal

Publication date: 20 May 2016

Published in: Top (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11750-015-0386-8

zbMATH Keywords

facility locationmulti-objective genetic algorithmmaximal coverageP-centerpartial coverage

Mathematics Subject Classification ID

Multi-objective and goal programming (90C29) Approximation methods and heuristics in mathematical programming (90C59) Discrete location and assignment (90B80)

Related Items (3)

Joint production and preventive maintenance scheduling for a single degraded machine by considering machine failures ⋮ A reference point-based evolutionary algorithm for approximating regions of interest in multiobjective problems ⋮ \(k\)-balanced center location problem: a new multi-objective facility location problem

Uses Software

• Genocop
• GAMS
• SPEA2
• FastPGA

Cites Work

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• A crossover operator that uses Pareto optimality in its definition
• The \(p\)-median problem: a survey of metaheuristic approaches
• A fuzzy multi-objective programming for optimization of fire station locations through genetic algorithms
• Generalized coverage: new developments in covering location models
• Multiple criteria facility location problems: a survey
• Multi-criteria location planning for public facilities in tsunami-prone coastal areas
• A multi-objective model for locating fire stations
• The gradual covering decay location problem on a network.
• A maximal covering location model in the presence of partial coverage
• Design and analysis of hybrid metaheuristics for the reliability \(p\)-median problem
• Covering models and optimization techniques for emergency response facility location and planning: a review
• Hybrid biobjective evolutionary algorithms for the design of a hospital waste management network
• Solution methods for the bi-objective (cost-coverage) unconstrained facility location problem with an illustrative example
• Solving the maximal covering location problem with heuristic concentration
• A single-point mutation evolutionary programming
• A fuzzy multi-objective covering-based vehicle location model for emergency services
• Solving large-scale uncapacitated facility location problems with evolutionary simulated annealing
• The Maximum Coverage Location Problem
• Evolutionary Algorithms for Solving Multi-Objective Problems
• On a Bicriterion Formulation of the Problems of Integrated System Identification and System Optimization
• On the use of genetic algorithms to solve location problems

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