Solving large-scale maximum expected covering location problems by genetic algorithms: a comparative study

DOI10.1016/S0377-2217(01)00260-0zbMath1081.90573MaRDI QIDQ1847206

Cem Saydam, Haldun Aytug

Publication date: 17 November 2002

Published in: European Journal of Operational Research (Search for Journal in Brave)

zbMATH Keywords

Genetic algorithmsInteger programmingLocation

Mathematics Subject Classification ID

Large-scale problems in mathematical programming (90C06) Approximation methods and heuristics in mathematical programming (90C59) Discrete location and assignment (90B80)

Related Items (14)

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Uses Software

• CPLEX
• Genocop

Cites Work

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• Review, extension and prediction in emergency service siting models
• The queueing maximal availability location problem: A model for the siting of emergency vehicles
• A genetic algorithm for the set covering problem
• Genetic learning of dynamic scheduling within a simulation environment
• Strategic facility location: A review
• Comparison of genetic algorithms, random restart and two-opt switching for solving large location-allocation problems
• The Maximal Expected Covering Location Problem: Revisited
• Solving an ambulance location model by tabu search
• The congested facility location problem
• Genetic Algorithms and Random Keys for Sequencing and Optimization
• Genetic Algorithms for Combinatorial Optimization: The Assemble Line Balancing Problem
• The Maximum Availability Location Problem
• Stopping Criteria for Finite Length Genetic Algorithms
• The Location of Emergency Service Facilities

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