Networks and Spatial Economics

, Volume 12, Issue 3, pp 421–439 | Cite as

An Efficient Hybrid Particle Swarm Optimization Algorithm for Solving the Uncapacitated Continuous Location-Allocation Problem

  • Abdolsalam Ghaderi
  • Mohammad Saeed Jabalameli
  • Farnaz Barzinpour
  • Ragheb Rahmaniani


Location-allocation problems are a class of complicated optimization problems that determine the location of facilities and the allocation of customers to the facilities. In this paper, the uncapacitated continuous location-allocation problem is considered, and a particle swarm optimization approach, which has not previously been applied to this problem, is presented. Two algorithms including classical and hybrid particle swarm optimization algorithms are developed. Local optima of the problem are obtained by two local search heuristics that exist in the literature. These algorithms are combined with particle swarm optimization to construct an efficient hybrid approach. Many large-scale problems are used to measure the effectiveness and efficiency of the proposed algorithms. Our results are compared with the best algorithms in the literature. The experimental results show that the hybrid PSO produces good solutions, is more efficient than the classical PSO, and is competitive with the best results from the literature. Additionally, the proposed hybrid PSO found better solutions for some instances than did the best known solutions in the literature.


Location Allocation Networks Local search Particle swarm optimization Hybrid algorithm 



Particle swarm optimization


Hybrid PSO




Uncapacitated continuous location-allocation problem




Simulated annealing


Tabu search


Genetic algorithm


Variable neighborhood search


Neural network


Local search


Alternate location-allocation


Interchange heuristic


Multi-start alternate algorithm


Variable neighborhood descent


Variable neighborhood decomposition search


Memetic algorithm



The authors wish to thank Prof. Michael Kuby for his helpful suggestions and anonymous referees for their valuable comments.


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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Abdolsalam Ghaderi
    • 1
  • Mohammad Saeed Jabalameli
    • 1
  • Farnaz Barzinpour
    • 1
  • Ragheb Rahmaniani
    • 1
  1. 1.Department of Industrial EngineeringIran University of Science and TechnologyTehranIran

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