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A modified multi-objective particle swarm optimisation algorithm for healthcare facility planning

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  • Sahar K. Elkady
  • Hisham M. Abdelsalam

Abstract

In this paper, a two-loop particle swarm optimisation (PSO) algorithm is proposed to solve multi-objective facility location-allocation problem for providing healthcare services. The problem is an extension of capacitated maximal covering location problem (CMCLP); besides the original function for maximising demand coverage, an additional objective function is added to minimise the travelled distance for the service seekers from outside the facility coverage area. The modified PSO is used with non-dominated sorting to solve the multi-objective problem attempting to find the best trade-off between the two objectives. Technique of order preference by similarity to ideal solution (TOPSIS) is used to consider the decision maker preferences of the solution. The algorithm performance is tested using a benchmark problem and the TOPSIS results are compared with the results from solving the problem represented as a single objective using weighting method. The proposed algorithm shows that locating the specialised facilities is done in a way that the trade-off between maximising demand coverage and minimising the travelled distance is optimised.

Suggested Citation

  • Sahar K. Elkady & Hisham M. Abdelsalam, 2016. "A modified multi-objective particle swarm optimisation algorithm for healthcare facility planning," International Journal of Business and Systems Research, Inderscience Enterprises Ltd, vol. 10(1), pages 1-22.
    • Handle: RePEc:ids:ijbsre:v:10:y:2016:i:1:p:1-22
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    References listed on IDEAS

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    Cited by:

    1. Derya Celik Turkoglu & Mujde Erol Genevois, 2020. "A comparative survey of service facility location problems," Annals of Operations Research, Springer, vol. 292(1), pages 399-468, September.

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