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Dynamic maximal covering location problem for fire stations under uncertainty: soft-computing approaches

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Abstract

In this paper, a mathematical formulation is presented for fire station’s locating and facilities allocating to stations in different periods and emergency situations (wars and natural disasters). This model is designed, considering amount of demands and facilities coverage radius, being dynamic based on traffic and type region and fuzzy in different periods. According to fact, in the model, amount of demand for each demand point depends on number of coverage and the location. In this model, location of stations is positioned once in different periods. The number of facilities which are allocated to stations are located dynamically and can be relocated in different periods. Since the proposed model is NP-hard, particle swarm optimization (PSO) and artificial bee colony (ABC) algorithms by considering an efficient combinatorial chromosome are presented to solve the problem at hand. In the PSO, way of making chromosome is such that locating chromosome, early and final allocation are presented in a novel approach. The results demonstrated that the presented PSO are better than ABC in terms of quality of solutions and computational time.

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Authors and Affiliations

  1. Department of Industrial Engineering, Faculty of Engineering, Islamic Azad University, West Tehran Branch, Tehran, Iran

    Vahid Hajipour

  2. Department of Industrial Engineering, Faculty of Engineering, Alzahra University, Tehran, Iran

    Parviz Fattahi & Samaneh Babaei Morad

  3. Department of Industrial Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamadan, Iran

    Hasan Bagheri

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  1. Vahid Hajipour
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  2. Parviz Fattahi
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  4. Samaneh Babaei Morad
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Correspondence to Vahid Hajipour.

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Hajipour, V., Fattahi, P., Bagheri, H. et al. Dynamic maximal covering location problem for fire stations under uncertainty: soft-computing approaches. Int J Syst Assur Eng Manag 13, 90–112 (2022). https://doi.org/10.1007/s13198-021-01109-8

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  • DOI: https://doi.org/10.1007/s13198-021-01109-8

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