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Construction site layout planning and safety management using fuzzy-based bee colony optimization model

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Abstract

The construction site layout planning is an activity that establishes the temporary facility location, thereby enhancing the efficiency of the construction. Recently, safety enhancement plays a significant role in construction site layout planning. This paper aims in developing an optimal construction site layout planning by fulfilling three main objectives, namely minimum cost facility, minimum risk of safety facility and minimum noise pollution. In addition to this, this paper also proposes a fuzzy-based bee colony optimization (FBCO) algorithm for tuning ρ and τ parameters so as to obtain a feasible and optimal solution. Also, this FBCO algorithm is employed to solve the construction site layout problem by satisfying the multi-objective function. Then, an FBCO-CLP approach is employed in obtaining a final optimal construction site layout plan. Moreover, the performance analysis of FBCO employs five benchmark functions to examine the effectiveness of the system for numerous aspects. Finally, a case study utilizes a residential building for verifying the proposed approach containing 13 temporary facilities. The experimental result reveals that the proposed FBCO-CSLP approach provides an optimal layout plan with minimum cost, noise pollution and safety risk facilities. Moreover, the comparative analysis is done by comparing the proposed approach with various other approaches such as ANN, GA, PSO, ABC and DE for three different types of facilities, namely cost facility, safety facility risk and noise facility. The experimental analysis reveals that the proposed approach provides better performances when compared with all other approaches.

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  1. Department of Project Management, Faculty of Civil Engineering, Ho Chi Minh City Open University, Ho Chi Minh City, Vietnam

    Phong Thanh Nguyen

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  1. Phong Thanh Nguyen
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Nguyen, P.T. Construction site layout planning and safety management using fuzzy-based bee colony optimization model. Neural Comput & Applic 33, 5821–5842 (2021). https://doi.org/10.1007/s00521-020-05361-0

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