Abstract
Symbiotic organisms search (SOS) is a promising metaheuristic algorithm that has been studied recently by numerous researchers due to its capability to solve various hard and complex optimization problems. SOS is a powerful optimization technique that mimics the simulation of the typical symbiotic interactions among organisms in an ecosystem. This study presents a new SOS-based hybrid algorithm for solving the challenging construction site layout planning (CSLP) discrete problems. A new algorithm called the hybrid symbiotic organisms search with local operators (HSOS-LO) represents a combination of the canonical SOS and several local search mechanisms aimed at increasing the searching capability in discrete-based solution space. In this study, three CSLP problems that consist of single and multi-floor facility layout problems are tested, and the obtained results were compared with other widely used metaheuristic algorithms. The results indicate the robust performance of the HSOS-LO algorithm in handling discrete-based CSLP problems.
Highlights
Determining the best site and facility layout, especially for large construction projects, has always been a critical and challenging task for construction managers
This study proposes a novel hybrid metaheuristic algorithm called hybrid symbiotic organisms search with local operators (HSOS-LO) for solving the construction site layout planning (CSLP) problem
This paper presented a novel optimization algorithm named hybrid symbiotic organisms search with local operators (HSOS-LO)
Summary
Determining the best site and facility layout, especially for large construction projects, has always been a critical and challenging task for construction managers. In the case of CSLP with a large number of facilities, it is hard to determine the optimal solution within an acceptable time frame [5]. The exact approaches are often inadequate in tackling large problems, while the heuristic search techniques appear reasonable since they are an inexact method for obtaining near-optimal solutions. Most metaheuristic algorithms allow their searching mechanism to accept less preferable candidate solutions leading to a wider solution space coverage and possibly a better result in comparison to the traditional heuristic methods. Cheng and Prayogo introduced a metaheuristic optimization algorithm, known as the symbiotic organisms search (SOS) [20]. This study proposes a novel hybrid metaheuristic algorithm called hybrid symbiotic organisms search with local operators (HSOS-LO) for solving the CSLP problem.
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