A Novel Hybrid Metaheuristic Algorithm for Optimization of Construction Management Site Layout Planning

Algorithms

Satria Fadil Persada¹  Doddy Prayogo²  Yu-Wei Wu³  Min-Yuan Cheng³  Vincent F. Yu⁴  A. A. N. Perwira Redi⁵  Reny Nadlifatin⁶ 

[1] Department of Business Management, Institut Teknologi Sepuluh Nopember, 60111 Jawa Timur, Indonesia;Department of Civil Engineering, Petra Christian University, 60236 Jawa Timur, Indonesia;Department of Civil and Construction Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan;Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 10607, Taiwan;Department of Logistic Engineering, Universitas Pertamina, 12220 Jakarta, Indonesia;Department of Technology Management, Institut Teknologi Sepuluh Nopember, 60111 Jawa Timur, Indonesia;

关键词: algorithms;    metaheuristic;    optimization;    symbiotic organisms search;    construction;    site layout planning;   

DOI  :  10.3390/a13050117

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown