Investigating multi-objective time, cost, and risk problems using the Grey Wolf Optimization algorithm
Mehmet Yilmaz1 (orcid id: 0000-0001-6164-6233)
Tayfun Dede2 (orcid id: 0000-0001-9672-2232)
Maksym Grzywiński3 (orcid id: 0000-0003-4345-3897)
1 Erzincan Binali Yıldırım University, Turkey
2 Karadeniz Technical University, Turkey
3 Czestochowa University of Technology, Poland
DOI: 10.17512/bozpe.2023.12.09
Article (PDF)
KEYWORDS
multi-objective optimization, grey wolf optimization algorithm, time-cost-risk
ABSTRACT
Safety plays a crucial role in construction projects. Safety risks encompass potential hazards such as work accidents, injuries, and security. Consequently, it is important to effectively manage these risks with equal emphasis on time and cost considerations during the project planning phase. Within the scope of this research, the grid and archive-based Grey Wolf Optimizer (GWO) algorithm was employed to investigate multi-objective time-cost-risk problems. By employing the GWO, multiple Pareto solutions were provided to the decisionmaker, facilitating improved decision-making. It was determined that the GWO algorithm yields better results in time-cost-risk problems compared to the Particle Swarm Optimization (PSO) and Differential Evolution (DE) algorithms.
Politechnika Częstochowska uczelnią dostępną.
