Giant Pacific octopus optimizer based on fitness-distance balance and natural survival method to solve time-cost-quality-labor trade-off problem in construction projects

To successfully arrange, execute, monitor, and complete a project, a project manager must play a key role in project management. The utilization of technology and artificial intelligence in the engineering industry has grown absolutely essential and guarantees that each nation's socioeconomic development needs are accomplished. This study proposes the Giant Pacific Octopus Optimizer Based on Fitness-Distance Balance and Natural Survivor Method to tackle the challenge of optimizing the optimal combination of time, cost, quality, and labor tradeoff in the construction industry. The Natural Survivor Method and Fitness Distance Balance selection techniques, along with the Tournament Selection technique, are used in this research to redesign and further enhance the mechanism of the Giant Pacific Octopus Optimizer, which enhances the convergence time by rapidly transitioning from random selection to best candidate selection. The results of Giant Pacific Octopus Optimizer Based on Fitness-Distance Balance and Natural Survivor Method were compared with many well-known, comparable algorithms to demonstrate the viability and effectiveness of the proposed model through case study of construction management, Friedman test, Wilcoxon Signed Rank test, Indicators evaluation and Stability analysis. Based on the results obtained, a robust model that is superior to the evaluated models was developed in this research.