Abstract
Numerous optimization techniques have been proposed for use in order to address issues with various building project components. It has become easier to solve difficult optimization issues in practice due to the development of numerous innovative algorithms in recent years. The utilization of the Slime Mold Algorithm model to optimize time, cost, and quality trade-off problems (TCQT) in this article. The effectiveness of the SMA model was analyzed, evaluated, and compared with the outcomes produced by the opposition-based multi-objective differential evolution (OMODE), nondominated sorting genetic algorithm II (NSGA-II), multiobjective particle swarm optimization (MOPSO), and multi-objective particle swarm optimization (MODE). The aforementioned results demonstrated the model’s potential as a strategy by substituting the three - factor approach and processing-time optimal. The management of project time, cost and quality is decisive for investment management activities.
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