Building projects with time–cost–quality–environment trade-off optimization using adaptive selection slime mold algorithm

Abstract

Every project manager deals with various challenges, and almost all tasks have backup plans to ensure efficient success. Therefore, it is essential to manage resources, notably in terms of time, cost, quality, and environmental impact, and this needs to be thoroughly shown. As a result, the adaptive selection slime mold algorithm (ASSMA) is proposed for repetitive projects due to multiple concurrent instances. It is made by merging the tournament selection (TS) method and the slime mold algorithm (SMA) model. The new model’s capabilities are demonstrated using a case study of a rural water pipeline project, and the outcomes of the ASSMA are contrasted with those of the data envelopment analysis (DEA) approach utilized by the previous researcher. Consequently, the ASSMA technique is an effective optimization matching method that can help project managers select the best strategy for a given activity. This study is anticipated to expand significantly and outperform other models by utilizing quality performance metrics.