Optimizing Project Resources Using the Hybrid Multi-objective Algorithm and Decision-Making Method

Schedule, cost, quality control, and rational use of labor and resources are key factors that project management aims to achieve, and these factors have a complex relationship with each other. However, almost all existing trade-off analysis models have only focused on addressing the time-cost issue without simultaneously considering the impact of collision activities on quality costs. Moreover, the results will be influenced by several external elements that are uncertain and hard to identify, such as weather conditions, machine and equipment capability, and labor efficiency, among others. Therefore, this research aims to develop an optimal model of project resource balance with quality considerations (TCQT) by applying fuzzy logic, the multi-objective social group optimization (MOSGO) algorithm, and the multi-criteria decision-making method (MCDM), while also considering the uncertainty of input variables. In this paper, fuzzy logic is used to select input and defuzzification to filter the results according to various factors. Additionally, the MOSGO algorithm is applied to determine a set of Pareto-optimal time-cost-quality curves, and multi-criteria decision-making methods are used to obtain the best outcome. The expected research outcome is the introduction of an optimization model that combines SGO, fuzzy techniques, and MCDM to optimize problems requiring resources along with quality control (TCQT) and integrate uncertainty that occurs in actual large-scale projects.