Application and Exploration of Global Optimization Algorithm for Construction Projects in Project Cost Management

Construction quality, project progress, and cost are the three key control indicators in construction projects, which are interdependent and mutually influential. This paper constructs a multi-objective optimization model for schedule-cost-quality based on multi-objective optimization theory. Using an improved genetic algorithm to solve the problem, a Pareto solution set is obtained. Based on this, the entropy-VIKOR model is applied to make decisions on the solution set, identifying the optimal solution from the alternative options. This paper takes the YC Expressway Project as the research object for multi-objective optimization calculations in project cost management. Python programming is used for solution, resulting in an optimal construction period of 113 days, a reduction of 27 days compared to the planned 140 days. Costs were reduced by 1.4486 million yuan, and quality levels were improved. The optimization results validate the scientific and practical applicability of the project management multi-objective optimization model and the entropy value-VIKOR decision-making method.