Integrated Many-Objective Optimization for Decision-Making and Dynamic Project Control

Abstract: Construction projects involve conflicting objectives beyond time and cost, including quality, safety risk, resource stability, and environmental impact. Many-objective optimization (MaOO) helps address this complexity in planning, but it provides limited support for decision-making during execution, and selecting one solution from Pareto-sets often depends on human judgment. To overcome these gaps, this paper proposes an integrated planning and control framework combining Opposition-Based NSGA-III (OBNSGA-III) for six-objective optimization, an Entropy-based-VIKOR model for compromise solution selection, and a Dynamic-MaOO re-optimization mechanism for execution control. A case study based on 25-activities is used to demonstrate effective decision support from planning to execution.