Two-Phase Differential Evolution for the Multiobjective Optimization of Time–Cost Tradeoffs in Resource-Constrained Construction Projects

Concurrent minimization of project time and project cost is an important issue in construction planning and management. Tradeoff optimization between these two variables is necessary to maximize overall construction project benefit. This paper presents a two-phase differential evolution (DE) model to resolve these problems. This model is able to effectively consider both time-cost effects and resource constraints. First, we introduce a novel multiple-objective algorithm, the chaotic initialized multiple objective differential evolution with adaptive-mutation strategy-based time-cost tradeoff, to determine the execution mode that best optimizes the time-cost balance. Subsequently, we introduce a DE-based resource-constrained method to generate a feasible schedule. A real construction case study is then used to illustrate the application of the proposed algorithm. Performance comparisons done with the nondominated sorting genetic algorithm, multiple objective particle swarm optimization, and multiple objective differential evolution further verify the efficiency and effectiveness of the proposed algorithm.