Enhanced trade-off of construction projects: Finance-resource-profit

The parameters of finance requirements, resource leveling, and anticipated profit have significant influence on many aspects of project management. These parameters interact and occasionally conflict with each other. Accordingly, achievement of a balance between these three parameters is crucial to ensure the accomplishment of project objectives. A multi-objective multimode scheduling optimization algorithm is proposed to establish the optimal trade-off between these three parameters. The strength Pareto evolutionary algorithm (SPEA) was implemented to obtain the solutions comprising the Pareto-optimal trade-off. The developed SPEA was validated by reproducing identical results of a time/cost trade-off problem in the literature. The developed SPEA was used to obtain the Pareto-optimal trade-off of a network of nine multimode activities that comprised fifty solutions. The trade-off of fifty solutions allows decision makers explore the impact of finance upon the efficiency of resource utilization and anticipated profit and thus select the solution that achieves the desired balance between the parameters. In addition, a fuzzy-based technique was used to identify the best compromise solution of the fifty solutions. The results proved the robustness and scalability of the developed algorithm. Finally, the finance-resource-profit trade-off offers potential solutions of maximized anticipated profit.