摘要
To minimize the deviations of the net present values of project payment for both the owner and the client and optimize project payment schedules, a Nash equilibrium model based on game theory was set up and a genetic algorithm was developed to work out the Nash equilibrium solution with a two-stage backward inductive approach that requires the client responds to the owner’s payment schedule with an activity schedule so as to maximize the client’s net present value of cash flows. A case study demonstrated that a payment schedule at the Nash equilibrium position enables both the owner and the client to gain their desirable interests, thus is a win-win solution for both parties. Despite the computation time of the proposed algrithm in need of improving, combining Nash equilibrium and genetic algorithm into a complete-information dynamic-game model is a promising method for project management optimization.
To minimize the deviations of the net present values of project payment for both the owner and the client and optimize project payment schedules, a Nash equilibrium model based on game theory was set up and a genetic algorithm was developed to work out the Nash equilibrium solution with a two-stage backward inductive approach that requires the client responds to the owner＇s payment schedule with an activity schedule so as to maximize the client＇s net present value of cash flows. A case study demonstrated that a payment schedule at the Nash equilibrium position enables both the owner and the client to gain their desirable interests, thus is a win-win solution for both parties. Despite the computation time of the proposed algrithm in need of improving, combining Nash equilibrium and genetic algorithm into a complete-information dynamic-game model is a promising method for project management optimization.
基金
Funded by the Science Research Program of Hebei Province under Grant No. 2002135.
