Simulated annealing for financing cost distribution based project payment scheduling from a joint perspective

Based on the distribution of the project financing cost over the contractor and the client, this paper involves the project payment scheduling problem from a joint perspective of the two parties. In the problem, the project financing cost is defined as the expense for raising money from the outside or the opportunity cost of the capital devoted into the project and the objective is to find the project payment schedule that can not only maximize the joint revenue of the two parties but also be accepted by them. Based on the characteristics of the problem, an optimization model consisting of two submodels is constructed using the activity-based method. For the strong NP-hardness of the problem, two simulated annealing algorithms with different searching structures are developed and compared with the multi-start iterative improvement method on the basis of a computational experiment performed on a data set generated randomly. The results show that the simulated annealing algorithm with the nested loop module seems to be the most promising algorithm for solving the defined problem especially when the scale of the problem becomes larger. In addition, the influences of some key parameters on the computational results are investigated through the full factorial experiment and a few useful conclusions are drawn.