Study of payment scheduling problem to achieve client–contractor agreement.

This paper aims to determine simultaneously the amount, timing, and location of progress payments in projects in order to achieve a set of equitable solutions in the client–contractor negotiation process. The objective function tries to minimize the distance between the final solutions and the best achievable solutions of the client and the contractor. Due to combinatorial nature of the proposed problem, an iterative two-stage search method is proposed. In the first stage, a set of payments is determined to maximize the contractor's net present value (NPV), another set to maximize the client's NPV, and another one to minimize the objective function. In the second stage, activities are rescheduled to improve the solutions by fixing the amount and location of progress payments. A hybrid meta-heuristic algorithm named GASA, along with a simulated annealing (SA) and a genetic algorithm (GA), is introduced for the first stage, while the activities are optimally scheduled in the second stage. It has been shown that SA is better for the contractor's objective function and GA for the client's objective function, but GASA is the best in all situations; besides, the proposed method has represented to be an efficient approach to obtain non-dominated solutions in the client–contractor negotiation process. [ABSTRACT FROM AUTHOR]