A Study of Resource-Constrained Project Optimization with Discounted Weighted Earliness-Tardiness Penalty Costs

This research consider a project scheduling problem with the object of minimizing weighted earliness-tardiness penalty costs, subject to precedence relations among the activities and resource-constrained. Project activities are assumed to have a known deterministic due date, a unit earliness as well as a unit tardiness penalty cost and constant renewable resource requirements. The objective is to schedule the activities in order to minimize the total weighted earliness–tardiness penalty cost of the project subject to the finish–start precedence constraints and the constant renewable resource availability constraints. With these features the problem becomes highly attractive in just-in-time environments. A genetic algorithm (GA) is proposed to solve this model. In addition design of experiments and response surface methodology are employed to tune the GA parameters and to evaluate the performance of the proposed method in 270 test problems. The results of the performance analysis will be shown at the end of this paper.