An efficient genetic algorithm to maximize net present value of project payments under inflation and bonus-penalty policy in resource investment problem

摘要

In order to develop a more realistic resource-constrained project-scheduling model that is applicable to real-world projects, in this paper, the resource investment problem with discounted cash flows and generalized precedence relations is investigated under inflation factor such that a bonus-penalty structure at the deadline of the project is imposed to force the project not to be finished beyond the deadline. The goal is to find activity schedules and resource requirement levels that maximize the net present value of the project cash flows. The problem is first mathematically modeled. Then, a genetic algorithm (GA) is designed using a new three-stage process that utilizes design of experiments and response surface methodology. The results of the performance analysis of the proposed methodology show an effective solution approach to the problem.