A scatter search procedure for maximizing the net present value of a project under renewable resource constraints

In this paper, we present a meta-heuristic algorithm for the well-known resource-constrained project scheduling problem with discounted cash flows. This optimization procedure maximizes the net present value of project subject to the precedence and renewable resource constraints. The problem is known to be NP-hard. We investigate the use of a enhanced bi-directional generation scheme and a recursive forward/backward improvement method and embed them in a meta-heuristic scatter search framework. We generate a large dataset of project instances under a controlled design and report detailed computational results. The solutions and project instances can be downloaded from a website in order to facilitate comparison with future research attempts.