Heuristic scheduling of resource-constrained projects with cash flows

Resource-constrained project scheduling with cash flows occurs in many settings, ranging from research and development to commercial and residential construction. Although efforts have been made to develop efficient optimal procedures to maximize the net present value of cash flows for resource-constrained projects, the inherent intractability of the problem has led to the development of a variety of heuristic methods to aid in the development of near-optimal schedules for large projects. This research focuses on the use of insights gained from the solution of a relaxed optimization model in developing heuristic procedures to schedule projects with multiple constrained resources. It is shown that a heuristic procedure with embedded priority rules that uses information from the revised solution of a relaxed optimization model increases project net present value. The heuristic procedure and nine different embedded priority rules are tested in a variety of project environments that account for different network structures, levels of resource constrainedness, and cash-flow parameters. Extensive testing with problems ranging in size from 21 to 1000 activities shows that the new heuristic procedures dominate heuristics using information from the critical path method, and in most cases outperform heuristics from previous research. The best performing heuristic rules classify activities into priority and secondary queues according to whether they lead to immediate progress payments, thus front loading the project schedule.