Dynamic Resource Constrained Multi-Project Scheduling Problem with Weighted Earliness/Tardiness Costs

Abstract

In this study, a conceptual framework is given for the dynamic resource-constrained multi-project scheduling problem with weighted earliness/tardiness costs (DRCMPSPWET), and a mathematical programming formulation of the problem is provided. In DRCMPSPWET, a project arrives on top of an existing project portfolio, and a due date has to be quoted for the new project while minimizing the costs of schedule changes. The objective function consists of the weighted earliness/tardiness costs of the activities of the existing projects in the current baseline schedule plus a term that increases linearly with the anticipated completion time of the new project. An iterated local search (LS)-based approach is developed for large instances of this problem. In order to analyze the performance and behavior of the proposed method, a new multi-project data set is created by controlling the total number of activities, the due date tightness, the due date range, the number of resource types, and the completion time factor in an instance. A series of computational experiments are carried out to test the performance of the LS approach. Exact solutions are provided for small instances. The results indicate that the LS heuristic performs well in terms of both solution quality and solution time.