Towards finding robust execution strategies for RCPSP/max with durational uncertainty

Abstract

Resource Constrained Project Scheduling Problems with minimum and maximum time lags (RCPSP/max) have been studied extensively in the literature. However, the more realistic RCPSP/max problems - ones where durations of activities are not known with certainty - have received scant interest and hence are the main focus of the paper. Towards addressing the significant computational complexity involved in tackling RCPSP/max with durational uncertainty, we employ a local search mechanism to generate robust schedules. In this regard, we make two key contributions: (a) Introducing and studying the key properties of a new decision rule to specify start times of activities with respect to dynamic realizations of the duration uncertainty; and (b) Deriving the fitness function that is used to guide the local search towards robust schedules. Experimental results show that the performance of local search is improved with the new fitness evaluation over the best known existing approach. Copyright © 2010, Association for the Advancement of Artificial Intelligence. All rights reserved.