The stochastic discrete time-cost tradeoff problem with decision-dependent uncertainty

Abstract

In this chapter we examine how managerial flexibility can be incorporated into project management techniques where project activities are executed under time-cost tradeoff settings and uncertainty. We advocate the use of a stochastic dynamic model where the activity scheduling decisions are taken dynamically over time thus offering flexibility to the decision maker of adjusting the decisions according to observations. To this end, we show that the problem is amenable to a Multi-Stage Stochastic Integer Programming approach with decision-dependent uncertainty as the decisions influence the revelation time of the random variables. We present the mathematical formulation of this problem and develop algorithmic approaches for obtaining effective lower and upper bounds. Our extensive computational results, based on a large number of test instances of varying size and degree of uncertainty, demonstrate the effectiveness of the proposed approaches in finding tight bounds for a class of non-standard stochastic programs bearing additional computational complexity.