Department Seminar: Siqian Shen, University Of Florida - Wednesday, Feb 16 @ 8:00am
Expectation and Chance-constrained Models and Algorithms for Insuring Critical Paths
Abstract: We consider a class of two-stage stochastic integer programming problems arising in the protection of vital arcs in a critical path network. We analyze a problem in which task finishing times are uncertain, but can be insured a priori to mitigate potential delays. A decision maker must trade off costs incurred in insuring arcs with expected penalties associated with late project completion times, where lateness penalties are assumed to be general lower semi-continuous nondecreasing functions of completion time. We provide decomposition strategies to solve this problem with respect to either convex or nonconvex penalty functions. In particular, for the nonconvex penalty case, we employ the Reformulation-Linearization Technique to make the problem amenable to solution via Benders decomposition. We also consider a chance-constrained version of this problem, in which the probability of completing a project on time is sufficiently large. We demonstrate the computational efficacy of our approach by testing a set of randomly generated instances, using the Sample Average Approximation method to guide our scenario generation.
Audience-Based Site-Wide Navigation:back to top