Speaker: Haoxiang Yang, Center for Nonlinear Studies, Los Alamos National Laboratory
Date/Time: August 13, 2019, 12:00pm-1:00pm
Location: Bahen Centre, Room 1220

Abstract: A stochastic disruption is a type of infrequent event in which the timing and the magnitude are random. We introduce the concept of stochastic disruptions and a stochastic optimization framework is proposed for such problems. In this talk, we present a special example: a project crashing problem under a single disruption. When a disruption occurs, the duration of an activity, which has not yet started, can change. Both the magnitude of the change of an activity’s duration and the timing of the disruption can be random. We prove that it is NP-hard to optimize the expected project span for this crashing problem, and illustrate its properties via examples. We formulate a stochastic mixed integer program (SMIP) with mixed integer recourse. This SMIP is computationally challenging to solve using existing techniques. We propose an adaptive branch-and-cut algorithm to solve the SMIP and evaluate the computational performance of our approach. Further extensions of such optimization models under stochastic disruptions can be applied to power system operations.

Full announcement at: MIE Events