Demand of emergency materials is usually uncertain and delayed as the latent period changes. With the consideration of the delay caused by the latent period of an epidemic, a multi-objective stochastic programming model for an emergency logistics network is constructed based on the epidemic diffusion rules. The genetic algorithm is adopted to solve the optimization model, and the application of...

Call center scheduling aims to set-up the workforce so as to meet target service levels. The service level depends on the mean rate of arrival calls, which fluctuates during the day and from day to day. The staff scheduling must adjust the workforce period per period during the day, but the flexibility in so doing is limited by the workforce organization by shifts. The challenge is to balance s...

This paper presents a decision making approach for mid-term scheduling of large industrial consumers based on the recently introduced class of Stochastic Dominance (SD)constrained stochastic programming. In this study, the electricity price in the pool as well as the rate of availability (unavailability) of the generating unit (forced outage rate) is considered as uncertain parameters. The self...

This paper, we presents a new primary-secondary-criteria scheduling model for resource-constrained project scheduling problem (RCPSP) with uncertain activity durations (UD) and cash flows (UC). The RCPSP-UD-UC approach producing a “robust” resource-feasible schedule immunized against uncertainties in the activity durations and which is on the sampling-based scenarios may be evaluated from a cos...

This paper considers evacuation via surface transportation networks in an uncertain environment. We focus on demand uncertainty which can lead to significant infeasibility cost during evacuation, where loss of life or property may appear. We develop a robust linear programming model based on a robust optimization approach where hard constraints are guaranteed within an appropriate uncertainty s...

We describe a two-stage robust optimization approach for solving network flow and design problems with uncertain demand. In two-stage network optimization one defers a subset of the flow decisions until after the realization of the uncertain demand. Availability of such a recourse action allows one to come up with less conservative solutions compared to single-stage optimization. However, this ...