Robust supplier selection problem, in a scenario-based approach has been proposed, when the demand and exchange rates are subject to uncertainties. First, a deterministic multi-objective mixed integer linear programming is developed; then, the robust counterpart of the proposed mixed integer linear programming is presented using the recent extension in robust optimization theory. We discuss dec...

Stochastic differential equations (SDEs) have been applied by engineers and economists because it can express the behavior of stochastic processes in compact expressions. In this paper, by using Grunwald-Letnikov fractional derivative, the stochastic differential model is improved. Two numerical examples are presented to show efficiency of the proposed model. A numerical optimization approach b...

This paper deals with day-ahead programming under uncertainties in microgrids (MGs). A two-stage stochastic programming with the fixed recourse approach was adopted. The studied MG was considered in the grid-connected mode with the capability of power exchange with the upstream network. Uncertain electricity market prices, unpredictable load demand, and uncertain wind and solar power values, du...

in this paper, we consider a stochastic time-cost tradeoff problem (tctp) in pert networks for project management, in which all activities are subjected to a linear cost function and assumed to be exponentially distributed. the aim of this problem is to maximize the project completion probability with a pre-known deadline to a predefined probability such that the required additional cost is min...

Maintenance optimization has been extensively studied in the past decades. However, most of existing maintenance models focus on single-component systems and are not applicable to complex consisting multiple components, due various interactions among components. The multicomponent problem, which joins stochastic processes regarding failures components with combinatorial problems grouping activi...

In the context of public transportation system, improving the service quality and robustness through minimizing the average passengers waiting time is a real challenge. This study provides robust stochastic programming models for train timetabling problem in urban rail transit systems. The objective is minimization of the weighted summation of the expected cost of passenger waiting time, its va...