This paper surveys the use of Monte Carlo sampling-based methods for stochastic
optimization problems. Such methods are required when—as it often happens in practice …

Over the past two decades, there has been explosive growth in the application of robust
optimization in operations management (robust OM), fueled by both significant advances in …

Faults on overhead power line infrastructures in electric power distribution systems (DSs)
can potentially ignite catastrophic wildfires, especially in areas exposed to high wind …

The aim of this study is to investigate the solution algorithm for solving the problem of
determining reliable shortest paths in road networks with stochastic travel times. The …

We consider a class of routing optimization problems under uncertainty in which all
decisions are made before the uncertainty is realized. The objective is to obtain optimal …

Emergency vehicles (EMVs) play a crucial role in responding to time-critical calls such as
medical emergencies and fire outbreaks in urban areas. Existing methods for EMV dispatch …

Aiming to provide a generic modeling framework for finding reliable paths in dynamic and
stochastic transportation networks, this paper addresses a class of two-stage routing models …

This paper addresses the problem of finding optimal paths in a network where all link travel
times are stochastic and time-dependent, and correlated over time and space. A disutility …

In this paper we study optimization problems with second-order stochastic dominance
constraints. This class of problems allows for the modeling of optimization problems where a …

This paper studies the problem of deploying electric bicycle (e-bike) sharing stations and
determining their capacities, ie the number of shared e-bikes and charging piles …