Immediately after a disruption, in order to minimize the negative impact inflicted on society, its imperative re-establish interdicted critical services enabled by infrastructure networks. In this paper, we study stochastic network recovery problem that tackles planning of restoration activities (considering limited resources) links so pre-disruption service flows can be re-established as quick...

The life of many people in the world is under the danger because of the accidents and unpredicted diseases, which require relief. Since, most of such cases occur in unpredictable condition, for an appropriate planning, the uncertain conditions should be investigated. Consequently, this paper investigates the integrated and multi-step process of locating, assigning and routing the air and la...

Stochastic programming is an optimization approach taking into account uncertainties in the system model. There are numerous possible applications of stochastic programming. The purpose of this short report is to introduce stochastic programming in simple, tutorial-like, terms. A simple example of an optimization of a covering gas demand is provided together with pointing out some fundamental p...

In this Appendix we first present the connection between the stochastic and the deterministic demand model used in Section 2 of the paper. We use the notation of the paper but also expand it as necessary to present the stochastic model and the results. In particular, we flesh out two dual based heuristics for the stochastic problem. Secondly, we briefly explain the connection between the stocha...

This paper considers a stochastic dynamic inventory problem involving a single item, linear cost structures, and finite distributions (but not necessarily independent) for the stochastic cost and demand parameters. We develop primal and dual algorithms for a multi-stage stochastic linear programming formulation for the problem. The complexity of the proposed algorithms is shown to be within O(N...

This paper considers a stochastic dynamic inventory problem involving a single item, linear cost structures, and finite distributions (but not necessarily independent) for the stochastic cost and demand parameters. We develop primal and dual algorithms for a multi-stage stochastic linear programming formulation for the problem. The complexity of the proposed algorithms is shown to be within O(N...

Abstract Uncertainty is everywhere in the food delivery process, which significantly influences decision-making for complex on-demand problems, affecting efficiency and customer satisfaction. Especially, service time an indispensable part of process impacted by various uncertain factors. Due to simplicity high accuracy requirement, we model as a Gaussian mixture (GMM). In detail, transform dist...

We expand the theory of consumer’s behavior, based on the Weak Axiom of Revealed Preference, to permit simultaneously both random choice and choice sets, which are not singletons. We provide a consistency postulate for demand behavior when such behavior is represented in terms of a stochastic demand correspondence. We show that, when the consumer spends her entire wealth, our rationality postul...