In this article we present an effective mixed-integer linear programming (MILP) formulation for design of a multi-echelon stochastic inventory system with uncertain customer demands. In You and Grossmann [2010] a three-echelon supply chain with inventories under uncertainty is presented. In that supply chain, the location of the plants and the customer demand zones (CDZ) are known. Potential di...

The dynamic vehicle allocation problem arises when a motor carrier must simultaneously and in real time coordinate the dispatching of vehicles from one region to the next all over the country. The decision to send a vehicle loaded or empty from one region to the next, arriving in the destination region at some point in the future, must anticipate the downstream impacts of the decision. The cons...

Content Delivery Networks (CDNs) have been identified as one of the relevant use cases where the emerging paradigm of Network Functions Virtualization (NFV) will likely be beneficial. In fact, virtualization fosters flexibility, since on-demand resource allocation of virtual CDN nodes can accommodate sudden traffic demand changes. However, there are cases where physical appliances should still ...

We propose a simple model of optimal stopping where the economic environment changes as a result of learning. A primary application of our framework is an optimal job search problem when the worker’s labour market opportunities are initially uncertain. We distinguish between two interpretations of the model. In the first, a worker learns about common market conditions, such as the number of pot...

I introduce irrational types, who are committed to their demands, into a bargaining model with an uncertain deadline for agreement. Rational agents imitate these demands, hoping to benefit from a “tough” reputation. When irrational types are committed to fixed demands and agents are patient, this provides an explanation for “deadline effects” in bargaining: agreement is “U-shaped”, occurring ei...

The availability of a good hydraulic model increases the reliability of the results of methodologies using it. Thus, the calibration of the model is a previous step that has to be done. The most uncertain parameters of the model are demands due to their constant variability. However, calibrating these demands requires a high computational cost that can be reduced by redefining the unknown param...

In this paper, we used the fuzzy set theory for modeling flexible constraints and uncertain data in nurse scheduling problems and proposed a fuzzy linear model for nurse rostering problems. The developed model can produce rosters that satisfy hospital objectives, ward requirements and staff preferences by satisfying their requests as much as possible. Fuzzy sets are used for modeling demands of...

This paper proposes a modified non-dominated sorting genetic algorithm (NSGA-II) for a bi-objective location-allocation model. The purpose is to define the best places and capacity of the distribution centers as well as to allocate consumers, in such a way that uncertain consumers demands are satisfied. The objectives of the mixed-integer non-linear programming (MINLP) model are to (1) minimize...

We introduce and study the following model for routing uncertain demands through a network. We are given a capacitated multicommodity flow network with a single source and multiple sinks, and demands that have known values but unknown sizes. We assume that the sizes of demands are governed by independent distributions, and that we know only the means of these distributions and an upper bound on...