abbreviate title: " ABC " classification with uncertain data 2 " ABC " CLASSIFICATION WITH UNCERTAIN DATA. This study presents an alternative way of classifying the different productive items of a company. A fuzzy model for the magnitudes involved (demand and cost) is described. This model contrasts with the classic Pareto classification (ABC), which ranks productive items according to their im...

We consider customer response time minimization in a two-echelon supply chain system with stochastic demand where the first echelon consists of one production plant and the other of one retailer. Traditionally models of this type only seek to minimize traditional operating costs. However, because of the highly competitive nature of the market, it is also essential for the manufacturer to respon...

This report documents the development of several transportation optimization models under uncertainty. First, a robust evacuation transportation planning model for freeway traffic systems was developed, in which demand is uncertain. The study results provide preliminary evidence that routing traffic using such a robust, optimization-based model can improve the average objective performance. Nex...

M any firms face environments with long manufacturing leadtimes, great product variety, and uncertain, nonstationary demand. A challenge is how to plan production and inventories to provide the best customer service at the least cost. In this paper, we first describe an application at Teradyne in which we implemented an inventory hedge to protect against cyclic demand variability. Based on this...

Manufacturers make production decisions and carry inventory to satisfy uncertain demand. When holding and shortage costs are high, carrying inventory could be even more expensive for a capacitated production system. Recent developments in information technology and sales strategies enabled firms to acquire, collect, or induce advance demand information. We address a periodic-review, stochastic,...

Robust optimization (RO) is a distribution-freeworst-case solutionmethodology designed for uncertain maximization problems via a max-min approach considering a bounded uncertainty set. It yields a feasible solution over this set with a guaranteed worst-case value. As opposed to a previous conception that RO is conservative based on optimal value analysis, we argue that in practice the uncertain...

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...