We introduce a unified modeling and solution framework for various classes of rich vehicle and inventory routing problems as well as other probability-based routing problems with a time-horizon dimension. Demand is assumed to be stochastic and non-stationary, and is forecast using any forecasting model that provides expected demands over the planning horizon, with error terms from any empirical...

X. Yao et al (Eds.): PPSN VIII, LNCS 3242, pp. 450–460, 2004. c © Springer-Verlag Berlin Heidelberg 2004 Abstract. In the vehicle routing problem with stochastic demands a vehicle has to serve a set of customers whose exact demand is known only upon arrival at the customer’s location. The objective is to find a permutation of the customers (an a priori tour) that minimizes the expected distance...

In search auctions, when the total budget for an advertising campaign during a certain promotion period is determined, advertisers have to distribute their budgets over a series of sequential temporal slots (e.g., daily budgets). However, due to the uncertainties existed in search markets, advertisers can only obtain the value range of budget demand for each temporal slot based on promotion log...

Problem statement: The shipment of goods from manufacturer to the consumer is a focal point of distribution logistics. In reality, the demand of consumers is not known a priori. This kind of distribution is dealt by Stochastic Vehicle Routing Problem (SVRP) which is a NP-hard problem. In this proposed work, VRP with stochastic demand is considered. A probability distribution is considered as a ...

In the vehicle routing problem with stochastic demands a vehicle has to serve a set of customers whose exact demand is known only upon arrival at the customer’s location. The objective is to find a permutation of the customers (an a priori tour) that minimizes the expected distance traveled by the vehicle. Since the objective function is computationally demanding, effective approximations of it...

We consider the vehicle routing problem with stochastic demands (VRPSD) under reoptimization. We develop and analyze a finite-horizon Markov decision process (MDP) formulation for the single vehicle case, and establish a partial characterization of the optimal policy. We also propose a heuristic solution methodology for our MDP, named partial reoptimization, based on the idea of restricting att...

One of the growing production strategies is hybrid Make-To-Stock (MTS)/ Make-To-Order (MTO), since this strategy benefit from the both well-know strategies MTS and MTO. Among handful research papers in the field of hybrid production context, no researches have been devoted to aggregate production planning level. Therefore, this paper addresses aggregate production planning from a tactical point...

Problems with Nonstationary Demands Huanan Zhang∗, Cong Shi∗, Chao Qin†, Cheng Hua‡ ∗ Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI 48109 {zhanghn, shicong}@umich.edu † Industrial Engineering and Management Sciences, Northwestern University, Evanston, IL 60208, [email protected] ‡ Yale School of Management, Yale University, New Haven, CT 06511, cheng....

In this paper, to cope with the stochastic dynamic (or multi-period) problem, two new quadratic assignment-based mathematical models corresponding to the dynamic and static approaches are developed. The product demands are presumed to be dependent uncertain variables with normal distribution having known expectation, variance, and covariance that change from one period to the next one, randomly...