We propose a dynamic program to find the shortest path in a network having exponential, gamma and normal probability distributions as arc lengths. Two operators of sum and comparison need to be adapted for the proposed dynamic program. Convolution approach is used to sum probability distributions being employed in the dynamic program. Article Download View … Read more
An integer programming model for the truck dock assignment problem with operational time constraint within cross docks has been proposed in (Miao, Z.,Lim, A.,Ma, H., 2009. Truck dock assignment problem with operational time constraint within crossdocks. European Journal of Operational Research 192 (1), 105–115). We address the following issues in this formulation: 1) from among … Read more
The portfolio optimization model has limited impact in practice due to estimation issues when applied with real data. To address this, we adapt two machine learning methods, regularization and cross-validation, for portfolio optimization. First, we introduce performance-based regularization (PBR), where the idea is to constrain the sample variances of the estimated portfolio risk and return, … Read more
The multi-hour bandwidth packing problem arises in telecommunication networks that span several time horizon. The problem seeks to select and route a set of messages from a given list of messages with prespecified requirement on demand for bandwidth under time varying traffic conditions on an undirected communication network such that the total profit is maximized. … Read more
We consider totally unimodular multistage stochastic programs, that is, multistage stochastic programs whose extensive-form constraint matrices are totally unimodular. We establish several sufficient conditions and identify examples that have arisen in the literature. Citation Ruichen (Richard) Sun, Oleg V. Shylo, Andrew J. Schaefer, Totally unimodular multistage stochastic programs, Operations Research Letters, Volume 43, Issue 1, … Read more
In this paper, we present a new scheme of a sampling method to solve chance constrained programs. First of all, a modified sample average approximation, namely Partial Sample Average Approximation (PSAA) is presented. The main advantage of our approach is that the PSAA problem has only continuous variables whilst the standard sample average approximation (SAA) … Read more