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According to the IBM Tech Trends Report in 2011, analytics has been identified as one of the four major technology trends in the 2010s. However, as predicted by McKinsey Global [...]

We present two decomposition algorithms for single product deep-sea maritime inventory routing problems (MIRPs) that possess a core substructure common in many real-world applications. The problem involves routing vessels, each [...]

Because semiconductor manufacturing is a complex and dynamic process, production scheduling in this industry typically relies on simple decision policies that use local rather than global information. Such myopic policies may lead to increased congestion in the material handling system and negatively impact throughput. In this paper, we propose a fluid-model lot dispatching policy that iteratively optimises lot selection based on current WIP distribution of the entire system. Furthermore, we propose to split the decision policies into two phases in order to include travel times information into the dispatching and targeting decisions. We provide simulation results for a prototype facility that show that our proposed policies outperform commonly used dispatching rules in throughput, machine utilisation and machine target accuracy. [ABSTRACT FROM AUTHOR]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ejor.2005.05.011 Byline: Ek-Peng Chew (a), Huei-Chuen Huang (a), Ellis L. Johnson (b), George L. Nemhauser (b), Joel S. Sokol (b), Chun-How Leong (c) Keywords: Dynamic programming; Multi-period capacity planning problem Abstract: This paper proposes a stochastic dynamic programming model for a short-term capacity planning model for air cargo space. Long-term cargo space is usually acquired by freight forwarders or shippers many months ahead on a contract basis, and usually the forecasted demand is unreliable. A re-planning of cargo space is needed when the date draws nearer to the flight departure time. Hence, for a given amount of long-term contract space, the decision for each stage is the quantity of additional space required for the next stage and the decision planning model evaluates the optimal cost policy based on the economic trade-off between the cost of backlogged shipment and the cost of acquiring additional cargo space. Under certain conditions, we show that the return function is convex with respect to the additional space acquired for a given state and the optimal expected cost for the remaining stages is an increasing convex function with respect to the state variables. These two properties can be carried backward recursively and therefore the optimal cost policy can be determined efficiently. Author Affiliation: (a) Department of Industrial and Systems Engineering, National University of Singapore, 1 Engineering Drive 2, Singapore 117576, Singapore (b) School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, United States (c) The Logistics Institute -- Asia Pacific, Singapore Article History: Received 4 June 2004; Accepted 18 May 2005

In this article, we address a version of the capacitated vehicle routing problem where there is a constraint on the total time that can be spent on computing delivery routes and loading the vehicles. This problem, which we call the vehicle loading and routing problem (VLRP), can arise, for example, in the delivery of small, quick‐turnaround orders from a warehouse. We propose a computation‐implementation parallelization (CIP) approach to solving large VLRP instances, and present computational results showing that CIP improves upon the conventional compute‐first‐implement‐later method. Our approach allows us to find lower‐cost solutions in the same amount of time, or alternatively to find equally good solutions that allow improvements in order cutoff time or truck dispatching time to increase customer satisfaction. [ABSTRACT FROM AUTHOR]

When I'm asked what the most important O.R. skill is for the majority of our students, I consistently answer, 'modeling.' Most of our students will not go on to develop […]

'The Undergraduate Operations Research Prize Competition is held each year to honor a student or group of students who conducted a significant applied project in operations research or management science, [...]

OK, we're not going to lie. This isn't your traditional 'Issues in Education' article. As you may or may not have noticed, every June this column turns into an advertisement [...]