Designing a road network for hazardous materials shipments

Cataloged from PDF version of article.We consider the problem of designating hazardous materials routes in and through a major population center. Initially, we restrict our attention to a minimally connected network (a tree) where we can predict accurately the flows on the network. We formulate the tree design problem as an integer programming problem with an objective of minimizing the total transport risk. Such design problems of moderate size can be solved using commercial solvers. We then develop a simple construction heuristic to expand the solution of the tree design problem by adding road segments. Such additions provide carriers with routing choices, which usually increase risks but reduce costs. The heuristic adds paths incrementally, which allows local authorities to trade off risk and cost. We use the road network of the city of Ravenna, Italy, to demonstrate the solution of our integer programming model and our path-addition heuristic. © 2005 Elsevier Ltd. All rights reserved

An integrated approach to inventory and flexible capacity management subject to fixed costs and non-stationary stochastic demand

In a manufacturing system with flexible capacity, inventory management can be coupled with capacity management in order to handle fluctuations in demand more effectively. Typical examples include the effective use of temporary workforce and overtime production. In this paper, we discuss an integrated model for inventory and flexible capacity management under non-stationary stochastic demand with the possibility of positive fixed costs, both for initiating production and for using contingent capacity. We analyze the characteristics of the optimal policies for the integrated problem. We also evaluate the value of utilizing flexible capacity under different settings, which enable us to develop managerial insights. © 2008 The Author(s)

Tales of a so(u)rcerer : optimal sourcing decisions under alternative capacitated suppliers and general cost structures

Most companies must procure items necessary for their businesses from out- side sources, where there are typically a number of competing suppliers with varying cost structures, price schemes, and capacities. This situation poses some interesting research questions from the outlook of different parties in the supply chain. We consider this problem from the perspective of (i) the party that needs to outsource, (ii) the party that is willing to serve as the source, and (iii) the party that has in-house capability to spare. We allow for stochastic demand, capacitated facilities (in-house and suppliers'), and general structures for all relevant cost components. Some simpler versions of this problem are shown to be NP-hard in the literature. We make use of a novel dynamic programming model with pseudo-polynomial complexity to address all three perspectives by solving the corresponding problems to optimality. Our modeling approach also lets us analyze different aspects of the problem environment such as pricing schemes and channel coordination issues. We derive several managerial insights, some of which are counter to collective intuition

Time-frequency analysis of signals using support adaptive Hermite-Gaussian expansions

Cataloged from PDF version of article.Since Hermite–Gaussian (HG) functions provide an orthonormal basis with the most compact time– frequency supports (TFSs), they are ideally suited for time–frequency component analysis of finite energy signals. For a signal component whose TFS tightly fits into a circular region around the origin, HG function expansion provides optimal representation by using the fewest number of basis functions. However, for signal components whose TFS has a non-circular shape away from the origin, straight forward expansions require excessively large number of HGs resulting to noise fitting. Furthermore, for closely spaced signal components with non-circular TFSs, direct application of HG expansion cannot provide reliable estimates to the individual signal components. To alleviate these problems, by using expectation maximization (EM) iterations, we propose a fully automated pre-processing technique which identifies and transforms TFSs of individual signal components to circular regions centered around the origin so that reliable signal estimates for the signal components can be obtained. The HG expansion order for each signal component is determined by using a robust estimation technique. Then, the estimated components are post-processed to transform their TFSs back to their original positions. The proposed technique can be used to analyze signals with overlapping components as long as the overlapped supports of the components have an area smaller than the effective support of a Gaussian atom which has the smallest time-bandwidth product. It is shown that if the area of the overlap region is larger than this threshold, the components cannot be uniquely identified. Obtained results on the synthetic and real signals demonstrate the effectiveness for the proposed time–frequency analysis technique under severe noise cases. © 2012 Elsevier Inc. All rights reserved

Integrated capacity and inventory management with capacity acquisition lead times

Cataloged from PDF version of article.We model a make-to-stock production system that utilizes permanent and contingent capacity to meet non-stationary stochastic demand, where a constant lead time is associated with the acquisition of contingent capacity. We determine the structure of the optimal solution concerning both the operational decisions of integrated inventory and flexible capacity management, and the tactical decision of determining the optimal permanent capacity level. Furthermore, we show that the inventory (either before or after production), the pipeline contingent capacity, the contingent capacity to be ordered, and the permanent capacity are economic substitutes. We also show that the stochastic demand variable and the optimal contingent capacity acquisition decisions are economic complements. Finally, we perform numerical experiments to evaluate the value of utilizing contingent capacity and to study the effects of capacity acquisition lead time, providing useful managerial insights. (C) 2008 Elsevier B.V. All rights reserved

Inventory control with partial batch ordering

In an in¯nite-horizon, periodic-review, single-item production/inventory system with random demand and back-ordering, we study the feature of batch ordering, where a separate ¯xed cost is associated for each batch ordered. Contrary to majority of the literature on this topic, we do not restrict the order quantities to be integer multiples of the batch size and instead allow the possibility of partial batches, in which case the ¯xed cost for ordering the batch is still fully charged. We build a model that particu- larly takes the batch ordering cost structure into account. We introduce an alternative cost accounting scheme to analyze the problem, and we discuss several properties of the optimal solution. Based on the analysis of a single-period problem and a multi-period lower-bound problem, we study two heuristic policies for the original partial batch or- dering problem, both of which perform very well computationally for a wide range of problem parameters. Finally, we compare the performance of the optimal policy to the performance of the best full-batch-size ordering policy to quantify the value of partial ordering °exibility

Integrated capacity and inventory management with capacity acquisition lead times

No abstrac