Some comments on preference order dynamic programming models

AbstractA simple deterministic dynamic programming model is used as a general framework for the analysis of stochastic versions of three classical optimization problems: knapsack, traveling salesperson, and assembly line balancing problems. It is shown that this model can provide an alternative to the preference order models proposed for these problems. Counterexample to the optimality of the preference order models are presented

Optimizing the strategic patient mix

In this paper we address the decision of choosing a patient mix for a hospital that leads to the most beneficial treatment case mix. We illustrate how capacity, case mix and patient mix decisions are interrelated and how understanding this complex relationship is crucial for achieving the maximum benefit from the fee-for-service financing system. Although studies to determine the case mix that is of maximum benefit exist in the literature, the hospital actions necessary to realize this case mix has seen less attention. We model the hospital as an $M/G/\infty$ queueing system to evaluate the impact of accepting certain patient types. Using this queueing model to generate the parameters, an optimization problem is formulated. We propose two methods for solving the optimization problem. The first is exact but requires an integer linear programming solver whereas the second is an approximation relying only on dynamic programming. The model is applied in the department of surgery at a Dutch hospital. The model determines which patient types result in the desired growth in the preferred surgical treatment areas. The case study highlights the impact of striving for a certain case mix without providing a sufficiently balanced supply of resources. In the case study we show how the desired case mix can be better archieved by investing in certain capacity

Investment Programming Model for Rural Community Water Systems

The Oklahoma Agricultural Experiment Station periodically issues revisions to its publications. The most current edition is made available. For access to an earlier edition, if available for this title, please contact the Oklahoma State University Library Archives by email at [email protected] or by phone at 405-744-6311

Scale in Production Systems; Based on an IIASA Workshop, June 26-29, 1979

When a new enterprise is planned or the scope of an organization is changed, a decision on scale has to be made. At a certain stage in the development of a technology, the economies of scale that have been established are overtaken by factors that had hitherto been considered secondary. Mistakes of scale have been made, from hospitals to electricity-generating boards. The mistakes of being too large are the most eye-catching, but the mistakes of being too small are probably just as frequent, and just as important. Twelve chapters of this book are based on reports of a workshop on scale and productive efficiency held at IIASA. The other eight chapters describe work done at the Institute; they also include discussion of the key issues relevant to scale that arose at the workshop, thus broadening the survey of this topic. This book treats problems of scale at various levels: at the unit (the equipment) and plant levels; and at industrial and national levels, and includes practical case descriptions that will be of value to managers and decision makers, as well as material of value to research workers

Modelling capacity expansion planning for an optical disc manufacturing system

Ankara : Department of Industrial Engineering and the Institute of Engineering and Science of Bilkent University, 1997.Thesis (Master's) -- Bilkent University, 1997.Includes bibliographical references leaves 84-86.The capacity expansion problems involve determination of the optimum timing and sizing of the capacity for the facilities that have to meet a given demand function. There are various versions of the problem in the literature. In this thesis, a mathematical model for the expansion of a facility producing a single commodity is formulated. This formulation is then used for solving the capacity expansion problem for an optical disc manufacturing system, producing two types of products by the use of two different capacity types. The effects of the technological improvements and economies of scale are considered. The dynamic programming approach is used and a forward recursion algorithm is devised and coded on a personal computer.Gündüz, ErdemM.S

Accountants\u27 index. Twenty-second supplement, January-December 1973

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Economic Capacity Expansion Planning: an Application to the Telephone Industry

Industrial Engineering and Managemen