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  • 1
    Electronic Resource
    Electronic Resource
    Service Management (2004)
    J. Mack Robinson College of Business, Georgia State University , Atlanta , GA 30303 , 404-651-4073, fax: 404-651-2804 : Decision Sciences
    Decision sciences 35 (2004), S. 0 
    Details
    ISSN: 1540-5915
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Economics
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.0011-7315.2004.35031.x
    Library Location Call Number Volume/Issue/Year Availability
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    Paper (German National Licenses)
    Fulltext
  • 2
    Electronic Resource
    Electronic Resource
    A Model for Resource Constrained Production and Inventory Management (1994)
    Oxford, UK : Blackwell Publishing Ltd
    Decision sciences 25 (1994), S. 0 
    Details
    ISSN: 1540-5915
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Economics
    Notes: We present a general model for multi-item production and inventory management problems that include a resource restriction. The decision variables in the model can take on a variety of interpretations, but will typically represent cycle times, production batch sizes, number of production runs, or order quantities for each item. We consider environments where item demand rates are approximately constant and performing an activity such as producing a batch of a product or placing an order results in the consumption of a scarceresource that is shared among the items. Some examples of shared resources include limited machine capacity, a restriction on the amount of money that can be tied up in stock, orlimited storage capacity. We focus on the case where the decision variables must be integer valued or selected from a discrete set of choices, such as when an integer number of production runs is desired for each item, or in order quantity problems where the items come in pack sizes containing more than one unit and, therefore, the order quantities must be an integer multiple of the pack sizes. We develop a heuristic and a branch and bound algorithm for solving the problem. The branch and bound algorithm includes reoptimization procedures and the heuristic to improve its performance. Computational testing indicates that the algorithms are effective for solving the general model.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1540-5915.1994.tb00821.x
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    Paper (German National Licenses)
    Fulltext
  • 3
    Electronic Resource
    Electronic Resource
    A Model for Planning Resource Requirements in Health Care Organizations (1998)
    Oxford, UK : Blackwell Publishing Ltd
    Decision sciences 29 (1998), S. 0 
    Details
    ISSN: 1540-5915
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Economics
    Notes: In this paper we present a general model and solution methodology for planning resource requirements (i.e., capacity) in health care organizations. To illustrate the general model, we consider two specific applications: a blood bank and a health maintenance organization (HMO). The blood bank capacity planning problem involves determining the number of donor beds required and determining the size of the nursing and support staff necessary. Capacity must be sufficient to handle the expected number of blood donors without causing excessive donor waiting times. Similar staff, equipment, and service level decisions arise in the HMO capacity planning problem. To determine resource requirements, we develop an optimization/queueing network model that minimizes capacity costs while controlling customer service by enforcing a set of performance constraints, such as setting an upper limit on the expected time a patient spends in the system. The queueing network model allows us to capture the stochastic behavior of health care systems and to measure customer service levels within the optimization framework.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1540-5915.1998.tb01351.x
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    Paper (German National Licenses)
    Fulltext
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