Substantiating The Optimal Distribution Policy Using Markov Decision Processes
AbstractThe paper represents a means of substantiating the optimal politicy of transport and distribution of goods groupage using Markov’s decisional processes, respectively through R. Howard’s method of strategies’ space. This kind of method is based on an iterative optimization algorithm, whose structure permits that, with the successive covering of each method, to limit the number of ulterior repetitions. In this way, the optimal politicy that result, constituted from a number of decisions, finite or not, aims at optimizing the following decisions in a close connection with the first decision’s consequences, whatever that would be. Concretely, a logistic centre’s managers have the responsibility of identifying the optimal transport policy of the unit loads prepared for being shipped in three ways: palletized, containerized and packaged, according to the ways of transport which will be used: causeway, railway and airway, and the costs associated to each shipping means.
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Bibliographic InfoArticle provided by Research Centre in Public Administration and Public Services, Bucharest, Romania in its journal Management Research and Practice.
Volume (Year): 2 (2010)
Issue (Month): 4 (December)
distribution centre; optimal policy; decision; average cost; unit loads.;
Find related papers by JEL classification:
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
- L81 - Industrial Organization - - Industry Studies: Services - - - Retail and Wholesale Trade; e-Commerce
- L91 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Transportation: General
- M10 - Business Administration and Business Economics; Marketing; Accounting - - Business Administration - - - General
- M11 - Business Administration and Business Economics; Marketing; Accounting - - Business Administration - - - Production Management
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