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Improvement of inventory control under parametric uncertainty and constraints

  • Nicholas Nechval*
  • , Konstantin Nechval
  • , Maris Purgailis
  • , Uldis Rozevskis
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paperResearchpeer-review

8 Citations (Scopus)

Abstract

The aim of the present paper is to show how the statistical inference equivalence principle (SIEP), the idea of which belongs to the authors, may be employed in the particular case of finding the effective statistical decisions for the multi-product inventory problems with constraints. To our knowledge, no analytical or efficient numerical method for finding the optimal policies under parametric uncertainty for the multi-product inventory problems with constraints has been reported in the literature. Using the (equivalent) predictive distributions, this paper represents an extension of analytical results obtained for unconstrained optimization under parametric uncertainty to the case of constrained optimization. A numerical example is given.

Original languageEnglish
Title of host publicationAdaptive and Natural Computing Algorithms - 10th International Conference, ICANNGA 2011, Proceedings
Pages136-146
Number of pages11
EditionPART 2
DOIs
Publication statusPublished - 2011
Event10th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2011 - Ljubljana, Slovenia
Duration: 14 Apr 201116 Apr 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume6594 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2011
Country/TerritorySlovenia
CityLjubljana
Period14/04/1116/04/11

Keywords

  • constraints
  • equivalent predictive inferences
  • Inventory problem
  • parametric uncertainty
  • pivotal quantity

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