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Author (up) Rojas, F.; Leiva, V. pdf  doi
  Title Inventory management in food companies with statistically dependent demand Type
  Year 2016 Publication Academia-Revista Latinoamericana De Administracion Abbreviated Journal Acad.-Rev. Latinoam. Adm.  
  Volume 29 Issue 4 Pages 450-485  
  Keywords Contribution margins; Multivariate distribution; Optimization methods; Probabilistic inventory models; Statistical dependence  
  Abstract Purpose – The objective of this paper is to propose a methodology based on random demand inventory models and dependence structures for a set of raw materials, referred to as “components”, used by food services that produce food rations referred to as “menus”. Design/methodology/approach – The contribution margins of food services that produce menus are optimised using random dependent demand inventory models. The statistical dependence between the demand for components and/or menus is incorporated into the model through the multivariate Gaussian (or normal) distribution. The contribution margins are optimised by using probabilistic inventory models for each component and stochastic programming with a differential evolution algorithm. Findings – When compared to the non-optimised system previously used by the company, the (average) expected contribution margin increases by 18.32 per cent when using a continuous review inventory model for groceries and uniperiodic models for perishable components (optimised system). Research limitations/implications – The multivariate modeling can be improved by using (a) other non-Gaussian (marginal) univariate probability distributions, by means of the copula method that considers more complex statistical dependence structures; (b) time-dependence, through autoregressive time-series structures and moving average; (c) random modelling of lead-time; and (d) demands for components with values equal to zero using zero-inflated or adjusted probability distribution. Practical implications – Professional management of the supply chain allows the users to register data concerning component identification, demand, and stock levels to subsequently be used with the proposed methodology, which must be implemented computationally. Originality/value – The proposed multivariate methodology allows it to describe demand dependence structures through inventory models applicable to components used to produce menus in food services.  
  Address [Rojas, Fernando] Univ Valparaiso, Sch Nutr & Dietet, Valparaiso, Chile, Email:;  
  Corporate Author Thesis  
  Publisher Emerald Group Publishing Ltd Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1012-8255 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000392137900006 Approved  
  Call Number UAI @ eduardo.moreno @ Serial 689  
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