2010
DOI: 10.1504/ijlsm.2010.034425
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The campaign and lot size scheduling problem: a modification of the Economic Lot Scheduling Problem for the pharmaceutical industry

Abstract: This paper presents a model to minimise inventory and setup costs in a multi-product operation where production is organised in campaigns. A campaign is defined as a number of successive, equally sized lots of a same product. Major and minor sets are considered. The decision variables are the per product time between campaigns and number of lots per campaign. Two cases are presented: when the time between campaigns is common to all products, and when it is a multiple of a common period. Examples are presented … Show more

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Cited by 4 publications
(1 citation statement)
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“…Also, Marques et al (2020) notices that current approaches to pharmaceutical supply chain design and management are still highly fragmented, and identifies the seamless integration and coordination across the SC network as one major challenge. Moreover, those approaches seem to be mostly driven by classical optimization models, hardly addressing the real end-to-end supply chain planning problem (Laínez et al 2012), and most of the literature still relies on operational planning and scheduling approaches based on optimization or hybrid simulation-optimization methods (Ruiz-Torres et al 2010;Moniz et al 2014;Marques et al 2017).…”
Section: Pharmaceutical Supply Chain Design and Planningmentioning
confidence: 99%
“…Also, Marques et al (2020) notices that current approaches to pharmaceutical supply chain design and management are still highly fragmented, and identifies the seamless integration and coordination across the SC network as one major challenge. Moreover, those approaches seem to be mostly driven by classical optimization models, hardly addressing the real end-to-end supply chain planning problem (Laínez et al 2012), and most of the literature still relies on operational planning and scheduling approaches based on optimization or hybrid simulation-optimization methods (Ruiz-Torres et al 2010;Moniz et al 2014;Marques et al 2017).…”
Section: Pharmaceutical Supply Chain Design and Planningmentioning
confidence: 99%