Optimal production scheduling for the dairy industry

Doganis, P; Sarimveis, H

dc.contributor.author	Doganis, P	en
dc.contributor.author	Sarimveis, H	en
dc.date.accessioned	2014-03-01T01:28:58Z
dc.date.available	2014-03-01T01:28:58Z
dc.date.issued	2008	en
dc.identifier.issn	0254-5330	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/19049
dc.subject	Mixed-integer linear programming	en
dc.subject	Optimization	en
dc.subject	Packaging	en
dc.subject	Parallel machines	en
dc.subject	Scheduling	en
dc.subject	Yogurt	en
dc.subject.classification	Operations Research & Management Science	en
dc.subject.other	PARALLEL PRODUCTION LINES	en
dc.subject.other	RESOURCE CONSTRAINTS	en
dc.subject.other	BATCH PLANTS	en
dc.subject.other	FORMULATION	en
dc.subject.other	MULTIPRODUCT	en
dc.subject.other	SYSTEMS	en
dc.title	Optimal production scheduling for the dairy industry	en
heal.type	journalArticle	en
heal.identifier.primary	10.1007/s10479-007-0285-y	en
heal.identifier.secondary	http://dx.doi.org/10.1007/s10479-007-0285-y	en
heal.language	English	en
heal.publicationDate	2008	en
heal.abstract	The increasing variety of products offered by the food industry has helped the industry to respond to market trends, but at the same time has resulted in a more complex production process, which requires flexibility and an efficient coordination of existing resources. Especially in industrial yogurt production, there is a wide variety of products that differ in features like fat content, the whey used to produce the mixture, the flavor, the size of the container or the language on the label. The great diversification and the special features that characterize yogurt production lines (satisfaction of multiple due dates, variable processing times, sequence-dependent setup times and costs and monitoring of inventory levels), render generic scheduling methodologies impractical for real-world applications. In this work we present a customized Mixed Integer Linear Programming (MILP) model for optimizing yogurt packaging lines that consist of multiple parallel machines. The model is characterized by parsimony in the utilization of binary variables and necessitates the use of only a small pre-determined number of time periods. The efficiency of the proposed model is illustrated through its application to the yogurt production plant of a leading dairy product manufacturing company in Greece. © 2007 Springer Science+Business Media, LLC.	en
heal.publisher	SPRINGER	en
heal.journalName	Annals of Operations Research	en
dc.identifier.doi	10.1007/s10479-007-0285-y	en
dc.identifier.isi	ISI:000252766600020	en
dc.identifier.volume	159	en
dc.identifier.issue	1	en
dc.identifier.spage	315	en
dc.identifier.epage	331	en