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dc.contributor.author
Masini, Guillermo Luis
dc.contributor.author
Blanco, Anibal Manuel
dc.contributor.author
Petracci,Noemí Cristina
dc.contributor.author
Bandoni, Jose Alberto
dc.contributor.other
Pistikopoulos, Efstratios N.
dc.contributor.other
Georgiadis, Michael C.
dc.contributor.other
Dua, Vivek
dc.contributor.other
Papageorgiou, Lazaros
dc.date.available
2021-05-04T19:04:00Z
dc.date.issued
2007
dc.identifier.citation
Masini, Guillermo Luis; Blanco, Anibal Manuel; Petracci,Noemí Cristina; Bandoni, Jose Alberto; Supply chain optimization in the fruit industry; Wiley-VCH; 4; 2007; 121-154
dc.identifier.isbn
978-3-527-31906-0
dc.identifier.uri
http://hdl.handle.net/11336/131319
dc.description.abstract
The pip fruit industry is a major economic activity in many countries. The supply chain of this industry is a complex system, which involve interactions among many productive, processing and storage nodes. Fresh fruit harvested in farms is processed in packaging plants to produce packed fruit and in juice and cider plants to produce concentrated juice and cider. Storage facilities within the system permit to keep the quality of the excess of fruit until it can be processed. Large volumes of fruit have to be transported between the different nodes of the chain during the whole year. Opposite to many supply chains which are “demand driven” systems, the fruit industry supply chains is typically a “production driven system” since the flows of goods are “pushed” by fresh fruit availability rather than “pulled” by client order placement. The pip fruit business can be thought as having a “negotiation instance” and an “operation instance”. In the “negotiation instance”, before the beginning of business cycle, the company’s managers pre-establish delivery commitments of products (packed fruit, concentrated juice and cider) with different clients based on estimations of future fruit availability from farms. In the “operation instance” of the system, the pre-established commitments are sought to be satisfied as close as possible with the actual fruit income profile. Due to the large amount of involved decisions on what, how much, and when to purchase, store and allocate fruit, planning models constitute a valuable tool in the decision making process. In this contribution a detailed and complete tactical planning model to aid in the negotiation instance of a typical large company that operates several nodes of the fruit industry supply chain is presented. The proposed Linear Programming model considers the many interactions of the real network and the typical operative practices of the business. The model is devised to estimate the “production profiles” of the different final products of the system (packed fruit, juice and cider) as well as the “resources profiles” (fresh fruit, storage capacity and transportation logistics) required to feasibly operate in order to maximize the total net profit of the company. Results are presented for a typical large company operating in the supply chain of the pip fruit industry of Argentina. A very realistic scenario for a negotiation instance of the company is developed and discussed. A complete set of data is provided to reproduce the entire case study formulated as a Linear Programming model with about 34,000 equations and 143,000 variables. Optimum profiles for the maximum provision of the different products at a pre-determined delivery schedule, along with an estimation of raw material and other resources requirements in order to reach that level of production, are determined by the model. These results constitute valuable information for company managers to negotiate contracts with clients and suppliers in the coming business cycle.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Wiley-VCH
dc.rights
info:eu-repo/semantics/restrictedAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.source
https://onlinelibrary.wiley.com/doi/book/10.1002/9783527631278
dc.subject
SUPPLY CHAIN
dc.subject
FRUIT INDUSTRY
dc.subject
TACTICAL PLANNING
dc.subject.classification
Ingeniería de Procesos Químicos
dc.subject.classification
Ingeniería Química
dc.subject.classification
INGENIERÍAS Y TECNOLOGÍAS
dc.title
Supply chain optimization in the fruit industry
dc.type
info:eu-repo/semantics/publishedVersion
dc.type
info:eu-repo/semantics/bookPart
dc.type
info:ar-repo/semantics/parte de libro
dc.date.updated
2021-03-26T13:02:08Z
dc.journal.volume
4
dc.journal.pagination
121-154
dc.journal.pais
Alemania
dc.journal.ciudad
Weinheim
dc.description.fil
Fil: Masini, Guillermo Luis. Universidad Nacional del Comahue; Argentina
dc.description.fil
Fil: Blanco, Anibal Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
dc.description.fil
Fil: Petracci,Noemí Cristina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
dc.description.fil
Fil: Bandoni, Jose Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://onlinelibrary.wiley.com/doi/abs/10.1002/9783527631278.ch5
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1002/9783527631278.ch5
dc.conicet.paginas
350
dc.source.titulo
Supply chain optimization
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