Goal programming for supply chain optimization with insufficient capacity

Mohan Chiriki; Yooneun Lee; Vittaldas V. Prabhu

doi:10.1007/978-3-319-66926-7_9

Goal programming for supply chain optimization with insufficient capacity

Mohan Chiriki, Yooneun Lee, Vittaldas V. Prabhu

Marcus Department of Industrial and Manufacturing Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This article presents three different approaches to modeling and solving the classic transportation-location problem including the traditional cost-minimization mixed integer linear program. It is shown that modeling these problems as a profit maximization mixed integer program instead allows for the relaxation of a set of constraints. An alternative multi-objective optimization model using goal programming is also presented. A representative model of the fluid milk supply chain in the U.S. is developed to demonstrate the scenarios and solutions achieved by the three different models to conclude that the multi-objective model is a robust approach to solve these optimization problems even when there is only a single explicit objective.

Original language	English (US)
Title of host publication	Advances in Production Management Systems
Subtitle of host publication	The Path to Intelligent, Collaborative and Sustainable Manufacturing - IFIP WG 5.7 International Conference, APMS 2017, Proceedings
Editors	Dimitris Kiritsis, Klaus-Dieter Thoben, Hermann Lodding, Ralph Riedel, Gregor von Cieminski
Publisher	Springer New York LLC
Pages	73-80
Number of pages	8
ISBN (Print)	9783319669250
DOIs	https://doi.org/10.1007/978-3-319-66926-7_9
State	Published - 2017
Event	IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2017 - Hamburg, Germany Duration: Sep 3 2017 → Sep 7 2017

Publication series

Name	IFIP Advances in Information and Communication Technology
Volume	514
ISSN (Print)	1868-4238

Other

Other	IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2017
Country/Territory	Germany
City	Hamburg
Period	9/3/17 → 9/7/17

All Science Journal Classification (ASJC) codes

Information Systems
Computer Networks and Communications
Information Systems and Management

Access to Document

10.1007/978-3-319-66926-7_9

Cite this

Chiriki, M., Lee, Y., & Prabhu, V. V. (2017). Goal programming for supply chain optimization with insufficient capacity. In D. Kiritsis, K.-D. Thoben, H. Lodding, R. Riedel, & G. von Cieminski (Eds.), Advances in Production Management Systems: The Path to Intelligent, Collaborative and Sustainable Manufacturing - IFIP WG 5.7 International Conference, APMS 2017, Proceedings (pp. 73-80). (IFIP Advances in Information and Communication Technology; Vol. 514). Springer New York LLC. https://doi.org/10.1007/978-3-319-66926-7_9

Chiriki, Mohan ; Lee, Yooneun ; Prabhu, Vittaldas V. / Goal programming for supply chain optimization with insufficient capacity. Advances in Production Management Systems: The Path to Intelligent, Collaborative and Sustainable Manufacturing - IFIP WG 5.7 International Conference, APMS 2017, Proceedings. editor / Dimitris Kiritsis ; Klaus-Dieter Thoben ; Hermann Lodding ; Ralph Riedel ; Gregor von Cieminski. Springer New York LLC, 2017. pp. 73-80 (IFIP Advances in Information and Communication Technology).

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abstract = "This article presents three different approaches to modeling and solving the classic transportation-location problem including the traditional cost-minimization mixed integer linear program. It is shown that modeling these problems as a profit maximization mixed integer program instead allows for the relaxation of a set of constraints. An alternative multi-objective optimization model using goal programming is also presented. A representative model of the fluid milk supply chain in the U.S. is developed to demonstrate the scenarios and solutions achieved by the three different models to conclude that the multi-objective model is a robust approach to solve these optimization problems even when there is only a single explicit objective.",

author = "Mohan Chiriki and Yooneun Lee and Prabhu, {Vittaldas V.}",

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doi = "10.1007/978-3-319-66926-7_9",

language = "English (US)",

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series = "IFIP Advances in Information and Communication Technology",

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Chiriki, M, Lee, Y & Prabhu, VV 2017, Goal programming for supply chain optimization with insufficient capacity. in D Kiritsis, K-D Thoben, H Lodding, R Riedel & G von Cieminski (eds), Advances in Production Management Systems: The Path to Intelligent, Collaborative and Sustainable Manufacturing - IFIP WG 5.7 International Conference, APMS 2017, Proceedings. IFIP Advances in Information and Communication Technology, vol. 514, Springer New York LLC, pp. 73-80, IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2017, Hamburg, Germany, 9/3/17. https://doi.org/10.1007/978-3-319-66926-7_9

Goal programming for supply chain optimization with insufficient capacity. / Chiriki, Mohan; Lee, Yooneun; Prabhu, Vittaldas V.
Advances in Production Management Systems: The Path to Intelligent, Collaborative and Sustainable Manufacturing - IFIP WG 5.7 International Conference, APMS 2017, Proceedings. ed. / Dimitris Kiritsis; Klaus-Dieter Thoben; Hermann Lodding; Ralph Riedel; Gregor von Cieminski. Springer New York LLC, 2017. p. 73-80 (IFIP Advances in Information and Communication Technology; Vol. 514).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - This article presents three different approaches to modeling and solving the classic transportation-location problem including the traditional cost-minimization mixed integer linear program. It is shown that modeling these problems as a profit maximization mixed integer program instead allows for the relaxation of a set of constraints. An alternative multi-objective optimization model using goal programming is also presented. A representative model of the fluid milk supply chain in the U.S. is developed to demonstrate the scenarios and solutions achieved by the three different models to conclude that the multi-objective model is a robust approach to solve these optimization problems even when there is only a single explicit objective.

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Chiriki M, Lee Y, Prabhu VV. Goal programming for supply chain optimization with insufficient capacity. In Kiritsis D, Thoben KD, Lodding H, Riedel R, von Cieminski G, editors, Advances in Production Management Systems: The Path to Intelligent, Collaborative and Sustainable Manufacturing - IFIP WG 5.7 International Conference, APMS 2017, Proceedings. Springer New York LLC. 2017. p. 73-80. (IFIP Advances in Information and Communication Technology). doi: 10.1007/978-3-319-66926-7_9

Goal programming for supply chain optimization with insufficient capacity

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