A mixed integer programming model for integrating MRP and job shop scheduling

K. J. Chen; Ping Ji

A mixed integer programming model for integrating MRP and job shop scheduling

K. J. Chen, Ping Ji

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

2 Citations (Scopus)

Abstract

This paper presents a Mixed Integer Programming (MIP) model which succeeds in a systematic integration of the production planning and job shop scheduling problems. The proposed model explicitly considers capacity constraints, operation sequences, lead times and due dates in a dynamic demand environment. The objective of the model is to seek the minimum both production flow time and penalty costs including tardiness and earliness costs. The output of the model is operation schedules with order starting time and finish time. The integrated model is verified with a commercial software package and tested with a small example. The model will be further improved and meta-heuristics will be used to solve the model more efficiently.

Original language	English
Title of host publication	Advances in e-Engineering and Digital Enterprise Technology - I. Proceedings of the Fourth International Conference on e-Engineering and Digital Enterprise Technology
Pages	145-150
Number of pages	6
Publication status	Published - 1 Dec 2004
Event	Advances in e-Engineering and Digital Enterprise Technology - I. Proceedings of the Fourth International Conference on e-Engineering and Digital Enterprise Technology - Leeds, United Kingdom Duration: 1 Sept 2004 → 3 Sept 2004

Conference

Conference	Advances in e-Engineering and Digital Enterprise Technology - I. Proceedings of the Fourth International Conference on e-Engineering and Digital Enterprise Technology
Country/Territory	United Kingdom
City	Leeds
Period	1/09/04 → 3/09/04

ASJC Scopus subject areas

Engineering(all)

Cite this

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title = "A mixed integer programming model for integrating MRP and job shop scheduling",

abstract = "This paper presents a Mixed Integer Programming (MIP) model which succeeds in a systematic integration of the production planning and job shop scheduling problems. The proposed model explicitly considers capacity constraints, operation sequences, lead times and due dates in a dynamic demand environment. The objective of the model is to seek the minimum both production flow time and penalty costs including tardiness and earliness costs. The output of the model is operation schedules with order starting time and finish time. The integrated model is verified with a commercial software package and tested with a small example. The model will be further improved and meta-heuristics will be used to solve the model more efficiently.",

author = "Chen, {K. J.} and Ping Ji",

year = "2004",

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booktitle = "Advances in e-Engineering and Digital Enterprise Technology - I. Proceedings of the Fourth International Conference on e-Engineering and Digital Enterprise Technology",

note = "Advances in e-Engineering and Digital Enterprise Technology - I. Proceedings of the Fourth International Conference on e-Engineering and Digital Enterprise Technology ; Conference date: 01-09-2004 Through 03-09-2004",

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Chen, KJ & Ji, P 2004, A mixed integer programming model for integrating MRP and job shop scheduling. in Advances in e-Engineering and Digital Enterprise Technology - I. Proceedings of the Fourth International Conference on e-Engineering and Digital Enterprise Technology. pp. 145-150, Advances in e-Engineering and Digital Enterprise Technology - I. Proceedings of the Fourth International Conference on e-Engineering and Digital Enterprise Technology, Leeds, United Kingdom, 1/09/04.

A mixed integer programming model for integrating MRP and job shop scheduling. / Chen, K. J.; Ji, Ping.

Advances in e-Engineering and Digital Enterprise Technology - I. Proceedings of the Fourth International Conference on e-Engineering and Digital Enterprise Technology. 2004. p. 145-150.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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N2 - This paper presents a Mixed Integer Programming (MIP) model which succeeds in a systematic integration of the production planning and job shop scheduling problems. The proposed model explicitly considers capacity constraints, operation sequences, lead times and due dates in a dynamic demand environment. The objective of the model is to seek the minimum both production flow time and penalty costs including tardiness and earliness costs. The output of the model is operation schedules with order starting time and finish time. The integrated model is verified with a commercial software package and tested with a small example. The model will be further improved and meta-heuristics will be used to solve the model more efficiently.

AB - This paper presents a Mixed Integer Programming (MIP) model which succeeds in a systematic integration of the production planning and job shop scheduling problems. The proposed model explicitly considers capacity constraints, operation sequences, lead times and due dates in a dynamic demand environment. The objective of the model is to seek the minimum both production flow time and penalty costs including tardiness and earliness costs. The output of the model is operation schedules with order starting time and finish time. The integrated model is verified with a commercial software package and tested with a small example. The model will be further improved and meta-heuristics will be used to solve the model more efficiently.

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M3 - Conference article published in proceeding or book

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BT - Advances in e-Engineering and Digital Enterprise Technology - I. Proceedings of the Fourth International Conference on e-Engineering and Digital Enterprise Technology

T2 - Advances in e-Engineering and Digital Enterprise Technology - I. Proceedings of the Fourth International Conference on e-Engineering and Digital Enterprise Technology

Y2 - 1 September 2004 through 3 September 2004

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A mixed integer programming model for integrating MRP and job shop scheduling

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