Optimised Job-Shop Scheduling via Genetic Algorithm for a Manufacturing Production System

Zhonghua Shen; Keith J. Burnham; Leonid Smalov

doi:10.1007/978-3-319-08422-0_13

Optimised Job-Shop Scheduling via Genetic Algorithm for a Manufacturing Production System

Zhonghua Shen, Keith J. Burnham, Leonid Smalov

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

5 Citations (Scopus)

Abstract

The present work aims to develop a genetic algorithm (GA)-based approach to optimise the job-shop scheduling problem in a micro-brewery to minimise the production time and costs. In a production system, orders are placed randomly to form a queue. The problem is how to optimally schedule the tasks through the production process given the constraints on capacity and the customer satisfaction/service level. The work concentrates on formulating a mathematical model and to modify the scheduling problem based on a GA approach

Original language	English
Title of host publication	Advances in Intelligent Systems and Computing: Proceedings of the Twenty-Third International Conference on Systems Engineering
Editors	Henry Selvaraj, Dawid Zydek, Grzegorz Chmaj
Publisher	Springer Verlag
Pages	89-92
Volume	1089
ISBN (Print)	978-3-319-08421-3
DOIs	https://doi.org/10.1007/978-3-319-08422-0_13
Publication status	Published - 2015

Bibliographical note

This paper is not available on the repository. The paper was given at the 23rd International Conference on Systems Engineering, ICSEng 2014; Las Vegas, NV; United States; 19 August 2014 through 21 August 2014

Keywords

genetic algorithm
mathematical model
production process
scheduling

Access to Document

10.1007/978-3-319-08422-0_13

Cite this

Shen, Z., Burnham, K. J., & Smalov, L. (2015). Optimised Job-Shop Scheduling via Genetic Algorithm for a Manufacturing Production System. In H. Selvaraj, D. Zydek, & G. Chmaj (Eds.), Advances in Intelligent Systems and Computing: Proceedings of the Twenty-Third International Conference on Systems Engineering (Vol. 1089, pp. 89-92). Springer Verlag. https://doi.org/10.1007/978-3-319-08422-0_13

Optimised Job-Shop Scheduling via Genetic Algorithm for a Manufacturing Production System. / Shen, Zhonghua; Burnham, Keith J.; Smalov, Leonid.
Advances in Intelligent Systems and Computing: Proceedings of the Twenty-Third International Conference on Systems Engineering. ed. / Henry Selvaraj; Dawid Zydek; Grzegorz Chmaj. Vol. 1089 Springer Verlag, 2015. p. 89-92.

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

Shen, Z, Burnham, KJ & Smalov, L 2015, Optimised Job-Shop Scheduling via Genetic Algorithm for a Manufacturing Production System. in H Selvaraj, D Zydek & G Chmaj (eds), Advances in Intelligent Systems and Computing: Proceedings of the Twenty-Third International Conference on Systems Engineering. vol. 1089, Springer Verlag, pp. 89-92. https://doi.org/10.1007/978-3-319-08422-0_13

Shen, Zhonghua ; Burnham, Keith J. ; Smalov, Leonid. / Optimised Job-Shop Scheduling via Genetic Algorithm for a Manufacturing Production System. Advances in Intelligent Systems and Computing: Proceedings of the Twenty-Third International Conference on Systems Engineering. editor / Henry Selvaraj ; Dawid Zydek ; Grzegorz Chmaj. Vol. 1089 Springer Verlag, 2015. pp. 89-92

@inbook{e6637b624177499789a65ff9c5c8e03b,

title = "Optimised Job-Shop Scheduling via Genetic Algorithm for a Manufacturing Production System",

abstract = "The present work aims to develop a genetic algorithm (GA)-based approach to optimise the job-shop scheduling problem in a micro-brewery to minimise the production time and costs. In a production system, orders are placed randomly to form a queue. The problem is how to optimally schedule the tasks through the production process given the constraints on capacity and the customer satisfaction/service level. The work concentrates on formulating a mathematical model and to modify the scheduling problem based on a GA approach",

keywords = "genetic algorithm, mathematical model, production process, scheduling",

author = "Zhonghua Shen and Burnham, {Keith J.} and Leonid Smalov",

note = "This paper is not available on the repository. The paper was given at the 23rd International Conference on Systems Engineering, ICSEng 2014; Las Vegas, NV; United States; 19 August 2014 through 21 August 2014",

year = "2015",

doi = "10.1007/978-3-319-08422-0_13",

language = "English",

isbn = "978-3-319-08421-3",

volume = "1089",

pages = "89--92",

editor = "Henry Selvaraj and Dawid Zydek and Grzegorz Chmaj",

booktitle = "Advances in Intelligent Systems and Computing: Proceedings of the Twenty-Third International Conference on Systems Engineering",

publisher = "Springer Verlag",

address = "Austria",

}

TY - CHAP

T1 - Optimised Job-Shop Scheduling via Genetic Algorithm for a Manufacturing Production System

AU - Shen, Zhonghua

AU - Burnham, Keith J.

AU - Smalov, Leonid

N1 - This paper is not available on the repository. The paper was given at the 23rd International Conference on Systems Engineering, ICSEng 2014; Las Vegas, NV; United States; 19 August 2014 through 21 August 2014

PY - 2015

Y1 - 2015

N2 - The present work aims to develop a genetic algorithm (GA)-based approach to optimise the job-shop scheduling problem in a micro-brewery to minimise the production time and costs. In a production system, orders are placed randomly to form a queue. The problem is how to optimally schedule the tasks through the production process given the constraints on capacity and the customer satisfaction/service level. The work concentrates on formulating a mathematical model and to modify the scheduling problem based on a GA approach

AB - The present work aims to develop a genetic algorithm (GA)-based approach to optimise the job-shop scheduling problem in a micro-brewery to minimise the production time and costs. In a production system, orders are placed randomly to form a queue. The problem is how to optimally schedule the tasks through the production process given the constraints on capacity and the customer satisfaction/service level. The work concentrates on formulating a mathematical model and to modify the scheduling problem based on a GA approach

KW - genetic algorithm

KW - mathematical model

KW - production process

KW - scheduling

U2 - 10.1007/978-3-319-08422-0_13

DO - 10.1007/978-3-319-08422-0_13

M3 - Chapter

SN - 978-3-319-08421-3

VL - 1089

SP - 89

EP - 92

BT - Advances in Intelligent Systems and Computing: Proceedings of the Twenty-Third International Conference on Systems Engineering

A2 - Selvaraj, Henry

A2 - Zydek, Dawid

A2 - Chmaj, Grzegorz

PB - Springer Verlag

ER -

Optimised Job-Shop Scheduling via Genetic Algorithm for a Manufacturing Production System

Abstract

Bibliographical note

Keywords

Access to Document

Fingerprint

Cite this