Proceedings of the 5th International Conference on Advanced Design and Manufacturing Engineering

A genetic algorithm to determine a production schedule under time-vary unit cost and shortages

Authors
Chang Ouyang Bing, Bo Hsiao Liang
Corresponding Author
Chang Ouyang Bing
Available Online October 2015.
DOI
https://doi.org/10.2991/icadme-15.2015.71How to use a DOI?
Keywords
Time-vary unit cost; Economic production quantity; Shortage; Genetic algorithm
Abstract
Considering a linear or exponential trend in unit production cost under a foreseeable time horizon, this study discusses the economic production quantity (EPQ) with shortages problem for a production system. A genetic algorithm (GA) with the chromosome of real number type to solve this problem is presented. Although, standard GA operators are used to generate new populations, the particular of this study is that we select two differentiate equations to develop a proposed production scheme. Then, compute the total cost with this production scheme as the fitness function to evaluate the populations. In this study, an explicit procedure to obtain the local optimal solution is provided and numerical examples to illustrate the proposed model are shown as well.
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This is an open access article distributed under the CC BY-NC license.

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Volume Title
Proceedings of the 5th International Conference on Advanced Design and Manufacturing Engineering
Series
Advances in Engineering Research
Publication Date
October 2015
ISBN
978-94-6252-113-1
ISSN
2352-5401
DOI
https://doi.org/10.2991/icadme-15.2015.71How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Chang Ouyang Bing
AU  - Bo Hsiao Liang
PY  - 2015/10
DA  - 2015/10
TI  - A genetic algorithm to determine a production schedule under time-vary unit cost and shortages
BT  - Proceedings of the 5th International Conference on Advanced Design and Manufacturing Engineering
PB  - Atlantis Press
SP  - 356
EP  - 359
SN  - 2352-5401
UR  - https://doi.org/10.2991/icadme-15.2015.71
DO  - https://doi.org/10.2991/icadme-15.2015.71
ID  - Bing2015/10
ER  -