Intelligent apparel production planning for optimizing manual operations using fuzzy set theory and evolutionary algorithms

P. Y. Mok

doi:10.1109/GEFS.2011.5949496

Intelligent apparel production planning for optimizing manual operations using fuzzy set theory and evolutionary algorithms

P. Y. Mok^*

^*Corresponding author for this work

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

5 Citations (Scopus)

Abstract

Effective and accurate production planning is essential for garment manufacturers to survive in today's competitive apparel industry. Varying customer demands, shorter lifecycles and changing fashion trends are amongst the factors that make accurate production planning important. Manufacturers strive to fulfil requirements such as on-time completion, short production lead time and effective allocation of job order to specific production lines. However, effective production planning is difficult to achieve because the apparel manufacturing environment is fuzzy and dynamic. This paper suggests the use of intelligent production planning algorithms, based on fuzzy set theory, genetic algorithms (GA) and multi-objective genetic algorithms (MOGA), to achieve optimal solutions for apparel production planning.

Original language	English
Title of host publication	IEEE SSCI 2011
Subtitle of host publication	Symposium Series on Computational Intelligence - GEFS 2011: 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems
Pages	103-110
Number of pages	8
DOIs	https://doi.org/10.1109/GEFS.2011.5949496
Publication status	Published - 2011
Externally published	Yes
Event	Symposium Series on Computational Intelligence, IEEE SSCI 2011 - 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems, GEFS 2011 - Paris, France Duration: 11 Apr 2011 → 15 Apr 2011

Publication series

Name	IEEE SSCI 2011: Symposium Series on Computational Intelligence - GEFS 2011: 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems

Conference

Conference	Symposium Series on Computational Intelligence, IEEE SSCI 2011 - 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems, GEFS 2011
Country/Territory	France
City	Paris
Period	11/04/11 → 15/04/11

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Keywords

Apparel Production Planning and Learning Curve Effects
Evolutionary computing and genetic algorithm
Fuzzy set

Access to Document

10.1109/GEFS.2011.5949496

Cite this

Mok, P. Y. (2011). Intelligent apparel production planning for optimizing manual operations using fuzzy set theory and evolutionary algorithms. In IEEE SSCI 2011: Symposium Series on Computational Intelligence - GEFS 2011: 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems (pp. 103-110). Article 5949496 (IEEE SSCI 2011: Symposium Series on Computational Intelligence - GEFS 2011: 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems). https://doi.org/10.1109/GEFS.2011.5949496

Mok, P. Y. / Intelligent apparel production planning for optimizing manual operations using fuzzy set theory and evolutionary algorithms. IEEE SSCI 2011: Symposium Series on Computational Intelligence - GEFS 2011: 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems. 2011. pp. 103-110 (IEEE SSCI 2011: Symposium Series on Computational Intelligence - GEFS 2011: 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems).

@inproceedings{faeda7834ede44d4a237a2934446671a,

title = "Intelligent apparel production planning for optimizing manual operations using fuzzy set theory and evolutionary algorithms",

abstract = "Effective and accurate production planning is essential for garment manufacturers to survive in today's competitive apparel industry. Varying customer demands, shorter lifecycles and changing fashion trends are amongst the factors that make accurate production planning important. Manufacturers strive to fulfil requirements such as on-time completion, short production lead time and effective allocation of job order to specific production lines. However, effective production planning is difficult to achieve because the apparel manufacturing environment is fuzzy and dynamic. This paper suggests the use of intelligent production planning algorithms, based on fuzzy set theory, genetic algorithms (GA) and multi-objective genetic algorithms (MOGA), to achieve optimal solutions for apparel production planning.",

keywords = "Apparel Production Planning and Learning Curve Effects, Evolutionary computing and genetic algorithm, Fuzzy set",

author = "Mok, \{P. Y.\}",

year = "2011",

doi = "10.1109/GEFS.2011.5949496",

language = "English",

isbn = "9781612840505",

series = "IEEE SSCI 2011: Symposium Series on Computational Intelligence - GEFS 2011: 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems",

pages = "103--110",

booktitle = "IEEE SSCI 2011",

note = "Symposium Series on Computational Intelligence, IEEE SSCI 2011 - 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems, GEFS 2011 ; Conference date: 11-04-2011 Through 15-04-2011",

}

Mok, PY 2011, Intelligent apparel production planning for optimizing manual operations using fuzzy set theory and evolutionary algorithms. in IEEE SSCI 2011: Symposium Series on Computational Intelligence - GEFS 2011: 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems., 5949496, IEEE SSCI 2011: Symposium Series on Computational Intelligence - GEFS 2011: 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems, pp. 103-110, Symposium Series on Computational Intelligence, IEEE SSCI 2011 - 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems, GEFS 2011, Paris, France, 11/04/11. https://doi.org/10.1109/GEFS.2011.5949496

Intelligent apparel production planning for optimizing manual operations using fuzzy set theory and evolutionary algorithms. / Mok, P. Y.
IEEE SSCI 2011: Symposium Series on Computational Intelligence - GEFS 2011: 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems. 2011. p. 103-110 5949496 (IEEE SSCI 2011: Symposium Series on Computational Intelligence - GEFS 2011: 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems).

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

TY - GEN

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AU - Mok, P. Y.

PY - 2011

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AB - Effective and accurate production planning is essential for garment manufacturers to survive in today's competitive apparel industry. Varying customer demands, shorter lifecycles and changing fashion trends are amongst the factors that make accurate production planning important. Manufacturers strive to fulfil requirements such as on-time completion, short production lead time and effective allocation of job order to specific production lines. However, effective production planning is difficult to achieve because the apparel manufacturing environment is fuzzy and dynamic. This paper suggests the use of intelligent production planning algorithms, based on fuzzy set theory, genetic algorithms (GA) and multi-objective genetic algorithms (MOGA), to achieve optimal solutions for apparel production planning.

KW - Apparel Production Planning and Learning Curve Effects

KW - Evolutionary computing and genetic algorithm

KW - Fuzzy set

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UR - https://www.scopus.com/pages/publications/79961222429

U2 - 10.1109/GEFS.2011.5949496

DO - 10.1109/GEFS.2011.5949496

M3 - Conference Paper published in a book

SN - 9781612840505

T3 - IEEE SSCI 2011: Symposium Series on Computational Intelligence - GEFS 2011: 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems

SP - 103

EP - 110

BT - IEEE SSCI 2011

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Y2 - 11 April 2011 through 15 April 2011

ER -

Mok PY. Intelligent apparel production planning for optimizing manual operations using fuzzy set theory and evolutionary algorithms. In IEEE SSCI 2011: Symposium Series on Computational Intelligence - GEFS 2011: 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems. 2011. p. 103-110. 5949496. (IEEE SSCI 2011: Symposium Series on Computational Intelligence - GEFS 2011: 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems). doi: 10.1109/GEFS.2011.5949496

Intelligent apparel production planning for optimizing manual operations using fuzzy set theory and evolutionary algorithms

Abstract

Publication series

Conference

UN SDGs

Keywords

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