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Journals / An International Journal of Optimization and Control: Theories & Applications (IJOCTA) / 2019 / Cilt: 9 - Sayı: 2

A genetic algorithm for fuzzy order acceptance and scheduling problem

Esra KARAKAŞ
Hakan ÖZPALAMUTÇU
Pages
186–196
Publication Date
2022-10-11
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Due to the NP-hard nature of the problem, the developed GA hasgreat importance to obtain a solution even for big scale fuzzy OAS problem.Also, the proposed GA can be utilized easily by all practitioners via thedeveloped user interface.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In light of the imprecise and fuzzy nature of real production environments, theorder acceptance and scheduling (OAS) problem is associated with fuzzyprocessing times, fuzzy sequence dependent set up time and fuzzy due dates.
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Key Findings & Data:The proposed algorithm is illustratedand analyzed using examples with different order sizes.
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Conclusion & Impact:Due to the NP-hard nature of the problem, the developed GA hasgreat importance to obtain a solution even for big scale fuzzy OAS problem.Also, the proposed GA can be utilized easily by all practitioners via thedeveloped user interface.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

In light of the imprecise and fuzzy nature of real production environments, theorder acceptance and scheduling (OAS) problem is associated with fuzzyprocessing times, fuzzy sequence dependent set up time and fuzzy due dates. Inthis study, a genetic algorithm (GA) which uses fuzzy ranking methods isproposed to solve the fuzzy OAS problem. The proposed algorithm is illustratedand analyzed using examples with different order sizes. As illustrative numericalexamples, fuzzy OAS problems with 10, 15, 20, 25, 30 and 100 orders areconsidered. The feasibility and effectiveness of the proposed method aredemonstrated. Due to the NP-hard nature of the problem, the developed GA hasgreat importance to obtain a solution even for big scale fuzzy OAS problem.Also, the proposed GA can be utilized easily by all practitioners via thedeveloped user interface.

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Cite This Article

KARAKAŞ, E., ÖZPALAMUTÇU, H. (2022). A genetic algorithm for fuzzy order acceptance and scheduling problem. An International Journal of Optimization and Control: Theories & Applications (IJOCTA), Cilt: 9 - Sayı: 2, 186–196. https://ajindex.com/articles/440595

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