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Journals / Istanbul University Journal of Electrical and Electronics Engineering / 2009 / Cilt: 9 - Sayı: 2

A modified genetic algorithm for the generalized assignment problems

Mustafa B. AKBULUT
A. Egemen YILMAZ
Pages
951–958
Publication Date
2022-10-18
DOI
—
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AI Summary & Key Takeaways

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

The performance of the proposed method has been investigated in details viasome test cases constructed for the multi-target tracking problems.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this paper, a specialized Genetic Algorithm is proposed and applied for the solution of the GeneralizedAssignment Problem.
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Key Findings & Data:Special crossover and the mutation operators called Common Element Crossover (CEX) andIn-Pool Mutation (IPM) respectively has been defined by focusing on the special needs and nature of theGeneralized Assignment Problem.
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Conclusion & Impact:The performance of the proposed method has been investigated in details viasome test cases constructed for the multi-target tracking problems.
🔬Design:Lab & Field Experiment
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

In this paper, a specialized Genetic Algorithm is proposed and applied for the solution of the GeneralizedAssignment Problem. Special crossover and the mutation operators called Common Element Crossover (CEX) andIn-Pool Mutation (IPM) respectively has been defined by focusing on the special needs and nature of theGeneralized Assignment Problem. The performance of the proposed method has been investigated in details viasome test cases constructed for the multi-target tracking problems.

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Cite This Article

AKBULUT, M. B., YILMAZ, A. E. (2022). A modified genetic algorithm for the generalized assignment problems. Istanbul University Journal of Electrical and Electronics Engineering, Cilt: 9 - Sayı: 2, 951–958. https://ajindex.com/articles/543733

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