Ant colony optimization algorithm to the inter-cell layout problem in cellular manufacturing [An article from: European Journal of Operational Research]
Book Details
Author(s)M. Solimanpur, P. Vrat, R. Shankar
PublisherElsevier
ISBN / ASINB000RR0XE4
ISBN-13978B000RR0XE2
AvailabilityAvailable for download now
MarketplaceUnited States 🇺🇸
Description
This digital document is a journal article from European Journal of Operational Research, published by Elsevier in 2004. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
Description:
The inter-cell layout problem is discussed and a mathematical formulation for material flow between the cells is presented. The problem is modeled as a quadratic assignment problem (QAP). An ant algorithm is developed to solve the formulated problem. The performance of the proposed ant algorithm is compared to the facility layout algorithms such as H63, HC63-66, CRAFT and Bubble Search as well as other existing ant colony implementations for QAP such as FANT, HAS-QAP, MMAS-QAP"2"-"o"p"t, and ANTS algorithms. The experimental results show that the proposed ant algorithm performs significantly better than the facility layout algorithms. Also, our experimental results reveal that the proposed ant algorithm is effective and efficient as compared to other existing ant algorithms.
Description:
The inter-cell layout problem is discussed and a mathematical formulation for material flow between the cells is presented. The problem is modeled as a quadratic assignment problem (QAP). An ant algorithm is developed to solve the formulated problem. The performance of the proposed ant algorithm is compared to the facility layout algorithms such as H63, HC63-66, CRAFT and Bubble Search as well as other existing ant colony implementations for QAP such as FANT, HAS-QAP, MMAS-QAP"2"-"o"p"t, and ANTS algorithms. The experimental results show that the proposed ant algorithm performs significantly better than the facility layout algorithms. Also, our experimental results reveal that the proposed ant algorithm is effective and efficient as compared to other existing ant algorithms.
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