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The quadratic assignment problem in the context of the printed circuit [An article from: Computers and Operations Research]
Book Details
Author(s)E. Duman, I. Or
PublisherElsevier
ISBN / ASINB000P6OFYG
ISBN-13978B000P6OFY6
MarketplaceUnited Kingdom 🇬🇧
Description
This digital document is a journal article from Computers and Operations Research, published by Elsevier in 2007. 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 sequencing of placement and the configuration of the feeder is among the main problems involved in printed circuit board (PCB) assembly optimization. In some machine architectures, the latter problem can be formulated as the well known NP-hard quadratic assignment problem (QAP). In this study, a search is made among those metaheuristics that have recently found widespread application in order to identify a heuristic procedure that performs well with the QAP in the PCB assembly context. To this end, specific algorithms reflecting implementations of Taboo Search, Simulated Annealing and Genetic Algorithm-type metaheuristics were tested and compared using real PCB assembly data. The same set of algorithms was also tested on general QAP problems and it was observed that algorithms which performed successfully in the PCB context could perform poorly in the general situation. In the light of this, it can be concluded that ascertaining the best performing heuristic is complicated by the fact that the performance of a heuristic depends on the context of the problem, which determines the structure and relationships of problem parameters.
Description:
The sequencing of placement and the configuration of the feeder is among the main problems involved in printed circuit board (PCB) assembly optimization. In some machine architectures, the latter problem can be formulated as the well known NP-hard quadratic assignment problem (QAP). In this study, a search is made among those metaheuristics that have recently found widespread application in order to identify a heuristic procedure that performs well with the QAP in the PCB assembly context. To this end, specific algorithms reflecting implementations of Taboo Search, Simulated Annealing and Genetic Algorithm-type metaheuristics were tested and compared using real PCB assembly data. The same set of algorithms was also tested on general QAP problems and it was observed that algorithms which performed successfully in the PCB context could perform poorly in the general situation. In the light of this, it can be concluded that ascertaining the best performing heuristic is complicated by the fact that the performance of a heuristic depends on the context of the problem, which determines the structure and relationships of problem parameters.
