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{ "item_title" : "Development of a Genetic Algorithm to Automate Clustering of a Dependency Structure Matrix", "item_author" : [" James L. Rogers", "Nasa Technical Reports Server (Ntrs)", "Et Al "], "item_description" : "Much technology assessment and organization design data exists in Microsoft Excel spreadsheets. Tools are needed to put this data into a form that can be used by design managers to make design decisions. One need is to cluster data that is highly coupled. Tools such as the Dependency Structure Matrix (DSM) and a Genetic Algorithm (GA) can be of great benefit. However, no tool currently combines the DSM and a GA to solve the clustering problem. This paper describes a new software tool that interfaces a GA written as an Excel macro with a DSM in spreadsheet format. The results of several test cases are included to demonstrate how well this new tool works.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/1/28/725/415/1287254152_b.jpg", "price_data" : { "retail_price" : "14.75", "online_price" : "14.75", "our_price" : "14.75", "club_price" : "14.75", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Development of a Genetic Algorithm to Automate Clustering of a Dependency Structure Matrix|James L. Rogers

Development of a Genetic Algorithm to Automate Clustering of a Dependency Structure Matrix

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Overview

Much technology assessment and organization design data exists in Microsoft Excel spreadsheets. Tools are needed to put this data into a form that can be used by design managers to make design decisions. One need is to cluster data that is highly coupled. Tools such as the Dependency Structure Matrix (DSM) and a Genetic Algorithm (GA) can be of great benefit. However, no tool currently combines the DSM and a GA to solve the clustering problem. This paper describes a new software tool that interfaces a GA written as an Excel macro with a DSM in spreadsheet format. The results of several test cases are included to demonstrate how well this new tool works.

Details

  • ISBN-13: 9781287254157
  • ISBN-10: 1287254152
  • Publisher: Bibliogov
  • Publish Date: July 2013
  • Dimensions: 9.69 x 7.44 x 0.05 inches
  • Shipping Weight: 0.13 pounds
  • Page Count: 22

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