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Minimizing total flowtime and maximum earliness on a single machine using multiple measures of fitness

Published: 25 June 2005 Publication History
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  • Abstract

    The intent of this research is to investigate methods to use genetic algorithms to find the set of efficient solutions to a bi-criteria problem. We propose a general methodology which is characterized by using different criteria upon which the decision to retain chromosomes into the next generation is made. We perform elite reproduction based on two general measures of "eliteness": non-dominated in the current population and performance measured in terms of each criterion individually. We investigate its performance on a specific bi-criteria scheduling problem, minimizing total flowtime and maximum earliness on a single machine.

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    1. Minimizing total flowtime and maximum earliness on a single machine using multiple measures of fitness

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        cover image ACM Conferences
        GECCO '05: Proceedings of the 7th annual conference on Genetic and evolutionary computation
        June 2005
        2272 pages
        ISBN:1595930108
        DOI:10.1145/1068009
        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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        Published: 25 June 2005

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        1. bi-criteria scheduling
        2. multicriteria genetic algorithm

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