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Minimizing total flowtime and maximum earliness on a single machine using multiple measures of fitness
Author(s) -
Mary E. Kurz,
Sarah Canterbury
Publication year - 2005
Publication title -
citeseer x (the pennsylvania state university)
Language(s) - English
Resource type - Conference proceedings
ISBN - 1-59593-010-8
DOI - 10.1145/1068009.1068144
Subject(s) - mathematical optimization , computer science , single machine scheduling , population , scheduling (production processes) , set (abstract data type) , mathematics , job shop scheduling , schedule , demography , sociology , programming language , operating system
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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