DocumentCode :
2917365
Title :
Methods for decreasing the number of objective evaluations for independent computationally expensive objective problems
Author :
Rohling, Greg
Author_Institution :
Georgia Tech Res. Inst., Atlanta, GA
fYear :
2008
fDate :
1-6 June 2008
Firstpage :
3305
Lastpage :
3310
Abstract :
In this paper, three new methods for pushing solutions toward a desired region of the objective space more quickly are explored; hypercube distance scaling, dynamic objective thresholding, and hypercube distance objective ordering. These methods are applicable for problems that do not require the entire Pareto front and that require an independent computationally expensive computation for each objective. The performance of these methods is evaluated with the multiple objective 0/1 knapsack problem.
Keywords :
Pareto optimisation; evolutionary computation; geometry; knapsack problems; Pareto front; dynamic objective thresholding; hypercube distance objective ordering; hypercube distance scaling; independent computationally expensive objective problems; knapsack problem; objective evaluations; Evolutionary computation; Hafnium; Hypercubes; Multidimensional systems; Optimization methods; Pareto optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1822-0
Electronic_ISBN :
978-1-4244-1823-7
Type :
conf
DOI :
10.1109/CEC.2008.4631245
Filename :
4631245
Link To Document :
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