Bentley, Peter J. and Wakefield, Jonathan P. (1998) Finding acceptable solutions in the pareto-optimal range using multiobjective genetic algorithms. In: Soft Computing in Engineering Design and Manufacturing. Springer-Verlag, pp. 231-240. ISBN 3-540-76214-0
This paper investigates the problem of using a genetic algorithm to converge on a small, user-defined subset of acceptable solutions to multiobjective problems, in the Pareto-optimal (P-O) range. The paper initially explores exactly why separate objectives can cause problems in a genetic algorithm (GA). A technique to guide the GA to converge on the subset of acceptable solutions is then introduced.
The paper then describes the application of six multiobjective techniques (three established methods and three new, or less commonly used methods) to four test functions. The previously unpublished distribution of solutions produced in the P-O range(s) by each method is described. The distribution of solutions and the ability of each method to guide the GA to converge on a small, user-defined subset of P-O solutions is then assessed, with the conclusion that two of the new multiobjective ranking methods are most useful.
|Item Type:||Book Chapter|
|Additional Information:||Presented at the 2nd On-line World Conference on Soft Computing in Engineering Design and Manufacturing (WSC2), 23-27 June 1997. The original publication is available at www.springerlink.com|
|Subjects:||T Technology > T Technology (General)|
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > TA Engineering (General). Civil engineering (General)
|Schools:||School of Computing and Engineering|
School of Computing and Engineering > Pedagogical Research Group
School of Computing and Engineering > Music Technology and Production Research Group
|Depositing User:||Jonathan Wakefield|
|Date Deposited:||12 May 2009 16:29|
|Last Modified:||16 Dec 2010 10:23|
Downloads per month over past year
Repository Staff Only: item control page