Colombo, Gualtiero and Mumford, Christine Lesley ![]() |
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Abstract
This paper compares the performance of three evolutionary multi-objective algorithms on the multiobjective knapsack problem. The three algorithms are SPEA2 (strength Pareto evolutionary algorithm, version 2), MOGLS (multi objective genetic local search) and SEAMO2 (simple evolutionary algorithm for multiobjective optimization, version 2). For each algorithm, we try two representations: bit-string and order-based. Our results suggest that a bit-string representation works best for MOGLS, but that SPEA2 and SEAMO2 perform better with an order-based approach. Although MOGLS outperforms the other algorithms in terms of solution quality, SEAMO2 runs much faster than its competitors and produces results of a similar standard to SPEA2.
Item Type: | Conference or Workshop Item (Paper) |
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Date Type: | Publication |
Status: | Published |
Schools: | Computer Science & Informatics |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
Additional Information: | Date of conference: 2-5 September 2005 |
Publisher: | IEEE |
ISBN: | 07803-93635 |
Date of First Compliant Deposit: | 30 March 2016 |
Last Modified: | 04 Feb 2025 16:45 |
URI: | https://orca.cardiff.ac.uk/id/eprint/31248 |
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