A new Reduced Space Searching Algorithm (RSSA) and its application in optimal design of alloy steels

Zhang, Qian and Mahfouf, Mahdi (2007) A new Reduced Space Searching Algorithm (RSSA) and its application in optimal design of alloy steels. In: Evolutionary Computation, 2007. CEC 2007. IEEE Congress on. IEEE pp. 1815-1822. ISBN 978-1-4244-1339-3. E-ISBN 978-1-4244-1340-9. (doi:https://doi.org/10.1109/CEC.2007.4424693) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

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Official URL
http://doi.org/10.1109/CEC.2007.4424693

Abstract

In this paper, a new search and optimisation algorithm based on a reduced space searching strategy, named RSSA, is presented. This algorithm originates from an idea which relates to a simple experience when humans search for an optimal solution to a 'real-life' problem, i.e. when humans search for a candidate solution given a certain objective, a large area tends to be scanned first; should one succeed in finding clues in relation to the predefined objective, then the search space is greatly reduced for a more detailed search. The proposed algorithm is validated via well-known benchmark functions and is found to be efficient. Furthermore, the algorithm is extended to include the multiobjective case. Simulation results of optimising some challenging benchmark multiobjective problems, including the ZDT and DTLZ series problems, suggest that the new algorithm can locate the Pareto-optimal front and performs better than some other salient optimisation algorithms. Then, this proposed algorithm is successfully applied to the optimal design of alloy steels, which aims at determining the optimal heat treatment regimes and the required weight percentages for the chemical composites in order to obtain the pre-defined mechanical properties of the material.

Item Type: Conference or workshop item (Paper)
Subjects: Q Science > Q Science (General) > Q335 Artificial intelligence
T Technology > TA Engineering (General). Civil engineering (General) > TA168 Systems engineering, cybernetics and intelligent systems
T Technology > TA Engineering (General). Civil engineering (General) > TA 403 Materials Science
Divisions: Faculties > Sciences > School of Engineering and Digital Arts > Instrumentation, Control and Embedded Systems
Depositing User: Qian Zhang
Date Deposited: 18 Sep 2015 16:29 UTC
Last Modified: 21 Sep 2015 14:18 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/50553 (The current URI for this page, for reference purposes)
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