dc.contributor.author | Chugh, T | |
dc.contributor.author | Kratky, T | |
dc.contributor.author | Miettinen, K | |
dc.contributor.author | Jin, Y | |
dc.contributor.author | Makkonen, P | |
dc.date.accessioned | 2019-06-07T08:47:43Z | |
dc.date.issued | 2019-07-17 | |
dc.description.abstract | We formulate and solve a real-world shape design optimization problem of an air intake ventilation system in a tractor cabin by using a preference-based surrogate-assisted evolutionary multiobjective optimization algorithm. We are motivated by practical applicability and focus on two main challenges faced by practitioners in industry:\ 1) meaningful formulation of the optimization problem reflecting the needs of a decision maker and 2) finding a desirable solution based on a decision maker's preferences when solving a problem with computationally expensive function evaluations. For the first challenge, we describe the procedure of modelling a component in the air intake ventilation system with commercial simulation tools. The problem to be solved involves time consuming computational fluid dynamics simulations. Therefore, for the second challenge, we extend a recently proposed Kriging-assisted evolutionary algorithm K-RVEA to incorporate a decision maker's preferences. Our numerical results indicate efficiency in using the computing resources available and the solutions obtained reflect the decision maker's preferences well. Actually, two of the solutions dominate the baseline design (the design provided by the decision maker before the optimization process). The decision maker was satisfied with the results and eventually selected one as the final solution. | en_GB |
dc.description.sponsorship | Natural Environment Research Council (NERC) | en_GB |
dc.identifier.citation | The Genetic and Evolutionary Computation Conference (GECCO ’19), 2019-07-13, 2019-07-17, Prague, Czech Republic, pp. 1147-1155. | en_GB |
dc.identifier.doi | 10.1145/3321707.3321745 | |
dc.identifier.grantnumber | NE/P017436/1 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/37390 | |
dc.language.iso | en | en_GB |
dc.publisher | Association for Computing Machinery (ACM) | en_GB |
dc.rights | ©2019 Association for Computing Machinery. Permission to make digital or hard copies of all or part of this work for personal orclassroom use is granted without fee provided that copies are not made or distributedfor profit or commercial advantage and that copies bear this notice and the full citationon the first page. Copyrights for components of this work owned by others than ACMmust be honored. Abstracting with credit is permitted. To copy otherwise, or republish,to post on servers or to redistribute to lists, requires prior specific permission and/or afee. Request permissions from permissions@acm.org | en_GB |
dc.subject | evolutionary optimization | en_GB |
dc.subject | Pareto optimality | en_GB |
dc.subject | decision-making | en_GB |
dc.subject | Computer-aided design | en_GB |
dc.title | Multiobjective shape design in a ventilation system with a preference-driven surrogate-assisted evolutionary algorithm | en_GB |
dc.type | Conference proceedings | en_GB |
dc.date.available | 2019-06-07T08:47:43Z | |
dc.identifier.isbn | 9781450361118 | |
dc.description | This is the author accepted manuscript. The final version is available from the Association for Computing Machinery via the DOI in this record. | en_GB |
dc.rights.uri | http://www.rioxx.net/licenses/all-rights-reserved | en_GB |
pubs.funder-ackownledgement | Yes | en_GB |
dcterms.dateAccepted | 2019-03-20 | |
exeter.funder | ::Natural Environment Research Council (NERC) | en_GB |
rioxxterms.version | AM | en_GB |
rioxxterms.licenseref.startdate | 2019-07-13 | |
rioxxterms.type | Conference Paper/Proceeding/Abstract | en_GB |
refterms.dateFCD | 2019-06-05T16:22:19Z | |
refterms.versionFCD | AM | |
refterms.dateFOA | 2019-08-07T09:10:52Z | |
refterms.panel | B | en_GB |