Configuring advanced evolutionary algorithms for multicriteria building spatial design optimisation

K. van der Blom, S. Boonstra, H. Hofmeyer, T. Bäck, M.T.M. Emmerich

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

9 Citations (Scopus)
6 Downloads (Pure)


In this paper solution approaches for solving the building spatial design optimisation problem for structural and energy performance are advanced on multiple fronts. A new initialisation operator is introduced to generate an unbiased initial population for a tailored version of SMS-EMOA with problem specific operators. Improvements to the mutation operator are proposed to eliminate bias and allow mutations consisting of multiple steps. Moreover, landscape analysis is applied in order to explore the landscape of both objectives and investigate the behaviour of the mutation operator. Parameter tuning is applied with the irace package and the Mixed Integer Evolution Strategy to find improved parameter settings and explore tuning with a relatively small number of expensive evaluations. Finally, the performances of the standard and tailored SMS-EMOA algorithms with tuned parameters are compared.

Original languageEnglish
Title of host publication2017 IEEE Congress on Evolutionary Computation (CEC) Proceedings, June 5-8, 2017, Donostia - San Sebastián, Spain
PublisherInstitute of Electrical and Electronics Engineers
Number of pages8
ISBN (Electronic)9781509046010
ISBN (Print)978-1-5090-4601-0
Publication statusPublished - 5 Jul 2017
Event2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Donostia-San Sebastian, Spain
Duration: 5 Jun 20178 Jun 2017


Conference2017 IEEE Congress on Evolutionary Computation, CEC 2017
Abbreviated titleCEC2017
CityDonostia-San Sebastian
Internet address


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