OPTIMUS: Self-Adaptive Differential Evolution with Ensemble of Mutation Strategies for Grasshopper Algorithmic Modeling

dc.contributor.author Cemre Cubukcuoglu
dc.contributor.author Berk Ekici
dc.contributor.author Mehmet Fatih Tasgetiren
dc.contributor.author Sevil Sariyildiz
dc.contributor.author Ekici, Berk
dc.contributor.author Sariyildiz, Sevil
dc.contributor.author Tasgetiren, Mehmet Fatih
dc.contributor.author Cubukcuoglu, Cemre
dc.date JUL
dc.date.accessioned 2025-10-06T16:22:30Z
dc.date.issued 2019
dc.description.abstract Most of the architectural design problems are basically real-parameter optimization problems. So any type of evolutionary and swarm algorithms can be used in this field. However there is a little attention on using optimization methods within the computer aided design (CAD) programs. In this paper we present Optimus which is a new optimization tool for grasshopper algorithmic modeling in Rhinoceros CAD software. Optimus implements self-adaptive differential evolution algorithm with ensemble of mutation strategies (jEDE). We made an experiment using standard test problems in the literature and some of the test problems proposed in IEEE CEC 2005. We reported minimum maximum average standard deviations and number of function evaluations of five replications for each function. Experimental results on the benchmark suite showed that Optimus (jEDE) outperforms other optimization tools namely Galapagos (genetic algorithm) SilverEye (particle swarm optimization) and Opossum (RbfOpt) by finding better results for 19 out of 20 problems. For only one function Galapagos presented slightly better result than Optimus. Ultimately we presented an architectural design problem and compared the tools for testing Optimus in the design domain. We reported minimum maximum average and number of function evaluations of one replication for each tool. Galapagos and Silvereye presented infeasible results whereas Optimus and Opossum found feasible solutions. However Optimus discovered a much better fitness result than Opossum. As a conclusion we discuss advantages and limitations of Optimus in comparison to other tools. The target audience of this paper is frequent users of parametric design modelling e.g. architects engineers designers. The main contribution of this paper is summarized as follows. Optimus showed that near-optimal solutions of architectural design problems can be improved by testing different types of algorithms with respect to no-free lunch theorem. Moreover Optimus facilitates implementing different type of algorithms due to its modular system.
dc.description.sponsorship M.F.T. was partially funded by the National Natural Science Foundation of China (Grant No. 51435009).
dc.description.sponsorship National Natural Science Foundation of China [51435009]
dc.description.sponsorship National Natural Science Foundation of China, NSFC, (51435009)
dc.identifier.doi 10.3390/a12070141
dc.identifier.issn 1999-4893
dc.identifier.scopus 2-s2.0-85075565129
dc.identifier.uri http://dx.doi.org/10.3390/a12070141
dc.identifier.uri https://gcris.yasar.edu.tr/handle/123456789/7410
dc.identifier.uri https://doi.org/10.3390/a12070141
dc.language.iso English
dc.publisher MDPI
dc.relation.ispartof Algorithms
dc.rights info:eu-repo/semantics/openAccess
dc.source ALGORITHMS
dc.subject grasshopper, optimization, differential evolution, architectural design, computational design, performance based design, building performance optimization, single-objective optimization, architectural design optimization, parametric design
dc.subject OPTIMIZATION, PERFORMANCE, PARAMETERS, BENCHMARK, SEARCH
dc.subject Differential Evolution
dc.subject Architectural Design
dc.subject Performance Based Design
dc.subject Optimization
dc.subject Building Performance Optimization
dc.subject Grasshopper
dc.subject Computational Design
dc.subject Single-Objective Optimization
dc.subject Architectural Design Optimization
dc.subject Parametric Design
dc.title OPTIMUS: Self-Adaptive Differential Evolution with Ensemble of Mutation Strategies for Grasshopper Algorithmic Modeling
dc.type Article
dspace.entity.type Publication
gdc.author.id Ekici, Berk/0000-0003-0406-9569
gdc.author.id Tasgetiren, M Fatih/0000-0001-8625-3671
gdc.author.id Tasgetiren, Mehmet Fatih/0000-0002-5716-575X
gdc.author.id Ugurlu, Cemre/0000-0001-8907-5903
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gdc.description.department
gdc.description.departmenttemp [Cubukcuoglu, Cemre; Ekici, Berk; Sariyildiz, Sevil] Delft Univ Technol, Fac Architecture & Built Environm, Chair Design Informat, Julianalaan 134, NL-2628 BL Delft, Netherlands; [Cubukcuoglu, Cemre] Yasar Univ, Fac Architecture, Dept Interior Architecture & Environm Design, Univ Caddesi,37-39 Agacli Yol, TR-35100 Izmir, Turkey; [Tasgetiren, Mehmet Fatih] Istinye Univ, Dept Ind & Syst Engn, Maltepe Mahallesi,Cirp Yolu B Ck 9, TR-34010 Istanbul, Turkey
gdc.description.issue 7
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
gdc.description.startpage 141
gdc.description.volume 12
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gdc.virtual.author Ekici, Berk
gdc.virtual.author Çubukçuoğlu, Cemre
gdc.virtual.author Taşgetiren, Mehmet Fatih
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person.identifier.orcid Cubukcuoglu- Cemre/0000-0001-8907-5903, Ekici- Berk/0000-0003-0406-9569, Tasgetiren- Mehmet Fatih/0000-0002-5716-575X, Tasgetiren- M. Fatih/0000-0001-8625-3671,
project.funder.name National Natural Science Foundation of China [51435009]
publicationissue.issueNumber 7
publicationvolume.volumeNumber 12
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