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Evolutionary Black-box Topology Optimization: Challenges and Promises

David Guirguis, Carlos Artemio Coello Coello, Kazuhiro Saitou, Nikola Aulig, Renato Picelli, Bo Zhu, Yuqing Zhou, William Vicente, Francesco Iorio, Markus Olhofer, Wojciech Matusik
2019 IEEE Transactions on Evolutionary Computation  
Black-box topology optimization (BBTO) uses evolutionary algorithms and other soft computing techniques to generate near-optimal topologies of mechanical structures.  ...  In this paper, we discuss topology optimization as a black-box optimization problem. We review the main BBTO methods, discuss their challenges and present approaches to relax them.  ...  in the conceptual and early design stages of mechanical structures, it can be extended to solve any problem regardless of the type of structure by using Black-box topology optimization (BBTO).  ... 
doi:10.1109/tevc.2019.2954411 fatcat:v72p6dsrvffmvimb3ajeifxskm

Challenges of evolvable hardware: past, present and the path to a promising future

Pauline C. Haddow, Andy M. Tyrrell
2011 Genetic Programming and Evolvable Machines  
EH thus started off as a new and exciting field with much promise.  ...  Evolvable Hardware (EH) is a field of evolutionary computation (EC) that focuses on the embodiment of evolution in a physical media.  ...  A further approach suggested by Stepney is that evolutionary techniques may be applied, not only to achieving functionality from a black box but also as a technique to identify such computational characteristics  ... 
doi:10.1007/s10710-011-9141-6 fatcat:5jal32pzizc2pclgoqggchuiz4

Energy Landscapes of Atomic Clusters as Black Box Optimization Benchmarks

C. L. Müller, I. F. Sbalzarini
2012 Evolutionary Computation  
We present the energy minimization of atomic clusters as a promising problem class for continuous black box optimization benchmarks.  ...  We hence suggest that the presented problem instances should be included in black box optimization benchmark suites.  ...  We expect that confirming or improving the currently known putatively optimal finite sphere packings is a formidable challenge for black box optimization methods.  ... 
doi:10.1162/evco_a_00086 pmid:22779442 fatcat:2w37ru3e2baozijiljtxknstqu

A survey of structural and multidisciplinary continuum topology optimization: post 2000

Joshua D. Deaton, Ramana V. Grandhi
2013 Structural And Multidisciplinary Optimization  
Topology optimization is the process of determining the optimal layout of material and connectivity inside a design domain.  ...  Evolutionary Structural Optimization (ESO), (3) boundary variation methods (level set and phase field), and (4) a new biologically inspired method based on cellular division rules.  ...  The views and conclusions contained herein are those of the authors and should not be interpreted as representing official policies or endorsements, either expressed or implied, of the Air Force Research  ... 
doi:10.1007/s00158-013-0956-z fatcat:ew4iik4z7zepzf376hxbxnruyy

Complexity Theory for Discrete Black-Box Optimization Heuristics [article]

Carola Doerr
2018 arXiv   pre-print
A predominant topic in the theory of evolutionary algorithms and, more generally, theory of randomized black-box optimization techniques is running time analysis.  ...  of running time analysis and black-box complexity can inspire new algorithmic solutions to well-researched problems in evolutionary computation.  ...  , operations research, and their interactions with data sciences.  ... 
arXiv:1801.02037v2 fatcat:icvhcv2svvaexaq3kno6xgrmta

An Optimization Algorithm Employing Multiple Metamodels and Optimizers

Yoel Tenne
2013 International Journal of Automation and Computing  
Modern engineering design optimization often relies on computer simulations to evaluate candidate designs, a setup which results in expensive black-box optimization problems.  ...  However, although a variety of metamodels and optimizers have been proposed, the optimal types to employ are problem dependant.  ...  Fig. 1 1 The layout of an expensive black-box optimization problem Fig. 2 2 The layout of an optimization iteration of the proposed algorithm functions × 10 repetitions per setting).  ... 
doi:10.1007/s11633-013-0716-y fatcat:yadgef54i5e75b4ygy7m3tofs4

A joint reflectometry-optimization algorithm for mapping the topology of an unknown wire network

Moussa Kafal, Jaume Benoit, Christophe Layer
2017 2017 IEEE SENSORS  
A joint reflectometry-optimization algorithm for mapping the topology of an unknown wire network.  ...  In this paper, we propose a nondestructive testing approach based on the tenets of reflectometry methods and genetic algorithms to retrieve the topology and load impedances of unknown embedded complex  ...  CONCLUSION In this paper, we have proposed a non-destructive testing approach, the TDR-GA methodology, which is based on the tenets of TDR and genetic algorithms for retrieving the topology of a black-boxed  ... 
doi:10.1109/icsens.2017.8234208 fatcat:o4ercmtbnngftbxfn6k4shtpca

Beyond black-box optimization: a review of selective pressures for evolutionary robotics

Stephane Doncieux, Jean-Baptiste Mouret
2014 Evolutionary Intelligence  
When considering evolutionary robotics as black-box optimization, the selective pressure is mainly driven by a user-defined, black-box fitness function, and a domain-independent selection procedure.  ...  However, most evolutionary robotics experiments face similar challenges in similar setups: the selective pressure, and, in particular, the fitness function, is not a pure user-defined black box.  ...  Fortunately, evolutionary robotics is not black-box optimization: most experiments have both common challenges and similar setups.  ... 
doi:10.1007/s12065-014-0110-x fatcat:zev64dia3vcszgefpujd4xxgzi

Policy Optimization by Genetic Distillation [article]

Tanmay Gangwani, Jian Peng
2018 arXiv   pre-print
Inspired by natural selection, operators, including mutation, crossover and selection, provide effective heuristics for search and black-box optimization.  ...  Here, we present Genetic Policy Optimization (GPO), a new genetic algorithm for sample-efficient deep policy optimization.  ...  Recently, Salimans et al. (2017) proposed a version of Evolution Strategies (ES) for black-box policy optimization.  ... 
arXiv:1711.01012v2 fatcat:d3rvfngimzbozkbb4ykqe3r274

Finding an Optimal Team

Michał Okulewicz
2016 Position Papers of the 2016 Federated Conference on Computer Science and Information Systems  
The quality of the team is assessed in a black-box optimization environment, where the optimized function acts as a metaphor of the project to be completed within the certain time limit (number of fitness  ...  The employees in a team are modeled according to the Belbin's Team Roles and the Particle Swarm Optimization (PSO) is used as a teamwork framework algorithm, while Evolutionary Algorithm (EA) as an algorithm  ...  The quality of the team is assessed in a black-box optimization environment, where the optimized function acts as a metaphor of the project to be completed within the certain time limit (number of fitness  ... 
doi:10.15439/2016f465 dblp:conf/fedcsis/Okulewicz16 fatcat:rman6n6f7bekdk3n3oix6zkunq

A Comparative Study of PSO and CMA-ES Algorithms on Black-box Optimization Benchmarks

Paweł Szynkiewicz
2018 Journal of Telecommunications and Information Technology  
Selection and tuning of the appropriate optimization solver for a particular task can be challenging and requires expert knowledge of the methods to be considered.  ...  COCO (COmparing Continuous Optimizers) -a platform for systematic and sound comparisons of real-parameter global optimization solvers was used to evaluate the performance of CMA-ES and PSO methods.  ...  Acknowledgments The work has been performed as part of the CYBERSE-CIDENT/369195/I/NCBR/2017 project, co-financed by the National Centre for Research and Development, under the CyberSecIdent Program.  ... 
doi:10.26636/jtit.2018.127418 fatcat:sfnn3pbgjffjvmdeezqtctbjam

OPT-GAN: A Broad-Spectrum Global Optimizer for Black-box Problems by Learning Distribution [article]

Minfang Lu, Shuai Ning, Shuangrong Liu, Fengyang Sun, Bo Zhang, Bo Yang, Lin Wang
2022 arXiv   pre-print
Black-box optimization (BBO) algorithms are concerned with finding the best solutions for problems with missing analytical details.  ...  Experiments on diverse BBO benchmarks and a high dimensional real world application exhibit that OPT-GAN outperforms other traditional and neural net-based BBO algorithms.  ...  Optimization How do we use OPT-GAN to optimize a black-box problem?  ... 
arXiv:2102.03888v5 fatcat:jasjmzqjkbhdzgi5zk5qmd2doy

Deep Neural Architecture Search with Deep Graph Bayesian Optimization [article]

Lizheng Ma, Jiaxu Cui, Bo Yang
2019 arXiv   pre-print
black-box objectives and their uncertainty.  ...  Bayesian optimization (BO) is an effective method of finding the global optima of black-box functions.  ...  Bayesian optimization (BO) is an effective global optimization algorithm, with the goal of finding the optima of black-box objectives.  ... 
arXiv:1905.06159v1 fatcat:fb7capt2mrbaflf3ze2tqampwi

A new taxonomy of global optimization algorithms

Jörg Stork, A. E. Eiben, Thomas Bartz-Beielstein
2020 Natural Computing  
AbstractSurrogate-based optimization, nature-inspired metaheuristics, and hybrid combinations have become state of the art in algorithm design for solving real-world optimization problems.  ...  This article presents a taxonomy of the field, which explores and matches algorithm strategies by extracting similarities and differences in their search strategies.  ...  For the automatic algorithm selection, numerous operators influence the convergence behavior, and the search strategy itself becomes a black-box that is challenging to comprehend.  ... 
doi:10.1007/s11047-020-09820-4 fatcat:dparw6nuzfcypjepqelwk7wnue

Evolutionary Structural Optimization Method [chapter]

2010 Evolutionary Topology Optimization of Continuum Structures  
The search for a general method capable of performing simultaneous shape and topology optimization has been a great challenge.  ...  This problem has previously been solved by several researchers as one of the most challenging problems in topology optimization, e,g, Olhoff et al (1991) , Rozvany and Zhou (1991) and Zhou and Rozvany  ...  The proposed method is capable of performing simultaneous shape and topology optimization.  ... 
doi:10.1002/9780470689486.ch2 fatcat:nkq3x62kkjfa7g57s7nujw5pgu
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