Evolutionary Constrained Optimization

Langbeschreibung
This book makes available a self-contained collection of modern research addressing the general constrained optimization problems using evolutionary algorithms. Broadly the topics covered include constraint handling for single and multi-objective optimizations; penalty function based methodology; multi-objective based methodology; new constraint handling mechanism; hybrid methodology; scaling issues in constrained optimization; design of scalable test problems; parameter adaptation in constrained optimization; handling of integer, discrete and mix variables in addition to continuous variables; application of constraint handling techniques to real-world problems; and constrained optimization in dynamic environment. There is also a separate chapter on hybrid optimization, which is gaining lots of popularity nowadays due to its capability of bridging the gap between evolutionary and classical optimization. The material in the book is useful to researchers, novice, and experts alike. The book will also be useful for classroom teaching and future research.
Hauptbeschreibung
Self-contained collection of current research addressing the general constrained optimization problems
Inhaltsverzeichnis
A Critical Review of Adaptive Penalty Techniques in Evolutionary Computation.- Ruggedness Quantifying for Constrained Continuous Fitness Landscapes.- Trust Regions in Surrogate-Assisted Evolutionary Programming for Constrained Expensive Black-Box Optimization.- Ephemeral Resource Constraints in Optimization.- Incremental Approximation Models for Constrained Evolutionary Optimization.- Efficient Constrained Optimization by the ¿ Constrained Differential Evolution with Rough Approximation.- Analyzing the Behaviour of Multi-Recombinative Evolution Strategies Applied to a Conically Constrained Problem.- Locating Potentially Disjoint Feasible Regions of a Search Space with a Particle Swarm Optimizer.- Ensemble of Constraint Handling Techniques for Single Objective Constrained Optimization.- Evolutionary Constrained Optimization: A Hybrid Approach.
Rituparna Datta is a postdoctoral research fellow with the Robot Intelligence Technology (RIT) Laboratory at the Korea Advanced Institute of Science and Technology (KAIST). He earned his PhD in Mechanical Engineering at Indian Institute of Technology (IIT) Kanpur and thereafter worked as a Project Scientist in the Smart Materials, Structures, and Systems Lab at IIT Kanpur. His current research work involves investigation of Evolutionary Algorithms-based approaches to constrained optimization, applying multi-objective optimization in engineering design problems, memetic algorithms, derivative-free optimization, and robotics. He is a member of ACM, IEEE, and IEEE Computational Intelligence Society. He has been invited to deliver lectures in several institutes and universities across the globe, including at the Trinity College Dublin (TCD), Delft University of Technology (TUDELFT), University of Western Australia (UWA), University of Minho, Portugal, University of Nova de Lisboa, Portugal, University of Coimbra, Portugal, and IIT Kanpur, India. He is a regular reviewer of IEEE Transactions on Evolutionary Computation, Journal of Applied Soft Computing, Journal of Engineering Optimization, Journal of The Franklin Institute, and International Journal of Computer Systems in Science and Engineering, and was in the program committee of Genetic and Evolutionary Computation Conference (GECCO 2014), iNaCoMM2013, GECCO 2013, GECCO 2012, GECCO 2011, eighth international conference on Simulated Evolution And Learning (SEAL 2010), international conference on molecules to materials (ICMM-06), and some Indian conferences.  He has also chaired session in ACODS 2014 and UKIERI Workshop on Structural Health Monitoring 2012, GECCO 2011, IICAI 2011 to name a few. He was awarded an international travel grant (Young Scientist), from Department of Science and Technology, Govt. of India, in July 2011 and June 2012 and travel grants from Queensland University, Australia, June 2012, GECCO Student Travel Grant, ACM, New York.
ISBN-13:
9788132221838
Veröffentl:
2014
Erscheinungsdatum:
30.12.2014
Seiten:
336
Autor:
Kalyanmoy Deb
Gewicht:
670 g
Format:
241x160x24 mm
Serie:
Infosys Science Foundation Series in Applied Sciences and Engineering
Sprache:
Englisch

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