###### computation

- In artificial intelligence , an evolutionary algorithm ( EA ) is a subset of evolutionary computation , a generic population-based metaheuristic optimization algorithm . (wikipedia.org)
- Adaptive and Self-Adaptive Evolutionary Computation. (springer.com)
- 1997). Handbook of Evolutionary Computation . (springer.com)
- EAs are one kind of evolutionary computation and differ from genetic algorithms . (foldoc.org)
- This self-contained reference is invaluable to students, researchers and in particular to computer scientists, operational research scientists and engineers working in evolutionary computation, genetic algorithms and artificial intelligence. (springer.com)
- Our system follows an approach based on interactive evolutionary computation. (springer.com)
- Evolutionary computation is an old field of computer science that started in the end of the 1960s nearly simultaneously in different parts of the world. (igi-global.com)
- DEAP is a novel evolutionary computation framework for rapid prototyping and testing of ideas. (github.com)
- The field of Evolutionary Computation has developed significantly over the past 30 years and today consists a variety of subfields such as genetic algorithms, evolution strate- gies, evolutionary programming, and genetic programming, each with their own algorithmic perspectives and goals. (springer.com)
- A. E. Smith, "Swarm intelligence: from natural to artificial systems [book reviews]," IEEE Transactions on Evolutionary Computation , vol. 4, no. 2, pp. 192-193, 2000. (hindawi.com)
- Y. Pehlivanoglu, "A new particle swarm optimization method enhanced with a periodic mutation strategy and neural networks," IEEE Transactions on Evolutionary Computation , vol. 17, no. 3, pp. 436-452, 2012. (hindawi.com)
- Particle swarm optimization with an aging leader and challengers," IEEE Transactions on Evolutionary Computation , vol. 17, no. 2, pp. 241-258, 2012. (hindawi.com)
- EASEA is a framework designed to help non-expert programmers to optimize their problems by evolutionary computation. (springer.com)
- No. XVI in genetic and evolutionary computation. (springer.com)
- In: Proceedings of the 9th annual genetic and evolutionary computation conference (GECCO). (springer.com)
- De Jong K (2008) Evolutionary computation: a unified approach. (springer.com)

###### multi-objective optimization

- Faster Evolutionary Multi-Objective Optimization via GALE, the Geometric Active Learner. (springer.com)
- Deb K (2001) Multi-objective Optimization using Evolutionary Algorithm. (springer.com)

###### Genetic Algorithm Optimization

- Chen L (2003) Real Coded Genetic Algorithm Optimization of Long Term Reservoir Operation. (springer.com)

###### optimization algorithm

- This study also shows that the chaos algorithm has enriched the search of general optimization algorithm and thus may be used for optimizing complex non-linear water resources systems. (springer.com)
- Han F, Lu QS (2008) An improved chaos optimization algorithm and its application in the economic load dispatch problem. (springer.com)
- Achievable speedups are also shown onto different NVIDIA GPGPUs cards for different optimization algorithm families. (springer.com)

###### Approaches

- Please note that there are different approaches for the implementation of evolutionary algorithms. (kdnuggets.com)
- In this paper, we provide a systematic comparison of various evolutionary approaches to multiobjective optimization using six carefully chosen test functions. (psu.edu)

###### evolution

- Techniques from evolutionary algorithms applied to the modeling of biological evolution are generally limited to explorations of microevolutionary processes and planning models based upon cellular processes. (wikipedia.org)
- Evolutionary algorithms is a class of randomized heuristics inspired by natural evolution. (springer.com)
- After testing different algorithm variants we conclude that the best option is an asexual EA using order-based representation and an adaptation mechanism that periodically changes the fitness function during the evolution. (springer.com)
- Evolutionary algorithm is a generic optimization technique mimicking the ideas of natural evolution. (kdnuggets.com)
- One of the greatest achievements of the science of evolution is the evolutionary algorithm. (thespoof.com)
- In the present study, the chaos algorithm is coupled with evolutionary optimization algorithms such as genetic algorithm (GA) and differential evolution (DE) algorithm for generating the initial population and applied for maximizing the hydropower production from a reservoir. (springer.com)
- The results are then compared with conventional genetic algorithm and differential evolution algorithm. (springer.com)
- The results show that the chaotic differential evolution (CDE) algorithm performs better than other techniques in terms of total annual power production. (springer.com)
- Adeyemo J, Otieno F (2010) Differential evolution algorithm for solving multi-objective crop planning model. (springer.com)

###### Heuristics

- In this book the author provides an introduction to the methods used to analyze evolutionary algorithms and other randomized search heuristics. (springer.com)
- 1996). "Problem Structure Heuristics and Scaling Behavior for Genetic Algorithms," Artificial Intelligence 81, 327-347. (springer.com)

###### Particle Swarm Optimi

- Y. Rahmat-Samii, "Genetic algorithm (ga) and particle swarm optimization (pso) in engineering electromagnetics," in Proceedings of the 17th International Conference on Applied Electromagnetics and Communications (ICECom '03) , pp. 1-5, 2003. (hindawi.com)

###### Multiobjective Optimization

- The reader is introduced to a range of applications, as Introduction to Evolutionary Algorithms demonstrates how to model real world problems, how to encode and decode individuals, and how to design effective search operators according to the chromosome structures with examples of constraint optimization, multiobjective optimization, combinatorial optimization, and supervised/unsupervised learning. (springer.com)

###### researchers

- So the book is a useful reference for both graduate students and researchers engaged with the theoretical analysis of such algorithms. (springer.com)
- Spanish researchers are employing evolutionary algorithms to find solutions to complex scientific and engineering problems. (hpcwire.com)
- The book will be useful for researchers and practitioners in the area of computational intelligence, particularly those engaged with heuristic search, multimodal optimization, evolutionary computing, and experimental analysis. (springer.com)
- Evolutionary Algorithms in VLSI CAD is intended for CAD developers and researchers as well as those working in evolutionary algorithms and techniques supporting modern design tools and processes. (bookdepository.com)
- Willard Miller, Jr., Professor and Director v PREFACE The IMA Workshop on Evolutionary Algorithms brought together many of the top researchers working in the area of Evolutionary Com- putation for a week of intensive interaction. (springer.com)
- SBSE researchers often use an evolutionary algorithm to solve various software engineering problems. (springer.com)

###### global optimization

- This book offers the first comprehensive taxonomy for multimodal optimization algorithms, work with its root in topics such as niching, parallel evolutionary algorithms, and global optimization. (springer.com)
- I'm writing an e-book about global optimization, including topics like evolutionary algorithms, genetic algorithms, and genetic programming. (perlmonks.org)

###### 2002

- Alba E, Tomassini M (2002) Parallelism and evolutionary algorithms. (springer.com)

###### Keywords

- This process is experimental and the keywords may be updated as the learning algorithm improves. (springer.com)

###### Elitist

- Elitist algorithms make sure that the best individuals are not discarded, by transferring them directly into the next generation. (igi-global.com)

###### computational

- Furthermore, it scales up better with the problem size than the other two algorithms and indicates a linear computational complexity. (springer.com)

###### Estimation

- The estimation methodology involves evolutionary algorithms using artificial neural network (ANN) and genetic algorithm (GA). The ANN is used to map the relationship of tumor parameters (depth, size, and heat generation) to the temperature profile over the idealized breast model. (hindawi.com)

###### randomly generated

- An evolutionary algorithm maintains a population of structures (usually randomly generated initially), that evolves according to rules of selection, recombination, mutation and survival, referred to as genetic operators. (foldoc.org)
- The results of the evolutionary algorithm mainly depend on the randomly generated initial population that is arrived based on the probabilistic theory. (springer.com)

###### mainly

- Each test function involves a particular feature that is known to cause difficulty in the evolutionary optimization process, mainly in converging to the Pareto-optimal front (e.g., multimodality and deception). (psu.edu)

###### processes

- His work consolidates the recent successes in this domain, presenting and explaining use cases, algorithms, and performance measures, with a focus throughout on the goals of the optimization processes and a deep understanding of the algorithms used. (springer.com)

###### data structures

- It seeks to make algorithms explicit and data structures transparent. (github.com)

###### Convergence

- The second is the code method should speeds up the convergence speed of the algorithm search. (techrepublic.com)

###### experimental

- This paper presents the results of an experimental investigation on solving graph coloring problems with Evolutionary Algorithms (EAs). (springer.com)
- However, in contrast to what was suspected beforehand, the experimental results indicate a hierarchy of the algorithms under consideration. (psu.edu)

###### Search

- Finally, elitism is shown to be an important factor for improving evolutionary multiobjective search. (psu.edu)
- Memetic Algorithm (MA) is an Evolutionary Algorithm that includes one or more local search phases within its evolutionary cycle to obtain the minimum wirelength by reducing delay in partitioning and by reducing area in floorplanning. (hindawi.com)
- The algorithm combines a hierarchical design technique like genetic algorithm and constructive technique like Simulated Annealing for local search to solve VLSI partitioning and floorplanning problem. (hindawi.com)
- Goldberg DE (1989) Genetic Algorithms in Search, Optimization and Machine Learning. (springer.com)
- Krüger F, Maitre O, Jiménez S, Baumes L, Collet P (2010) Speedups between ×70 and ×120 for a generic local search (memetic) algorithm on a single GPGPU chip. (springer.com)

###### Proceedings

- 1991). Proceedings of the 4th International Conference on Genetic Algorithms . (springer.com)
- An O . n 0.4/-Approximation Algorithm for 3-Coloring (and Improved Approximation Algorithms for k -Coloring)," Proceedings of the 21st ACM Symposium on Theory of Computing . (springer.com)
- This IMA Volume in Mathematics and its Applications EVOLUTIONARY ALGORITHMS is based on the proceedings of a workshop that was an integral part of the 1996-97 IMA program on "MATHEMATICS IN HIGH-PERFORMANCE COMPUTING. (springer.com)

###### visualization

- Generating random graphs with particular characteristics is crucial for evaluating graph algorithms, layouts and visualization techniques. (springer.com)
- Faloutsos, C., Lin, K.-I. FastMap: a fast algorithm for indexing, data-mining and visualization of traditional and multimedia datasets. (springer.com)

###### Adaptive

- We compare this adaptive EA to a powerful traditional graph coloring technique DSatur and the Grouping Genetic Algorithm (GGA) on a wide range of problem instances with different size, topology and edge density. (springer.com)
- In this paper we just made a study on the various classical problem solving using the evolutionary algorithms and various methodologies for adaptive population models and sizing methodologies. (bartleby.com)

###### neural

- Gruau, F.: Neural Network Synthesis using Cellular Encoding and Genetic Algorithms. (springer.com)
- I do a lot of work with genetic algorithms and neural nets and it would be interesting to be able to easily output your results on a 3D contour map of the problem space. (perlmonks.org)

###### parallel

- Li JM, Wang XJ, He RS, Chi ZX (2007) An efficient fine-grained parallel genetic algorithm based on GPU-accelerated. (springer.com)

###### economics

- Evolutionary algorithms are becoming increasingly attractive across various disciplines, such as operations research, computer science, industrial engineering, electrical engineering, social science and economics. (springer.com)

###### problems

- Evolutionary algorithms often perform well approximating solutions to all types of problems because they ideally do not make any assumption about the underlying fitness landscape . (wikipedia.org)
- This textbook is the second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, significantly augmented with contemporary knowledge and adapted for the classroom. (springer.com)
- It combines existing and emerging tools to design, simulate, evaluate, and deploy solutions for complex, real-world problems using evolutionary algorithms on the example of swarms of unmanned aerial vehicles (UAVs). (springer.com)
- In this paper, EASEA is presented by its underlying algorithms and by some example problems. (springer.com)

###### Computing

- Fok KL, Wong TT, Wong ML (2007) Evolutionary computing on consumer graphics hardware. (springer.com)

###### graph

- In this paper we describe the graph generation process from a user's perspective, provide details about our evolutionary algorithm, and demonstrate how GraphCuisine is employed to generate graphs that mimic a given real-world network. (springer.com)

###### mutation

- Unlike evolutionary algorithms, SWAY does not use mutation or cross-over or multi-generational reasoning to find interesting subspaces but relies on the underlying dimensions of the solution space. (springer.com)

###### Framework

- FREVO - Framework for evolutionary design. (springer.com)

###### Basic Concepts

- Evolutionary Algorithms in VLSI CAD presents the basic concepts of EAs, and considers the application of EAs in VLSI CAD. (bookdepository.com)

###### Introduction

- Introduction to Evolutionary Algorithms presents an insightful, comprehensive, and up-to-date treatment of evolutionary algorithms. (springer.com)
- Introduction to Evolutionary Algorithms is intended as a textbook or self-study material for both advanced undergraduates and graduate students. (springer.com)

###### Abstract

- A Survey on Data Mining Classification Algorithms Abstract: Classification is one of the most familiar data mining technique and model finding process that is used for transmission the data into different classes according to particular condition. (bartleby.com)

###### theoretical

- By adopting a complexity-theoretical perspective, he derives general limitations for black-box optimization, yielding lower bounds on the performance of evolutionary algorithms, and then develops general methods for deriving upper and lower bounds step by step. (springer.com)

###### consists

- Evolutionary Algorithms in VLSI CAD consists of two parts. (bookdepository.com)

###### parameters

- Evolutionary programming - Similar to genetic programming, but the structure of the program is fixed and its numerical parameters are allowed to evolve. (wikipedia.org)

###### problem

- therefore, there may be no direct link between algorithm complexity and problem complexity. (wikipedia.org)
- For the evolutionary algorithm, the representation of the electronic circuit has two methods, one kind is code with the electronic circuit solution space, and the other is code with the problem space. (techrepublic.com)
- In fact, one major problem in evolutionary biology and phylogenetics is the near-impossibility of defining the distance between two different phylogenetic trees mathematically. (perlmonks.org)
- The following code gives a quick overview how simple it is to implement the Onemax problem optimization with genetic algorithm using DEAP. (github.com)

###### different

- They are applied in many different contexts, in particular in optimization, and analysis of such algorithms has seen tremendous advances in recent years. (springer.com)

###### Analysis

- 1992). "A Formal Analysis of the Role of Multi-point Crossover in Genetic Algorithms," Annals of Mathematics and Artificial Intelligence 5, 1-26. (springer.com)

###### solutions

- Combinatoric and real-valued function optimisation in which the optimisation surface or fitness landscape is "rugged", possessing many locally optimal solutions, are well suited for evolutionary algorithms. (foldoc.org)

###### various

- All the various features of multi-objective evolutionary algorithms (MOEAs) are presented in an innovative and student-friendly fashion, incorporating state-of-the-art research results. (springer.com)
- This various constraints given the way to lead the concept of using the evolutionary algorithms. (bartleby.com)

###### design

- He starts with an algorithmic and modular perspective and gives guidelines for the design of evolutionary algorithms. (springer.com)
- In Evolutionary and biologically inspired music, sound, art and design (Lecture notes in computer science, Vol. 7247, pp. 108-116). (springer.com)

###### Rule

- Chang FJ, Chen L (1998) Real-coded genetic algorithm for rule-based flood control reservoir management. (springer.com)
- Chang FJ, Chen L, Chang L (2005) Optimizing the reservoir operating rule curves by genetic algorithms. (springer.com)

###### generic

- This resulted in strong trends that still survive, even though it is now possible to outline a generic structure for an evolutionary algorithm that is described in this chapter. (igi-global.com)

###### performance

- Robustness versus performance in sorting and tournament algorithms. (springer.com)
- R. Salomon, "Re-evaluating genetic algorithm performance under coordinate rotation of benchmark functions. (hindawi.com)

###### Work

- How do Evolutionary Algorithms Work? (kdnuggets.com)