Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
An introduction to genetic algorithms
An introduction to genetic algorithms
Fitness inheritance in genetic algorithms
SAC '95 Proceedings of the 1995 ACM symposium on Applied computing
Intelligence through simulated evolution: forty years of evolutionary programming
Intelligence through simulated evolution: forty years of evolutionary programming
Swarm intelligence
Efficient and Accurate Parallel Genetic Algorithms
Efficient and Accurate Parallel Genetic Algorithms
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Evolution strategies –A comprehensive introduction
Natural Computing: an international journal
Journal of Global Optimization
Genetic Search with Approximate Function Evaluation
Proceedings of the 1st International Conference on Genetic Algorithms
Genetic Programming for Financial Time Series Prediction
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
Measuring ISP topologies with rocketfuel
IEEE/ACM Transactions on Networking (TON)
Ant Colony Optimization
FMGA: Finding Motifs by Genetic Algorithm
BIBE '04 Proceedings of the 4th IEEE Symposium on Bioinformatics and Bioengineering
A comprehensive survey of fitness approximation in evolutionary computation
Soft Computing - A Fusion of Foundations, Methodologies and Applications
DE/EDA: a new evolutionary algorithm for global optimization
Information Sciences—Informatics and Computer Science: An International Journal
The encoding complexity of network coding
IEEE/ACM Transactions on Networking (TON) - Special issue on networking and information theory
Minimum-cost multicast over coded packet networks
IEEE/ACM Transactions on Networking (TON) - Special issue on networking and information theory
Loopy Substructural Local Search for the Bayesian Optimization Algorithm
SLS '09 Proceedings of the Second International Workshop on Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics
Analyzing probabilistic models in hierarchical BOA
IEEE Transactions on Evolutionary Computation - Special issue on evolutionary algorithms based on probabilistic models
Information Sciences: an International Journal
Entropy-based substructural local search for the bayesian optimization algorithm
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Differential evolution in constrained numerical optimization: An empirical study
Information Sciences: an International Journal
Entropy-based evaluation relaxation strategy for Bayesian optimization algorithm
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part II
Estimation of particle swarm distribution algorithms: Combining the benefits of PSO and EDAs
Information Sciences: an International Journal
A circuit representation technique for automated circuit design
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Information Theory
Information flow decomposition for network coding
IEEE Transactions on Information Theory
Information Sciences: an International Journal
Information Sciences: an International Journal
A Boltzmann based estimation of distribution algorithm
Information Sciences: an International Journal
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This paper introduces the notion of an entropy measurement for populations of candidate solutions in evolutionary algorithms, developing both conditional and joint entropy-based algorithms. We describe the inherent characteristics of the entropy measurement and how these affect the search process. Following these discussions, we develop a recognition mechanism through which promising candidate solutions can be identified without the need of invoking costly evaluation functions. This on-demand evaluation strategy (ODES) is able to perform decision making tasks regardless of whether the actual fitness evaluation is necessary or not, making it an ideal efficiency enhancement technique for accelerating the computational process of evolutionary algorithms. Two different evolutionary algorithms, a traditional genetic algorithm and a multivariate estimation of distribution algorithm, are employed as example targets for the application of our on-demand evaluation strategy. Ultimately, experimental results confirm that our method is able to broadly improve the performance of various population-based global searchers.