Parameter setting in evolutionary algorithms.
From MaRDI portal
Publication:870736
DOI10.1007/978-3-540-69432-8zbMath1139.68047OpenAlexW1543258308MaRDI QIDQ870736
No author found.
Publication date: 14 March 2007
Published in: Studies in Computational Intelligence (Search for Journal in Brave)
Full work available at URL: https://hal.inria.fr/inria-00140549/file/param-final.pdf
Nonnumerical algorithms (68W05) Learning and adaptive systems in artificial intelligence (68T05) Proceedings, conferences, collections, etc. pertaining to computer science (68-06) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)
Related Items (29)
ParadisEO-MO: from fitness landscape analysis to efficient local search algorithms ⋮ Reverse assignment: calibrating link cost functions and updating demand from traffic counts and time measurements ⋮ A comparative study on recently-introduced nature-based global optimization methods in complex mechanical system design ⋮ Generalized Nets as a Tool for the Modelling of Data Mining Processes ⋮ Parameter-less algorithm for evolutionary-based optimization: for continuous and combinatorial problems ⋮ Autonomous operator management for evolutionary algorithms ⋮ A double-loop hybrid algorithm for the traveling salesman problem with arbitrary neighbourhoods ⋮ Predictive modeling in a steelmaking process using optimized relevance vector regression and support vector regression ⋮ Improving complex SMT strategies with learning ⋮ A matheuristic algorithm for the pollution and energy minimization traveling salesman problems ⋮ Statistical design of genetic algorithms for combinatorial optimization problems ⋮ A new taxonomy of global optimization algorithms ⋮ New Ways to Calibrate Evolutionary Algorithms ⋮ \( \delta\)MOEA/D-AWACD: improving constant-distance-based MOEA/D-AWA using a step function parameter control mechanism ⋮ Self-adjusting population sizes for non-elitist evolutionary algorithms: why success rates matter ⋮ Analyzing bandit-based adaptive operator selection mechanisms ⋮ Filled function method for nonlinear model predictive control ⋮ A survey on optimization metaheuristics ⋮ Tuning Algorithms for Stochastic Black-Box Optimization: State of the Art and Future Perspectives ⋮ A novel hybrid PSO-based metaheuristic for costly portfolio selection problems ⋮ Relevance vector machine with tuning based on self-adaptive differential evolution approach for predictive modelling of a chemical process ⋮ Analysing the Robustness of Multiobjectivisation Approaches Applied to Large Scale Optimisation Problems ⋮ A hybrid breakout local search and reinforcement learning approach to the vertex separator problem ⋮ A divide and conquer method for learning large fuzzy cognitive maps ⋮ The use of explicit building blocks in evolutionary computation ⋮ Association rule mining through adaptive parameter control in particle swarm optimization ⋮ Review of utilization of genetic algorithms in heat transfer problems ⋮ Performance analysis of the simultaneous perturbation stochastic approximation algorithm on the noisy sphere model ⋮ Ambulance routing in disaster response considering variable patient condition: NSGA-II and MOPSO algorithms
This page was built for publication: Parameter setting in evolutionary algorithms.
