A Survey of Hyper-heuristics for Dynamic Optimization Problems
暂无分享,去创建一个
Bernabé Dorronsoro | Nelson Rangel-Valdez | Claudia Gómez Santillán | Laura Cruz Reyes | Teodoro Eduardo Macias-Escobar
[1] A. Sima Etaner-Uyar,et al. An Investigation of Selection Hyper-heuristics in Dynamic Environments , 2011, EvoApplications.
[2] Edmund K. Burke,et al. A methodology for determining an effective subset of heuristics in selection hyper-heuristics , 2017, Eur. J. Oper. Res..
[3] Andrew W. Moore,et al. Reinforcement Learning: A Survey , 1996, J. Artif. Intell. Res..
[4] Graham Kendall,et al. Automatic Design of a Hyper-Heuristic Framework With Gene Expression Programming for Combinatorial Optimization Problems , 2015, IEEE Transactions on Evolutionary Computation.
[5] Haluk Topcuoglu,et al. A hyper-heuristic based framework for dynamic optimization problems , 2014, Appl. Soft Comput..
[6] Ender Özcan,et al. An Experimental Study on Hyper-heuristics and Exam Timetabling , 2006, PATAT.
[7] Andries Petrus Engelbrecht,et al. Analysis of hyper-heuristic performance in different dynamic environments , 2014, 2014 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments (CIDUE).
[8] Jürgen Branke,et al. Memory enhanced evolutionary algorithms for changing optimization problems , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).
[9] A. Sima Etaner-Uyar,et al. Selection hyper-heuristics in dynamic environments , 2013, J. Oper. Res. Soc..
[10] María Cristina Riff,et al. DVRP: a hard dynamic combinatorial optimisation problem tackled by an evolutionary hyper-heuristic , 2010, J. Heuristics.
[11] Edmund K. Burke,et al. A greedy hyper-heuristic in dynamic environments , 2009, GECCO '09.
[12] Graham Kendall,et al. Channel assignment in cellular communication using a great deluge hyper-heuristic , 2004, Proceedings. 2004 12th IEEE International Conference on Networks (ICON 2004) (IEEE Cat. No.04EX955).
[13] Xin Yao,et al. Population-Based Incremental Learning With Associative Memory for Dynamic Environments , 2008, IEEE Transactions on Evolutionary Computation.
[14] Graham Kendall,et al. An Investigation of Automated Planograms Using a Simulated Annealing Based Hyper-Heuristic , 2005 .
[15] Graham Kendall,et al. A Dynamic Multiarmed Bandit-Gene Expression Programming Hyper-Heuristic for Combinatorial Optimization Problems , 2015, IEEE Transactions on Cybernetics.
[16] Adil Baykasoglu,et al. Dynamic optimization in binary search spaces via weighted superposition attraction algorithm , 2018, Expert Syst. Appl..
[17] Graham Kendall,et al. A Classification of Hyper-heuristic Approaches , 2010 .
[18] Andries Petrus Engelbrecht,et al. Analysis of selection hyper-heuristics for population-based meta-heuristics in real-valued dynamic optimization , 2018, Swarm Evol. Comput..
[19] Shengxiang Yang,et al. Evolutionary dynamic optimization: A survey of the state of the art , 2012, Swarm Evol. Comput..
[20] A. Sima Etaner-Uyar,et al. A hybrid multi-population framework for dynamic environments combining online and offline learning , 2013, Soft Comput..
[21] Yi Mei,et al. Genetic programming for production scheduling: a survey with a unified framework , 2017, Complex & Intelligent Systems.
[22] A. Sima Etaner-Uyar,et al. An Ant-Based Selection Hyper-heuristic for Dynamic Environments , 2013, EvoApplications.
[23] Lawrence Davis,et al. Bit-Climbing, Representational Bias, and Test Suite Design , 1991, ICGA.
[24] Peter I. Cowling,et al. Binary Exponential Back Off for Tabu Tenure in Hyperheuristics , 2009, EvoCOP.
[25] Andrés Espinal,et al. Evolvability Metric Estimation by a Parallel Perceptron for On-Line Selection Hyper-Heuristics , 2017, IEEE Access.
[26] Lamjed Ben Said,et al. Dynamic Multi-objective Optimization Using Evolutionary Algorithms: A Survey , 2017, Recent Advances in Evolutionary Multi-objective Optimization.
[27] Shengxiang Yang,et al. A memetic algorithm with adaptive hill climbing strategy for dynamic optimization problems , 2009, Soft Comput..
[28] Michel Gendreau,et al. Hyper-heuristics: a survey of the state of the art , 2013, J. Oper. Res. Soc..
[29] Mengjie Zhang,et al. Automated Design of Production Scheduling Heuristics: A Review , 2016, IEEE Transactions on Evolutionary Computation.
[30] A. Sima Etaner-Uyar,et al. A Framework to Hybridize PBIL and a Hyper-heuristic for Dynamic Environments , 2012, PPSN.
[31] David H. Wolpert,et al. No free lunch theorems for optimization , 1997, IEEE Trans. Evol. Comput..
[32] Daniele Loiacono,et al. Simulated Car Racing Championship: Competition Software Manual , 2013, ArXiv.
[33] Xin Yao,et al. Population Evolvability: Dynamic Fitness Landscape Analysis for Population-Based Metaheuristic Algorithms , 2018, IEEE Transactions on Evolutionary Computation.
[34] Silvestre Fialho,et al. Adaptive operator selection for optimization , 2010 .
[35] Berna Kiraz,et al. Hyper-heuristic approaches for the dynamic generalized assignment problem , 2010, 2010 10th International Conference on Intelligent Systems Design and Applications.
[36] Berkay Beygo,et al. A Hyperheuristic Approach for Dynamic Multilevel Capacitated Lot Sizing with Linked Lot Sizes for APS implementations , 2017 .
[37] Adil Baykasoglu,et al. Evolutionary and population-based methods versus constructive search strategies in dynamic combinatorial optimization , 2017, Inf. Sci..
[38] Graham Kendall,et al. A Hyperheuristic Approach to Scheduling a Sales Summit , 2000, PATAT.
[39] Andries Petrus Engelbrecht,et al. Alternative hyper-heuristic strategies for multi-method global optimization , 2010, IEEE Congress on Evolutionary Computation.
[40] A. Sima Etaner-Uyar,et al. Heuristics for car setup optimisation in TORCS , 2012, 2012 12th UK Workshop on Computational Intelligence (UKCI).
[41] Graham Kendall,et al. A Monte Carlo Hyper-Heuristic To Optimise Component Placement Sequencing For Multi Head Placement Machine , 2003 .
[42] Andries Petrus Engelbrecht,et al. Analysis of global information sharing in hyper-heuristics for different dynamic environments , 2015, 2015 IEEE Congress on Evolutionary Computation (CEC).
[43] Graham Kendall,et al. A simulated annealing hyper-heuristic methodology for flexible decision support , 2012, 4OR.
[44] Kalyanmoy Deb,et al. Dynamic Multi-objective Optimization and Decision-Making Using Modified NSGA-II: A Case Study on Hydro-thermal Power Scheduling , 2007, EMO.
[45] A. Sima Etaner-Uyar,et al. Heuristic selection in a multi-phase hybrid approach for dynamic environments , 2012, 2012 12th UK Workshop on Computational Intelligence (UKCI).
[46] Xin Yao,et al. Experimental study on population-based incremental learning algorithms for dynamic optimization problems , 2005, Soft Comput..
[47] Thomas Stützle,et al. Ant Colony Optimization , 2009, EMO.
[48] Fiona A. C. Polack,et al. Dynamic optimisation of preventative and corrective maintenance schedules for a large scale urban drainage system , 2017, Eur. J. Oper. Res..