A rigorous runtime analysis of the 2-MMASib on jump functions: ant colony optimizers can cope well with local optima
暂无分享,去创建一个
[1] Frank Neumann,et al. Bioinspired computation in combinatorial optimization: algorithms and their computational complexity , 2010, GECCO '12.
[2] Andrew M. Sutton,et al. On the runtime dynamics of the compact genetic algorithm on jump functions , 2018, GECCO.
[3] Benjamin Doerr,et al. Fast genetic algorithms , 2017, GECCO.
[4] Per Kristian Lehre,et al. Concentrated Hitting Times of Randomized Search Heuristics with Variable Drift , 2014, ISAAC.
[5] Xiequan Fan,et al. Exponential inequalities for martingales with applications , 2013, 1311.6273.
[6] Per Kristian Lehre,et al. On the limitations of the univariate marginal distribution algorithm to deception and where bivariate EDAs might help , 2019, FOGA '19.
[7] W. Gutjahr. On the Finite-Time Dynamics of Ant Colony Optimization , 2006 .
[8] Timo Kötzing,et al. Optimizing expected path lengths with ant colony optimization using fitness proportional update , 2013, FOGA XII '13.
[9] Frank Neumann,et al. Fast Building Block Assembly by Majority Vote Crossover , 2016, GECCO.
[10] Benjamin Doerr,et al. Theoretical Analyses of Multi-Objective Evolutionary Algorithms on Multi-Modal Objectives , 2020, ArXiv.
[11] Benjamin Doerr,et al. The (1 + (λ,λ)) GA is even faster on multimodal problems , 2020, GECCO.
[12] Thomas Stützle,et al. Ant Colony Optimization: A Component-Wise Overview , 2018, Handbook of Heuristics.
[13] Carsten Witt,et al. MMAS Versus Population-Based EA on a Family of Dynamic Fitness Functions , 2014, Algorithmica.
[14] Weijie Zheng,et al. Sharp Bounds for Genetic Drift in Estimation of Distribution Algorithms , 2020, IEEE Transactions on Evolutionary Computation.
[15] Carsten Witt,et al. Stagnation Detection with Randomized Local Search , 2021, EvoCOP.
[16] Dirk Sudholt,et al. Rigorous Analyses for the Combination of Ant Colony Optimization and Local Search , 2008, ANTS Conference.
[17] Jens Jägersküpper,et al. When the Plus Strategy Outperforms the Comma Strategyand When Not , 2007, 2007 IEEE Symposium on Foundations of Computational Intelligence.
[18] Manuel López-Ibáñez,et al. Ant colony optimization , 2010, GECCO '10.
[19] Enrique Alba,et al. Ant Colony Based Algorithms for Dynamic Optimization Problems , 2013, Metaheuristics for Dynamic Optimization.
[20] Thomas Jansen,et al. On the Black-Box Complexity of Example Functions: The Real Jump Function , 2015, FOGA.
[21] Thomas Jansen,et al. On the analysis of the (1+1) evolutionary algorithm , 2002, Theor. Comput. Sci..
[22] Duc-Cuong Dang,et al. Escaping Local Optima with Diversity Mechanisms and Crossover , 2016, GECCO.
[23] W. Gutjahr,et al. Runtime Analysis of Ant Colony Optimization with Best-So-Far Reinforcement , 2008 .
[24] Dirk Sudholt,et al. On the Choice of the Update Strength in Estimation-of-Distribution Algorithms and Ant Colony Optimization , 2018, Algorithmica.
[25] Dirk Sudholt,et al. Towards a Runtime Comparison of Natural and Artificial Evolution , 2015, Algorithmica.
[26] Walter J. Gutjahr,et al. First steps to the runtime complexity analysis of ant colony optimization , 2008, Comput. Oper. Res..
[27] Carsten Witt,et al. Self-Adjusting Evolutionary Algorithms for Multimodal Optimization , 2020, Algorithmica.
[28] Pietro Simone Oliveto,et al. Fast Artificial Immune Systems , 2018, PPSN.
[29] Frank Neumann,et al. Ant Colony Optimization and the minimum spanning tree problem , 2010, Theor. Comput. Sci..
[30] Andrew M. Sutton,et al. Robustness of Ant Colony Optimization to Noise , 2015, Evolutionary Computation.
[31] Carsten Witt,et al. Stagnation detection in highly multimodal fitness landscapes , 2021, GECCO.
[32] Frank Neumann,et al. Runtime Analysis of a Simple Ant Colony Optimization Algorithm , 2006, ISAAC.
[33] Dirk Sudholt,et al. A Simple Ant Colony Optimizer for Stochastic Shortest Path Problems , 2012, Algorithmica.
[34] Benjamin Doerr,et al. A tight runtime analysis for the cGA on jump functions: EDAs can cross fitness valleys at no extra cost , 2019, GECCO.
[35] Per Kristian Lehre,et al. Escaping Local Optima Using Crossover With Emergent Diversity , 2018, IEEE Transactions on Evolutionary Computation.
[36] Pietro Simone Oliveto,et al. On the runtime analysis of the opt-IA artificial immune system , 2017, GECCO.
[37] Benjamin Doerr,et al. Static and Self-Adjusting Mutation Strengths for Multi-valued Decision Variables , 2018, Algorithmica.
[38] Thomas Jansen,et al. The Analysis of Evolutionary Algorithms—A Proof That Crossover Really Can Help , 2002, Algorithmica.
[39] Benjamin Doerr,et al. Generalized jump functions , 2021, Annual Conference on Genetic and Evolutionary Computation.
[40] Luca Maria Gambardella,et al. A survey on metaheuristics for stochastic combinatorial optimization , 2009, Natural Computing.
[41] Benjamin Doerr,et al. The Univariate Marginal Distribution Algorithm Copes Well with Deception and Epistasis , 2020, Evolutionary Computation.
[42] Frank Neumann,et al. Theoretical Properties of Two ACO Approaches for the Traveling Salesman Problem , 2010, ANTS Conference.
[43] Andrei Lissovoi,et al. On the Time Complexity of Algorithm Selection Hyper-Heuristics for Multimodal Optimisation , 2019, AAAI.
[44] Benjamin Doerr,et al. Runtime Analysis of a Heavy-Tailed (1+(λ, λ)) Genetic Algorithm on Jump Functions , 2020, PPSN.
[45] Benjamin Doerr,et al. Crossover can provably be useful in evolutionary computation , 2008, GECCO '08.
[46] Timo Kötzing,et al. ACO Beats EA on a Dynamic Pseudo-Boolean Function , 2012, PPSN.
[47] Per Kristian Lehre,et al. Negative Drift in Populations , 2010, PPSN.
[48] Thomas Jansen,et al. Analyzing Evolutionary Algorithms: The Computer Science Perspective , 2012 .
[49] Aishwaryaprajna,et al. The benefits and limitations of voting mechanisms in evolutionary optimisation , 2019, FOGA '19.
[50] Thomas Stützle,et al. MAX-MIN Ant System , 2000, Future Gener. Comput. Syst..
[51] Thomas Bäck,et al. Theory of Evolutionary Computation: Recent Developments in Discrete Optimization , 2020, Theory of Evolutionary Computation.
[52] Yuren Zhou,et al. Runtime Analysis of an Ant Colony Optimization Algorithm for TSP Instances , 2009, IEEE Transactions on Evolutionary Computation.
[53] Dirk Sudholt,et al. A few ants are enough: ACO with iteration-best update , 2010, GECCO '10.
[54] Frank Neumann,et al. Design and Management of Complex Technical Processes and Systems by Means of Computational Intelligence Methods Runtime Analysis of a Simple Ant Colony Optimization Algorithm Runtime Analysis of a Simple Ant Colony Optimization Algorithm , 2022 .
[55] Per Kristian Lehre,et al. General Drift Analysis with Tail Bounds , 2013, ArXiv.
[56] Pietro Simone Oliveto,et al. How to Escape Local Optima in Black Box Optimisation: When Non-elitism Outperforms Elitism , 2017, Algorithmica.
[57] Per Kristian Lehre,et al. Ant colony optimization and the minimum cut problem , 2010, GECCO '10.
[58] Dirk Sudholt,et al. Runtime analysis of the 1-ANT ant colony optimizer , 2011, Theor. Comput. Sci..
[59] Benjamin Doerr. Does Comma Selection Help to Cope with Local Optima? , 2020, GECCO.
[60] Walter J. Gutjahr,et al. Ant Colony Optimization: Recent Developments in Theoretical Analysis , 2011, Theory of Randomized Search Heuristics.
[61] Benjamin Doerr,et al. Lazy parameter tuning and control: choosing all parameters randomly from a power-law distribution , 2021, Annual Conference on Genetic and Evolutionary Computation.