Dynamic Selection of Evolutionary Algorithm Operators Based on Online Learning and Fitness Landscape Metrics

Self-adaptive mechanisms for the identification of the most suitable variation operator in Evolutionary meta-heuristics rely almost exclusively on the measurement of the fitness of the offspring, which may not be sufficient to assess the optimality of an operator e.g., in a landscape with an high degree of neutrality. This paper proposes a novel Adaptive Operator Selection mechanism which uses a set of four Fitness Landscape Analysis techniques and an online learning algorithm, Dynamic Weighted Majority, to provide more detailed informations about the search space in order to better determine the most suitable crossover operator on a set of Capacitated Arc Routing Problem CARP instances. Extensive comparison with a state of the art approach has proved that this technique is able to produce comparable results on the set of benchmark problems.

[1]  Frédéric Saubion,et al.  A Compass to Guide Genetic Algorithms , 2008, PPSN.

[2]  D. Hinkley.  Inference about the change-point from cumulative sum tests , 1971 .

[3]  L. Darrell Whitley,et al.  The dispersion metric and the CMA evolution strategy , 2006, GECCO.

[4]  H. Barbosa.  On Adaptive Operator Probabilities in Real Coded Genetic Algorithms , 2000 .

[5]  Dirk Thierens,et al.  An Adaptive Pursuit Strategy for Allocating Operator Probabilities , 2005, BNAIC.

[6]  Marcus A. Maloof,et al.  Dynamic weighted majority: a new ensemble method for tracking concept drift , 2003, Third IEEE International Conference on Data Mining.

[7]  Jens Gottlieb,et al.  Evolutionary Computation in Combinatorial Optimization , 2006, Lecture Notes in Computer Science.

[8]  Luc Muyldermans,et al.  A guided local search heuristic for the capacitated arc routing problem , 2003, Eur. J. Oper. Res..

[9]  Peter Auer,et al.  Finite-time Analysis of the Multiarmed Bandit Problem , 2002, Machine Learning.

[10]  Xin Yao,et al.  Fitness-Probability Cloud and a Measure of Problem Hardness for Evolutionary Algorithms , 2011, EvoCOP.

[11]  Richard Granger,et al.  Beyond Incremental Processing: Tracking Concept Drift , 1986, AAAI.

[12]  Ian H. Witten,et al.  The WEKA data mining software: an update , 2009, SKDD.

[13]  Zbigniew Michalewicz,et al.  Parameter Control in Evolutionary Algorithms , 2007, Parameter Setting in Evolutionary Algorithms.

[14]  Yuri Pirola,et al.  A quantitative study of neutrality in GP boolean landscapes , 2006, GECCO '06.

[15]  Michèle Sebag,et al.  Dynamic Multi-Armed Bandits and Extreme Value-Based Rewards for Adaptive Operator Selection in Evolutionary Algorithms , 2009, LION.

[16]  Bruce L. Golden,et al.  Capacitated arc routing problems , 1981, Networks.

[17]  Xin Yao,et al.  Diversity-Driven Selection of Multiple Crossover Operators for the Capacitated Arc Routing Problem , 2014, EvoCOP.

[18]  Simon M. Lucas,et al.  Parallel Problem Solving from Nature - PPSN X, 10th International Conference Dortmund, Germany, September 13-17, 2008, Proceedings , 2008, PPSN.

[19]  Lawrence Davis,et al.  Adapting Operator Probabilities in Genetic Algorithms , 1989, ICGA.

[20]  Xin Yao,et al.  The Impact of Diversity on Online Ensemble Learning in the Presence of Concept Drift , 2010, IEEE Transactions on Knowledge and Data Engineering.

[21]  Peter Merz,et al.  Advanced Fitness Landscape Analysis and the Performance of Memetic Algorithms , 2004, Evolutionary Computation.

[22]  N. Hansen,et al.  Markov Chain Analysis of Cumulative Step-Size Adaptation on a Linear Constrained Problem , 2015, Evolutionary Computation.

[23]  Christian Blum,et al.  Evolutionary Computation in Combinatorial Optimization , 2015, Lecture Notes in Computer Science.

[24]  Xin Yao,et al.  Stochastic ranking for constrained evolutionary optimization , 2000, IEEE Trans. Evol. Comput..

[25]  David E. Goldberg,et al.  Probability Matching, the Magnitude of Reinforcement, and Classifier System Bidding , 1990, Machine Learning.

[26]  Michèle Sebag,et al.  Adaptive operator selection with dynamic multi-armed bandits , 2008, GECCO '08.

[27]  Xin Yao,et al.  Memetic Algorithm With Extended Neighborhood Search for Capacitated Arc Routing Problems , 2009, IEEE Transactions on Evolutionary Computation.

[28]  Richard W. Eglese,et al.  Routeing Winter Gritting Vehicles , 1994, Discret. Appl. Math..

[29]  Bryant A. Julstrom,et al.  What Have You Done for Me Lately? Adapting Operator Probabilities in a Steady-State Genetic Algorithm , 1995, ICGA.