A self-adaptive binary differential evolution algorithm for large scale binary optimization problems

A new binary variant of the DE algorithm is presented.A new approach to design search strategies for the binary DE algorithms is suggested.The proposed algorithm is implemented and tested on modern benchmark problems and high dimensional knapsack problems.The performance of the proposed algorithm is compared against some recently presented binary algorithms. This study proposes a new self-adaptive binary variant of a differential evolution algorithm, based on measure of dissimilarity and named SabDE. It uses an adaptive mechanism for selecting how new trial solutions are generated, and a chaotic process for adapting parameter values. SabDE is compared against a number of existing state of the art algorithms, on a set of benchmark problems including high dimensional knapsack problems with up to 10,000 dimensions as well as on the 15 learning based problems of the Congress on Evolutionary Computation (CEC 2015). Experimental results reveal that the proposed algorithm performs competitively and in some cases is superior to the existing algorithms.

[1]  Mohd Ismail Abd Aziz,et al.  Enhanced compact artificial bee colony , 2015, Inf. Sci..

[2]  M. S. Kiran,et al.  XOR-based artificial bee colony algorithm for binary optimization , 2013 .

[3]  Philippe Michelon,et al.  A linearization framework for unconstrained quadratic (0-1) problems , 2009, Discret. Appl. Math..

[4]  Dervis Karaboga,et al.  AN IDEA BASED ON HONEY BEE SWARM FOR NUMERICAL OPTIMIZATION , 2005 .

[5]  Vassil Guliashki,et al.  LINEAR INTEGER PROGRAMMING METHODS AND APPROACHES-A SURVEY , 2011 .

[6]  Dervis Karaboga,et al.  A novel binary artificial bee colony algorithm based on genetic operators , 2015, Inf. Sci..

[7]  Minrui Fei,et al.  A Discrete Harmony Search Algorithm , 2010 .

[8]  Saku Kukkonen,et al.  Real-parameter optimization with differential evolution , 2005, 2005 IEEE Congress on Evolutionary Computation.

[9]  Ming Yu,et al.  Modified differential evolution algorithm and its application in thermal process model identification , 2010, 2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering.

[10]  Hu Peng,et al.  Novel Binary Encoding Differential Evolution Algorithm , 2011, ICSI.

[11]  Zong Woo Geem,et al.  A New Heuristic Optimization Algorithm: Harmony Search , 2001, Simul..

[12]  James C. Spall,et al.  Simultaneous Perturbation Stochastic Approximation , 2005 .

[13]  Hossein Nezamabadi-pour,et al.  A quantum-inspired gravitational search algorithm for binary encoded optimization problems , 2015, Eng. Appl. Artif. Intell..

[14]  H Nezamabadi Pour,et al.  BINARY PARTICLE SWARM OPTIMIZATION: CHALLENGES AND NEW SOLUTIONS , 2008 .

[15]  Andries Petrus Engelbrecht,et al.  Binary differential evolution strategies , 2007, 2007 IEEE Congress on Evolutionary Computation.

[16]  M. P. Saka,et al.  Adaptive Harmony Search Method for Structural Optimization , 2010 .

[17]  Russell C. Eberhart,et al.  A discrete binary version of the particle swarm algorithm , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.

[18]  Janez Brest,et al.  Self-Adapting Control Parameters in Differential Evolution: A Comparative Study on Numerical Benchmark Problems , 2006, IEEE Transactions on Evolutionary Computation.

[19]  Ponnuthurai N. Suganthan,et al.  An Adaptive Differential Evolution Algorithm With Novel Mutation and Crossover Strategies for Global Numerical Optimization , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[20]  G. Dantzig.  Discrete-Variable Extremum Problems , 1957 .

[21]  Hossein Nezamabadi-pour,et al.  BGSA: binary gravitational search algorithm , 2010, Natural Computing.

[22]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..

[23]  Yan Dong,et al.  Feature Selection with Discrete Binary Differential Evolution , 2009, 2009 International Conference on Artificial Intelligence and Computational Intelligence.

[24]  P. N. Suganthan,et al.  Differential Evolution: A Survey of the State-of-the-Art , 2011, IEEE Transactions on Evolutionary Computation.

[25]  Daniela Zaharie,et al.  Influence of crossover on the behavior of Differential Evolution Algorithms , 2009, Appl. Soft Comput..

[26]  Hanif D. Sherali,et al.  Evolution and state-of-the-art in integer programming , 2000 .

[27]  Yang Wang,et al.  Repairing the crossover rate in adaptive differential evolution , 2014, Appl. Soft Comput..

[28]  M. A. Khanesar,et al.  A novel binary particle swarm optimization , 2007, 2007 Mediterranean Conference on Control & Automation.

[29]  Bingyan Zhao,et al.  Novel Binary Differential Evolution Algorithm for Discrete Optimization , 2009, 2009 Fifth International Conference on Natural Computation.

[30]  P. N. Suganthan,et al.  Differential Evolution Algorithm With Strategy Adaptation for Global Numerical Optimization , 2009, IEEE Transactions on Evolutionary Computation.

[31]  Ville Tirronen,et al.  Recent advances in differential evolution: a survey and experimental analysis , 2010, Artificial Intelligence Review.

[32]  Kenneth V. Price,et al.  An introduction to differential evolution , 1999 .

[33]  William Kahan,et al.  Lecture Notes on the Status of IEEE Standard 754 for Binary Floating-Point Arithmetic , 1996 .

[34]  Liu Zhiming,et al.  Solving 0-1 Knapsack Problems by a Discrete Binary Version of Differential Evolution , 2008, 2008 Second International Symposium on Intelligent Information Technology Application.

[35]  H. S. Lopes,et al.  A Comparison of Differential Evolution Algorithm with Binary and Continuous Encoding for the MKP , 2013, 2013 BRICS Congress on Computational Intelligence and 11th Brazilian Congress on Computational Intelligence.

[36]  Zong Woo Geem,et al.  Harmony Search in Water Pump Switching Problem , 2005, ICNC.

[37]  Weicheng Xie,et al.  A binary differential evolution algorithm learning from explored solutions , 2014, Neurocomputing.

[38]  Zong Woo Geem,et al.  A survey on applications of the harmony search algorithm , 2013, Eng. Appl. Artif. Intell..

[39]  Carlos A. Coello Coello,et al.  A comparative study of differential evolution variants for global optimization , 2006, GECCO.

[40]  Xuefeng Yan,et al.  Self-adaptive differential evolution algorithm with discrete mutation control parameters , 2015, Expert Syst. Appl..

[41]  J. Kennedy,et al.  Neighborhood topologies in fully informed and best-of-neighborhood particle swarms , 2003, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[42]  Yupu Yang,et al.  Quantum-Inspired Differential Evolution for Binary Optimization , 2008, 2008 Fourth International Conference on Natural Computation.

[43]  Hossein Nezamabadi-pour,et al.  GSA: A Gravitational Search Algorithm , 2009, Inf. Sci..

[44]  Wenyin Gong,et al.  Differential Evolution With Ranking-Based Mutation Operators , 2013, IEEE Transactions on Cybernetics.

[45]  Ponnuthurai Nagaratnam Suganthan,et al.  Problem Definitions and Evaluation Criteria for CEC 2015 Special Session on Bound Constrained Single-Objective Computationally Expensive Numerical Optimization , 2015 .

[46]  Shafaatunnur Hasan,et al.  Memetic binary particle swarm optimization for discrete optimization problems , 2015, Inf. Sci..

[47]  Panos M. Pardalos,et al.  An improved adaptive binary Harmony Search algorithm , 2013, Inf. Sci..

[48]  Steven Li,et al.  A simplified binary harmony search algorithm for large scale 0-1 knapsack problems , 2015, Expert Syst. Appl..

[49]  Ali Husseinzadeh Kashan,et al.  DisABC: A new artificial bee colony algorithm for binary optimization , 2012, Appl. Soft Comput..

[50]  Andries Petrus Engelbrecht,et al.  Binary Differential Evolution , 2006, 2006 IEEE International Conference on Evolutionary Computation.

[51]  Deyu Tang,et al.  Grid Task Scheduling Strategy Based on Differential Evolution-Shuffled Frog Leaping Algorithm , 2012, 2012 International Conference on Computer Science and Service System.

[52]  Muhammad Khurram Khan,et al.  Binary Artificial Bee Colony optimization using bitwise operation , 2014, Comput. Ind. Eng..