Bi-Directional Self-Organization Technique for Enhancing the Genetic Algorithm

Genetic Algorithm (GA) is well-known optimization algorithm for solving various kinds of the optimization problem. GA is based on evolutionary principles and effectively solves the large-scale problem. In addition, it incorporates the variety of hybrid techniques to achieve the best performance in complex problems. However, self-organization is one of the popular model, which acquire global order from the local interaction among the individuals. The combined version of self-organization and genetic algorithm are adopted to improve the performance in attaining the convergence. This paper proposes a bi-directional self-organization process for improving the genetic algorithm which achieves the convergence and well-balanced diversity in the population. The experimentation is conducted on the standard test-bed of travelling salesman problem and instances are obtained from TSPLIB. Thus, the proposed algorithm has shown its dominance with the existing classical GA in terms of various parameter metrics.

[1]  Marc M. Van Hulle.  Self-organizing Maps , 2012, Handbook of Natural Computing.

[2]  Robert G. Reynolds,et al.  An improved class of real-coded Genetic Algorithms for numerical optimization✰ , 2018, Neurocomputing.

[3]  Xin-She Yang,et al.  Nature-Inspired Metaheuristic Algorithms , 2008 .

[4]  C. Tajani,et al.  GENETIC ALGORITHM ADOPTING IMMIGRATION OPERATOR TO SOLVE THE ASYMMETRIC TRAVELING SALESMAN PROBLEM , 2017 .

[5]  R. Subramanian,et al.  A NOVEL SELF-ORGANIZATION MODEL FOR IMPROVING THE PERFORMANCE OF PERMUTATION CODED GENETIC ALGORITHM , 2018 .

[6]  Yiu-Ming Cheung,et al.  Self-Organizing Map-Based Weight Design for Decomposition-Based Many-Objective Evolutionary Algorithm , 2018, IEEE Transactions on Evolutionary Computation.

[7]  Hui Wang,et al.  A new dynamic firefly algorithm for demand estimation of water resources , 2018, Inf. Sci..

[8]  Fang Miao,et al.  Genetic Algorithm with an Improved Initial Population Technique for Automatic Clustering of Low-Dimensional Data , 2018, Inf..

[9]  Eisuke Kita,et al.  Investigation of self-organizing map for genetic algorithm , 2010, Adv. Eng. Softw..

[10]  O. Yugay,et al.  Hybrid Genetic Algorithm for Solving Traveling Salesman Problem with Sorted Population , 2008, 2008 Third International Conference on Convergence and Hybrid Information Technology.

[11]  Poom Kumam,et al.  Perspectives and Experiments of Hybrid Particle Swarm Optimization and Genetic Algorithms to Solve Optimization Problems , 2018, ECONVN.

[12]  K. Katayama,et al.  The efficiency of hybrid mutation genetic algorithm for the travelling salesman problem , 2000 .

[13]  Lei Wang,et al.  ARAe-SOM+BCO: An enhanced artificial raindrop algorithm using self-organizing map and binomial crossover operator , 2018, Neurocomputing.

[14]  Doug Hains,et al.  Tunneling between optima: partition crossover for the traveling salesman problem , 2009, GECCO.

[15]  Bart De Moor,et al.  A Self-Tuning Genetic Algorithm with Applications in Biomarker Discovery , 2014, 2014 IEEE 27th International Symposium on Computer-Based Medical Systems.

[16]  Shengxiang Yang,et al.  Genetic Algorithms with Self-Organizing Behaviour in Dynamic Environments , 2007, Evolutionary Computation in Dynamic and Uncertain Environments.

[17]  Pothula Sujatha,et al.  GPS: a constraint-based gene position procurement in chromosome for solving large-scale multiobjective multiple knapsack problems , 2018, Frontiers of Computer Science.

[18]  Ramachandran Baskaran,et al.  A new population seeding technique for permutation-coded Genetic Algorithm: Service transfer approach , 2014, J. Comput. Sci..

[19]  Kwong-Sak Leung,et al.  An expanding self-organizing neural network for the traveling salesman problem , 2004, Neurocomputing.

[20]  Ayse T. Daloglu,et al.  An improved genetic algorithm with initial population strategy and self-adaptive member grouping , 2008 .

[21]  Jaafar Abouchabaka,et al.  Optimization Approach Based on Immigration Strategies for Symmetric Traveling Salesman Problem , 2017 .

[22]  Kusum Deep,et al.  A self-organizing migrating genetic algorithm for constrained optimization , 2008, Appl. Math. Comput..

[23]  Doug Hains,et al.  A Hybrid Genetic Algorithm for the Traveling Salesman Problem Using Generalized Partition Crossover , 2010, PPSN.