An improved krill herd algorithm: Krill herd with linear decreasing step

A deficiency of KH is analyzed.Why KH cannot achieve the excellent balance between exploration and exploitation in optimization processing is explained.To overcome the defect, an improved KH with linear decreasing step (KHLD) is proposed. Krill herd (KH) inspired by the herding behavior of the krill individuals is a new swarm intelligent algorithm which is proved to perform better than other swarm intelligent algorithms. However, there are some weak points yet. In this paper, we analyze a deficiency of KH which cannot achieve the excellent balance between exploration and exploitation in optimization processing and proposed an improved KH-krill herd with linear decreasing step (KHLD). Twenty benchmark functions are used to verify the effectiveness of these improvements and it is illustrated that, in most cases, the performance of KHLD is superior to the standard KH.

[1]  Amir Hossein Gandomi,et al.  Hybrid krill herd algorithm with differential evolution for global numerical optimization , 2014, Neural Computing and Applications.

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

[3]  Amir Hossein Gandomi,et al.  Stud krill herd algorithm , 2014, Neurocomputing.

[4]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[5]  M.A. El-Sharkawi,et al.  Swarm intelligence for routing in communication networks , 2001, GLOBECOM'01. IEEE Global Telecommunications Conference (Cat. No.01CH37270).

[6]  Gaige Wang,et al.  A Novel Hybrid Bat Algorithm with Harmony Search for Global Numerical Optimization , 2013, J. Appl. Math..

[7]  Amir Hossein Gandomi,et al.  A chaotic particle-swarm krill herd algorithm for global numerical optimization , 2013, Kybernetes.

[8]  Gai-Ge Wang,et al.  A New Improved Firefly Algorithm for Global Numerical Optimization , 2014 .

[9]  Xin-She Yang,et al.  Bat algorithm: a novel approach for global engineering optimization , 2012, 1211.6663.

[10]  Kazuyuki Mori,et al.  Immune Algorithm with Searching Diversity and its Application to Resource Allocation Problem , 1993 .

[11]  Gai-Ge Wang,et al.  A modified firefly algorithm for UCAV path planning , 2012 .

[12]  Amir Hossein Alavi,et al.  Levy-flight krill herd algorithm , 2013 .

[13]  Amir Hossein Alavi,et al.  Krill herd: A new bio-inspired optimization algorithm , 2012 .

[14]  Gaige Wang,et al.  A Hybrid Metaheuristic DE/CS Algorithm for UCAV Three-Dimension Path Planning , 2012, TheScientificWorldJournal.

[15]  Luo Liu,et al.  A hybrid meta-heuristic DE/CS Algorithm for UCAV path planning , 2012 .

[16]  Y. Volkan Pehlivanoglu,et al.  A New Particle Swarm Optimization Method Enhanced With a Periodic Mutation Strategy and Neural Networks , 2013, IEEE Transactions on Evolutionary Computation.

[17]  Minghong Liao,et al.  Development and Demonstration of an Artificial Immune Algorithm for Mangrove Mapping Using Landsat TM , 2013, IEEE Geoscience and Remote Sensing Letters.

[18]  Gaige Wang,et al.  A Bat Algorithm with Mutation for UCAV Path Planning , 2012, TheScientificWorldJournal.

[19]  Quan-Ke Pan,et al.  An Effective Artificial Bee Colony Algorithm for a Real-World Hybrid Flowshop Problem in Steelmaking Process , 2013, IEEE Transactions on Automation Science and Engineering.

[20]  Marco Dorigo,et al.  Swarm intelligence: from natural to artificial systems , 1999 .

[21]  Jiang Li,et al.  Erratum to: Incorporating mutation scheme into krill herd algorithm for global numerical optimization , 2013, Neural Computing and Applications.

[22]  Russell C. Eberhart,et al.  A new optimizer using particle swarm theory , 1995, MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science.

[23]  A. Gandomi,et al.  Simulated Annealing-Based Krill Herd Algorithm for Global Optimization , 2013 .

[24]  Amir Hossein Gandomi,et al.  Krill herd algorithm for optimum design of truss structures , 2013, Int. J. Bio Inspired Comput..