Table of Contents

• Evolving novel algorithm based on intellectual behavior of Wild dog group as optimizerAvtar Singh Buttar, Ashok Kumar Goel, Shakti Kumar. 1-7 [doi]
• A social-spider optimization approach for support vector machines parameters tuningDanillo Roberto Pereira, Mario A. Pazoti, Luis A. M. Pereira, João Paulo Papa. 8-13 [doi]
• A parametric testing of the Firefly algorithm in the determination of the optimal osmotic drying parameters for papayaJulian Scott Yeomans, Raha Imanirad. 14-19 [doi]
• Engineering optimization using interior search algorithmAmir Hossein Gandomi, David A. Roke. 20-26 [doi]
• Non-dominated sorting cuckoo search for multiobjective optimizationXingshi He, Na Li, Xin-She Yang. 27-33 [doi]
• Weight regularisation in particle swarm optimisation neural network trainingAnna Rakitianskaia, Andries Petrus Engelbrecht. 34-41 [doi]
• Gathering algorithm: A new concept of PSO based metaheuristic with dimensional mutationMichal Pluhacek, Roman Senkerik, Ivan Zelinka, Donald Davendra. 42-47 [doi]
• Comparison of self-adaptive particle swarm optimizersEt van Zyl, Ap Engelbrecht. 48-56 [doi]
• Confident but weakly informed: Tackling PSO's momentum conundrumChristopher K. Monson, Kevin D. Seppi. 57-64 [doi]
• Communication-aware distributed PSO for dynamic robotic searchLogan Perreault, Mike P. Wittie, John Sheppard. 65-72 [doi]
• A bio-inspired approach to task assignment of multi-robotsXin Yi, Anmin Zhu, Zhong Ming. 73-77 [doi]
• Naturally inspired optimization algorithms as applied to mobile robotic path planningSteven E. Muldoon, Chaomin Luo, Furao Shen, Hongwei Mo. 78-83 [doi]
• A fuzzy system for parameter adaptation in ant colony optimizationFrumen Olivas, Fevrier Valdez, Oscar Castillo. 84-89 [doi]
• OCbotics: An organic computing approach to collaborative robotic swarmsSebastian von Mammen, Sven Tomforde, Jörg Hähner, Patrick Lehner, Lukas Forschner, Andreas Hiemer, Mirela Nicola, Patrick Blickling. 90-97 [doi]
• Sensor-based autonomous robot navigation under unknown environments with grid map representationChaomin Luo, Jiyong Gao, Xinde Li, Hongwei Mo, Qimi Jiang. 98-104 [doi]
• MAX-SAT problem using evolutionary algorithmsHafiz Munsub Ali, David Mitchell, Daniel C. Lee. 105-112 [doi]
• A generic archive technique for enhancing the niching performance of evolutionary computationYu-hui Zhang, Yue-jiao Gong, Wei-neng Chen, Zhi-hui Zhan, Jun Zhang. 113-120 [doi]
• The hybrid swarm intelligence for S-system model-based genetic networkWei-Chang Yeh, Chia-Ling Huang. 121-127 [doi]
• Changing factor based food sources in artificial bee colonyTarun Kumar Sharma, Millie Pant, Ferrante Neri. 128-135 [doi]
• A new K-harmonic means based simplified swarm optimization for data miningChia-Ling Huang, Wei-Chang Yeh. 136-140 [doi]
• Asynchronous particle swarm optimization with discrete crossoverAndries P. Engelbrecht. 141-148 [doi]
• Particle swarm optimisation failure prediction based on fitness landscape characteristicsKatherine Malan, Andries P. Engelbrecht. 149-157 [doi]
• Evolutionary design of self-organizing particle systems for collective problem solvingBenjamin Bengfort, Philip Y. Kim, Kevin Harrison, James A. Reggia. 158-165 [doi]
• Towards a network-based approach to analyze particle swarm optimizersMarcos A. C. Oliveira, Carmelo J. A. Bastos Filho, Ronaldo Menezes. 166-173 [doi]
• Particle swarm optimization based distributed agreement in multi-agent dynamic systemsVeysel Gazi, Raúl Ordóñez. 174-180 [doi]
• Fitness function evaluations: A fair stopping condition?Andries P. Engelbrecht. 181-188 [doi]
• Parallel glowworm swarm optimization clustering algorithm based on MapReduceNailah Al-Madi, Ibrahim Aljarah, Simone A. Ludwig. 189-196 [doi]
• Analysis of stagnation behaviour of competitive coevolutionary trained neuro-controllersChristiaan Scheepers, Andries P. Engelbrecht. 197-204 [doi]
• Learning Bayesian classifiers using overlapping swarm intelligenceNathan Fortier, John W. Sheppard, Shane Strasser. 205-212 [doi]
• Human-swarm hybrids outperform both humans and swarms solving digital Jigsaw puzzlesDaniel W. Palmer, Marc Kirschenbaum, Eric Mustee, Jason Dengler. 213-220 [doi]
• An algorithm of polygonal approximation constrained by the offset directionXiaojing Xuan, Fangmin Dong, Shuifa Sun, Bangjun Lei. 221-225 [doi]
• A discontinuous recurrent neural network with predefined time convergence for solution of linear programmingJuan Diego Sanchez-Torres, Edgar N. Sanchez, Alexander G. Loukianov. 226-230 [doi]
• A biogeography-based optimization algorithm for energy efficient virtual machine placementHafiz Munsub Ali, Daniel C. Lee. 231-236 [doi]
• Improved particle swarm optimization based on greedy and adaptive featuresAderemi Oluyinka Adewumi, Akugbe Martins Arasomwan. 237-242 [doi]
• Repellent pheromones for effective swarm robot search in unknown environmentsFilip Fossum, Jean-Marc Montanier, Pauline C. Haddow. 243-250 [doi]
• A MOPSO based on hyper-heuristic to optimize many-objective problemsOlacir R. Castro, Aurora Pozo. 251-258 [doi]
• Using heterogeneous knowledge sharing strategies with dynamic vector-evaluated particle swarm optimisationMardé Helbig, Andries P. Engelbrecht. 259-266 [doi]
• A distributed and decentralized approach for ant colony optimization with fuzzy parameter adaptation in traveling salesman problemJake Collings, Eunjin Kim. 267-275 [doi]
• An extended EigenAnt colony system applied to the sequential ordering problemAhmed Ezzat, Ashraf M. Abdelbar, Donald C. Wunsch II. 276-282 [doi]
• A planner for autonomous risk-sensitive coverage (PARCov) by a team of unmanned aerial vehiclesAlex Wallar, Erion Plaku, Donald A. Sofge. 283-289 [doi]
• Path planning for swarms in dynamic environments by combining probabilistic roadmaps and potential fieldsAlex Wallar, Erion Plaku. 290-297 [doi]
• Feature selection for problem decomposition on high dimensional optimizationPedro Reta, Ricardo Landa. 298-304 [doi]
• Improving artifact selection via agent migration in multi-population cultural algorithmsFelicitas Mokom, Ziad Kobti. 305-312 [doi]
• An artificial bee colony algorithm for minimum weight dominating setC. G. Nitash, Alok Singh. 313-319 [doi]
• A new strategy to detect variable interactions in large scale global optimizationMohammad R. Raeesi N., Ziad Kobti. 320-327 [doi]
• A computational basis for the presence of sub-cultures in cultural algoithmsYousof A. Gawasmeh, Robert G. Reynolds. 328-335 [doi]
• Balancing search direction in cultural algorithm for enhanced global numerical optimizationMostafa Z. Ali, Noor H. Awad, Robert G. Reynolds. 336-342 [doi]
• Hybrid cooperative co-evolution for large scale optimizationMohammed El-Abd. 343-348 [doi]
• Prediction of university enrollment using computational intelligenceRyan Stallings, Biswanath Samanta. 349-356 [doi]