Combining PSO and FCM for Dynamic Fuzzy Clustering Problems -- Metaheuristics for solving a hybrid flexible flowshop problem with sequence-dependent setup times -- Using Particle Swarm Optimization Method to Invert Active Surface Waves -- A Fuzzy-Controlled Comprehensive Learning Particle Swarm Optimizer -- Fuzzy Logic Control Optimized by Artificial Immune System for Building Thermal Condition -- Smooth trajectory planning for robot using particle swarm optimization -- Multi-level parallelization for hybrid ACO -- Parallel and Distributed Implementation Models for Bio-inspired Optimization Algorithms -- Using bio-inspired algorithm to compensate web page color contrast for dichromat users -- Comparison of two swarm intelligence optimization algorithms on the textual color problem for web accessibility -- How Much Forcing is Necessary to Let the Results of Particle Swarms Converge? -- The use of ontology in semantic analysis of the published learners messages for adaptability -- A Hybrid PSO Applied to the Flexible Job Shop with Transport -- Multiple Mobile Target Tracking in Wireless Sensor Networks -- Swarm projects: beyond the metaphor -- An enhanced Particle Swarm Optimisation algorithm combined with Neural Networks to decrease computational time -- Robust Multi-Agent Patrolling Strategies using Reinforcement Learning -- BSG-Starcraft Radius improvements of Particle Swarm Optimization -- Algorithm: an application to Ceramic Matrix Composites -- An Efficient ACO-SA Hybrid Metaheuristic for the Synchronization of Single Frequency Networks in Broadcasting -- Floods Trajectories Modeling and Dynamic Relief Planning: A Bees Foraging Approach.

This book constitutes the thoroughly refereed post-conference proceedings of the 1st International Conference on Swarm Intelligence Based Optimization, ICSIBO 2014, held in Mulhouse, France, in May 2014. The 20 full papers presented were carefully reviewed and selected from 48 submissions. Topics of interest presented and discussed in the conference focuses on the theoretical progress of swarm intelligence metaheuristics and their applications in areas such as: theoretical advances of swarm intelligence metaheuristics, combinatorial, discrete, binary, constrained, multi-objective, multi-modal, dynamic, noisy, and large-scale optimization, artificial immune systems, particle swarms, ant colony, bacterial foraging, artificial bees, fireflies algorithm,  hybridization of algorithms, parallel/distributed computing, machine learning, data mining, data clustering, decision making and multi-agent systems based on swarm intelligence principles, adaptation and applications of swarm intelligence principles to real world problems in various domains.