Recent Advances in Swarm Intelligence and Evolutionary Computation [Paperback]

This timely review volume summarizes the state-of-the-art developments in nature-inspired algorithms and applications with the emphasis on swarm intelligence and bio-inspired computation. Topics include the analysis and overview of swarm intelligence and evolutionary computation, hybrid metaheuristic algorithms, bat algorithm, discrete cuckoo search, firefly algorithm, particle swarm optimization, and harmony search as well as convergent hybridization. Application case studies have focused on the dehydration of fruits and vegetables by the firefly algorithm and goal programming, feature selection by the binary flower pollination algorithm, job shop scheduling, single row facility layout optimization, training of feed-forward neural networks, damage and stiffness identification, synthesis of cross-ambiguity functions by the bat algorithm, web document clustering, truss analysis, water distribution networks, sustainable building designs and others.

As a timely review, this book can serve as an ideal reference for graduates, lecturers, engineers and researchers in computer science, evolutionary computing, artificial intelligence, machine learning, computational intelligence, data mining, engineering optimization and designs.

Swarm Intelligence and Evolutionary Computation: Overview and Analysis.- Globally convergent hybridization of particle swarm optimization using line search-based derivative-free techniques Fireflies in the Fruits and Vegetables: Combining the Firefly Algorithm with Goal Programming for Setting Optimal Osmotic Dehydration Parameters of Produce.- Hybrid Metaheuristic Algorithms: Past, Present and Future.- Binary Flower Pollination Algorithm and Its Application to Feature Selection.- Bat Algorithm Application for the Single Row Facility Layout Problem.- Discrete Cuckoo Search Applied to Job Shop Scheduling Problem.- Cuckoo Search and Bat Algorithm Applied to Training Feed-Forward Neural Networks.-lS²