Biologically-Inspired Optimisation Methods Parallel Algorithms, Systems and Applications /

• Corporate Author: SpringerLink (Online service)
• Other Authors: Lewis, Andrew. (Editor), Mostaghim, Sanaz. (Editor), Randall, Marcus. (Editor)
• Format: Electronic
• Language: English
• Published: Berlin, Heidelberg : Springer Berlin Heidelberg, 2009.
• Series: Studies in Computational Intelligence, 210
• Subjects: Engineering.; Artificial intelligence.; Engineering mathematics.; Appl.Mathematics/Computational Methods of Engineering.; Artificial Intelligence (incl. Robotics).
• Online Access: https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-3-642-01262-4

Humanity has often turned to Nature for inspiration to help it solve its problems. The systems She provides are often based on simple rules and premises, yet are able to adapt to new and complex environments quickly and efficiently. Problems from a range of human endeavours, including, science, engi...

Table of Contents:

• Evolutions Niche in Multi-Criterion Problem Solving
• Applications of Parallel Platforms and Models in Evolutionary Multi-Objective Optimisation
• Asynchronous Multi-Objective Particle Swarm Optimisation in Unreliable Distributed Environments
• Dynamic Problems and Nature Inspired Meta-heuristics
• Relaxation Labelling Using Distributed Neural Networks
• Extremal Optimisation for Assignment Type Problems
• Niching for Ant Colony Optimisation
• Using Ant Colony Optimisation to Improve Small Meander Line RFID Antennas
• The Radio Network Design Optimisation Problem and State-of-the-Art Solvers
• Parallel Evolutionary Algorithms for Urban Energy Management
• An Analysis of Dynamic Operators for Conformational Sampling on Grids
• Evolving Computer Chinese Chess Using Guided Learning.