TY - CHAP A1 - Yoon-Teck Bau A2 - Chin-Kuan Ho A3 - Hong-Tat Ewe ED1 - Felix T.S. Chan ED2 - Manoj Kumar Tiwari Y1 - 2007-12-01 PY - 2007 T1 - A New Ant Colony Optimization Approach for the Degree-Constrained Minimum Spanning Tree Problem Using Pruefer and Blob Codes Tree Coding N2 - In the era globalisation the emerging technologies are governing engineering industries to a multifaceted state. The escalating complexity has demanded researchers to find the possible ways of easing the solution of the problems. This has motivated the researchers to grasp ideas from the nature and implant it in the engineering sciences. This way of thinking led to emergence of many biologically inspired algorithms that have proven to be efficient in handling the computationally complex problems with competence such as Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), etc. Motivated by the capability of the biologically inspired algorithms the present book on "Swarm Intelligence: Focus on Ant and Particle Swarm Optimization" aims to present recent developments and applications concerning optimization with swarm intelligence techniques. The papers selected for this book comprise a cross-section of topics that reflect a variety of perspectives and disciplinary backgrounds. In addition to the introduction of new concepts of swarm intelligence, this book also presented some selected representative case studies covering power plant maintenance scheduling; geotechnical engineering; design and machining tolerances; layout problems; manufacturing process plan; job-shop scheduling; structural design; environmental dispatching problems; wireless communication; water distribution systems; multi-plant supply chain; fault diagnosis of airplane engines; and process scheduling. I believe these 27 chapters presented in this book adequately reflect these topics. BT - Swarm Intelligence SP - Ch. 3 UR - https://doi.org/10.5772/5096 DO - 10.5772/5096 SN - PB - IntechOpen CY - Rijeka Y2 - 2021-09-20 ER -