03596oam 2200601I 450 991015318570332120240501163852.01-315-29763-91-315-29765-51-315-29764-710.1201/9781315297651 (CKB)3710000000960806(MiAaPQ)EBC4748360(OCoLC)964527735(BIP)72183923(BIP)61866342(EXLCZ)99371000000096080620180331h20172017 uy 0engurcnu||||||||rdacontentrdamediardacarrierAdvances in metaheuristics applications in engineering systems /Timothy Ganesan, PhD, Pandian Vasant, PhD, Irraivan Elamvazuthi, PhD1st ed.Boca Raton :CRC Press,[2017]©20171 online resource (234 pages)1-138-45562-8 1-4987-1548-6 Includes bibliographical references at the end of each chapters and index.part I. Energy systems -- part II. Process optimization -- part III. Material engineering.Advances in Metaheuristics: Applications in Engineering Systems provides details on current approaches utilized in engineering optimization. It gives a comprehensive background on metaheuristic applications, focusing on main engineering sectors such as energy, process, and materials. It discusses topics such as algorithmic enhancements and performance measurement approaches, and provides insights into the implementation of metaheuristic strategies to multi-objective optimization problems. With this book, readers can learn to solve real-world engineering optimization problems effectively using the appropriate techniques from emerging fields including evolutionary and swarm intelligence, mathematical programming, and multi-objective optimization. The ten chapters of this book are divided into three parts. The first part discusses three industrial applications in the energy sector. The second focusses on process optimization and considers three engineering applications: optimization of a three-phase separator, process plant, and a pre-treatment process. The third and final part of this book covers industrial applications in material engineering, with a particular focus on sand mould-systems. It also includes discussions on the potential improvement of algorithmic characteristics via strategic algorithmic enhancements. This book helps fill the existing gap in literature on the implementation of metaheuristics in engineering applications and real-world engineering systems. It will be an important resource for engineers and decision-makers selecting and implementing metaheuristics to solve specific engineering problems.Industrial engineeringMathematicsElectric power systemsMathematicsMaterials scienceMathematicsMathematical optimizationHeuristic algorithmsIndustrial engineeringMathematics.Electric power systemsMathematics.Materials scienceMathematics.Mathematical optimization.Heuristic algorithms.620.00285/63Ganesan Timothy1213681Vasant PandianElamvazuthi IrraivanFlBoTFGFlBoTFGBOOK9910153185703321Advances in metaheuristics2802921UNINA