Nature-Inspired Algorithms and Applied Optimization

This book reviews the state-of-the-art developments in nature-inspired algorithms and their applications in various disciplines, ranging from feature selection and engineering design optimization to scheduling and vehicle routing. It introduces each algorithm and its implementation with case studies as well as extensive literature reviews, and also includes self-contained chapters featuring theoretical analyses, such as convergence analysis and no-free-lunch theorems so as to provide insights into the current nature-inspired optimization algorithms. Topics include ant colony optimization, the bat algorithm, B-spline curve fitting, cuckoo search, feature selection, economic load dispatch, the firefly algorithm, the flower pollination algorithm, knapsack problem, octonian and quaternion representations, particle swarm optimization, scheduling, wireless networks, vehicle routing with time windows, and maximally different alternatives. This timely book serves as a practical guide and reference resource for students, researchers and professionals.

Aceasta carte trece in revista evolutiile de ultima generatie in algoritmi inspirati in natura si aplicatiile acestora in diverse discipline, variind de la selectia caracteristicilor si optimizarea proiectarii tehnice pana la planificarea si rutare vehiculului. Acesta introduce fiecare algoritm si implementarea sa cu studii de caz, precum si revizuiri ample ale literaturii si include, de asemenea, capitole autonome care prezinta analize teoretice, cum ar fi analiza convergentei si teoremele fara pranz, astfel incat sa ofere informatii despre actuala natura inspirata de natura algoritmi de optimizare.