Joao Paulo do Vale Madeiro; Paulo Cesar Cortez; José Maria Da Silva Monteiro Filho; Angelo Roncalli Alencar Brayner Elsevier Science Publishing Co Inc (2018) Saatavuus: Tilaustuote Pehmeäkantinen kirja
Paulo Cortez (ed.); Luís Magalhães (ed.); Pedro Branco (ed.); Carlos Filipe Portela (ed.); Telmo Adão (ed.) Springer (2019) Saatavuus: Tilaustuote Pehmeäkantinen kirja
Anthony Barker; Maria Eugenia Pereira; Maria Teresa Cortez; Paulo Alexandre Pereira; Otilia Martins Springer International Publishing AG (2018) Saatavuus: Tilaustuote Kovakantinen kirja
Anthony Barker; Maria Eugénia Pereira; Maria Teresa Cortez; Paulo Alexandre Pereira; Otília Martins Springer International Publishing AG (2019) Saatavuus: Tilaustuote Pehmeäkantinen kirja
Manuel Filipe Santos (ed.); José Machado (ed.); Paulo Novais (ed.); Paulo Cortez (ed.); Pedro Miguel Moreira (ed.) Springer (2024) Saatavuus: Tulossa! Pehmeäkantinen kirja
Manuel Filipe Santos (ed.); José Machado (ed.); Paulo Novais (ed.); Paulo Cortez (ed.); Pedro Miguel Moreira (ed.) Springer (2024) Saatavuus: Tulossa! Pehmeäkantinen kirja
Springer Sivumäärä: 188 sivua Asu: Pehmeäkantinen kirja Painos: 2014 Julkaisuvuosi: 2014, 22.09.2014 (lisätietoa) Kieli: Englanti
The goal of this book is to gather in a single document the most relevant concepts related to modern optimization methods, showing how such concepts and methods can be addressed using the open source, multi-platform R tool. Modern optimization methods, also known as metaheuristics, are particularly useful for solving complex problems for which no specialized optimization algorithm has been developed. These methods often yield high quality solutions with a more reasonable use of computational resources (e.g. memory and processing effort). Examples of popular modern methods discussed in this book are: simulated annealing; tabu search; genetic algorithms; differential evolution; and particle swarm optimization. This book is suitable for undergraduate and graduate students in Computer Science, Information Technology, and related areas, as well as data analysts interested in exploring modern optimization methods using R.
