Music-Inspired Harmony Search Algorithm : Theory and Applications

Zong Woo Geem

ISBN 10: 364200184X / ISBN 13: 9783642001840

Published by Springer, Berlin, Springer Berlin Heidelberg, Springer, 2009

About this Item

Druck auf Anfrage Neuware - Printed after ordering - Calculus has been used in solving many scientific and engineering problems. For optimization problems, however, the differential calculus technique sometimes has a drawback when the objective function is step-wise, discontinuous, or multi-modal, or when decision variables are discrete rather than continuous. Thus, researchers have recently turned their interests into metaheuristic algorithms that have been inspired by natural phenomena such as evolution, animal behavior, or metallic annealing.This book especially focuses on a music-inspired metaheuristic algorithm, harmony search. Interestingly, there exists an analogy between music and optimization: each musical instrument corresponds to each decision variable; musical note corresponds to variable value; and harmony corresponds to solution vector. Just like musicians in Jazz improvisation play notes randomly or based on experiences in order to find fantastic harmony, variables in the harmony search algorithm have random values or previously-memorized good values in order to find optimal solution.

Seller Inventory # 9783642001840

Bibliographic Details

• Title: Music-Inspired Harmony Search Algorithm : Theory and Applications
• Publisher: Springer, Berlin, Springer Berlin Heidelberg, Springer
• Publication Date: 2009
• Language: English
• ISBN 10: 364200184X
• ISBN 13: 9783642001840
• Binding: Buch
• Condition: Neu
• Dimensions: 235W x 155H x 35D millimeters 235 millimeters width by 155 millimeters height by 35 millimeters depth
• Weight: 438 grams

About this title

Synopsis

Calculus has been used in solving many scientific and engineering problems. For optimization problems, however, the differential calculus technique sometimes has a drawback when the objective function is step-wise, discontinuous, or multi-modal, or when decision variables are discrete rather than continuous. Thus, researchers have recently turned their interests into metaheuristic algorithms that have been inspired by natural phenomena such as evolution, animal behavior, or metallic annealing.

This book especially focuses on a music-inspired metaheuristic algorithm, harmony search. Interestingly, there exists an analogy between music and optimization: each musical instrument corresponds to each decision variable; musical note corresponds to variable value; and harmony corresponds to solution vector. Just like musicians in Jazz improvisation play notes randomly or based on experiences in order to find fantastic harmony, variables in the harmony search algorithm have random values or previously-memorized good values in order to find optimal solution.