Decomposition-based evolutionary optimization in complex environments

by Li, Juan, (Mathematician)

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Title Statements

Full title :Decomposition-based evolutionary optimization in complex environments / Juan Li, Bin Xin, Jie Chen, Beijing Institute of Technology, China.

Summary

"Multi-objective optimization problems (MOPs) and uncertain optimization problems (UOPs) which widely exist in real life are challengeable problems in the fields of decision making, system designing, and scheduling, amongst others. Decomposition exploits the ideas of 'making things simple' and 'divide and conquer' to transform a complex problem into a series of simple ones with the aim of reducing the computational complexity. In order to tackle the abovementioned two types of complicated optimization problems, this book introduces the decomposition strategy and conducts a systematic study to perfect the usage of decomposition in the field of multi-objective optimization, and extend the usage of decomposition in the field of uncertain optimization"--

Edition Statements

Publication Date:2021

Publication Statements

Publisher(s):World Scientific
Place of Publication:Hoboken
Language:eng
Publication Date:2021

The Physical Object

Description:1 online resource

Edition Identifiers

ISBN:9789811218996, 9811218994
oclc:on1163922686
LC Classification:TA347.E96
Dewey Decimal:006.3/823

Intro -- Contents -- Preface -- Acknowledgments -- About the Authors -- 1. Introduction -- 1.1 Uncertain and Multi-objective Optimization -- 1.2 Mathematical Formulations of the Uncertain and Multi-objective Optimization Problem -- 1.2.1 Multi-objective Optimization Problems -- 1.2.2 Uncertain Optimization Problems -- 1.3 Brief Introduction to Multi-objective Evolutionary Algorithms -- 1.3.1 Pareto Dominance-based MOEAs -- 1.3.2 Performance Indicator-based MOEAs -- 1.3.3 Decomposition-based MOEAs -- 1.3.4 MOEAs for Many-objective Optimization Problems