NDLI: An Adaptive Multi-objective Immune Optimization Algorithm

Content Provider	IEEE Xplore Digital Library
Author	Lu Hong
Copyright Year	2009
Abstract	It is difficult for traditional search methods to solve multi-objective optimization problems. Based on the idea of clonal selection principle, we present an adaptive multi-objective immune optimization algorithm (AMIOA) for function optimization problems and analyze its powerful performance from the immune system point of view. The main feature of the algorithm is the global search performance and the solution sets produced are highly competitive in terms of convergence, diversity and distribution. The comparative simulation results show that the proposed algorithm not only can obtain a set of solutions including the global optimum and multiple local optima, but also has much less computational cost than other algorithms.
Starting Page	140
Ending Page	143
File Size	294120
Page Count	4
File Format	PDF
ISBN	9780769537283
DOI	10.1109/CASE.2009.133
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-07-11
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Automation Adaptive systems multi-objective function optimization Optimization methods Control systems Adaptive control clonal selection principle artificial immune systems Programmable control Automatic control Systems engineering and theory Immune system Power engineering and energy
Content Type	Text
Resource Type	Article

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An Adaptive Multi-objective Immune Optimization Algorithm