NDLI: Ant-genetic algorithms based on multi-objective optimization

Content Provider	IEEE Xplore Digital Library
Author	Xianmin Wei
Copyright Year	2011
Description	Author affiliation: Computer and Communication Engineering School of Weifang University, China (Xianmin Wei)
Abstract	In this paper, a new algorithm called multi-objective ant-genetic algorithms, which is based on the continuous space optimization is presented to solve constrained multi-objective function optimization problems. For the trait of multi-objective optimization, we define the pheromone instruction inheritance searching strategy and the method of pheromone updating. Then we combine four means of pheromone instruction inheritance searching, introduction of excellent decision-making, decision set updating and changing algorithm termination condition together so that the constringent speed of searching has improved a lot and the quantity of Pareto optimal decisions were controlled, also the distributing area of decisions were enlarged, the diversity of the swarm was maintained. At the same time, the termination conditions of multi-objective ant-genetic algorithms were presented. In the end, an example was listed to prove that the algorithms were effective, and it can find a group of widely distributed Pareto optimal decisions.
Starting Page	1815
Ending Page	1818
File Size	533817
Page Count	4
File Format	PDF
ISBN	9781457715860
e-ISBN	9781457715877
DOI	10.1109/ICCSNT.2011.6182321
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-12-24
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Pareto optimal decisions Ant-genetic algorithms Constrained multi-objective optimization Boundary conditions Optimization
Content Type	Text
Resource Type	Article

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