RETRACTED ARTICLE: A Multi-agent Based Self-adaptive Genetic Algorithm for the Long-term Car Pooling Problem

An agent-based Virtual Organization is a complex entity where dynamic collections of agents agree to share resources in order to accomplish a global goal or offer a complex service. An important problem for the performance of the Virtual Organization is the distribution of the agents across the computational resources. The final distribution should provide a good load balancing for the organization. In this article, a genetic algorithm is applied to calculate a proper distribution across hosts in an agent-based Virtual Organization. Additionally, an abstract multi-agent system architecture which provides infrastructure for Virtual Organization distribution is introduced. The developed genetic solution employs an elitist crossover operator where one of the children inherits the most promising genetic material from the parents with higher probability. In order to validate the genetic proposal, the designed genetic algorithm has been successfully compared to several heuristics in different scenarios.

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Multi-agent Based Distributed Genetic Algorithm Applied to the Optimization of Self-Adaptive PID Parameters of Hydro-turbine

2012 Second International Conference on Intelligent System Design and Engineering Application ◽

10.1109/isdea.2012.576 ◽

2012 ◽

Cited By ~ 2

Author(s):

Anbo Meng ◽

Xiangang Peng ◽

Hao Yin

Keyword(s):

Genetic Algorithm ◽

Agent Based ◽

Hydro Turbine ◽

Multi Agent ◽

Distributed Genetic Algorithm ◽

Self Adaptive

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Constrained self-adaptive genetic algorithm

SeMA Journal ◽

10.1007/s40324-016-0068-y ◽

2016 ◽

Vol 73 (3) ◽

pp. 261-285 ◽

Cited By ~ 1

Author(s):

Tapan Kumar Singh

Keyword(s):

Genetic Algorithm ◽

Adaptive Genetic Algorithm ◽

Self Adaptive

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Crowding Self-Adaptive Genetic Algorithm and Its Application in Facility Layout Problem

International Journal of Advancements in Computing Technology ◽

10.4156/ijact.vol4.issue7.23 ◽

2012 ◽

Vol 4 (7) ◽

pp. 203-212

Author(s):

Yi Zhang ◽

Hu Zhang ◽

Zheng Liu ◽

Huifang Li

Keyword(s):

Genetic Algorithm ◽

Facility Layout ◽

Adaptive Genetic Algorithm ◽

Layout Problem ◽

Facility Layout Problem ◽

Self Adaptive

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An Adaptive Genetic Algorithm of Adjusting Sensor Acquisition Frequency

Sensors ◽

10.3390/s20040990 ◽

2020 ◽

Vol 20 (4) ◽

pp. 990 ◽

Cited By ~ 4

Author(s):

Feng Chen ◽

Shouzhi Xu ◽

Ying Zhao ◽

Hui Zhang

Keyword(s):

Genetic Algorithm ◽

Data Acquisition ◽

Reducing Power ◽

Sensor Nodes ◽

Monitoring Data ◽

Adaptive Genetic Algorithm ◽

Environment Monitoring ◽

Wireless Sensor Nodes ◽

Acquisition Strategies

Portable meteorological stations are widely applied in environment monitoring systems, but they are always limited in power-supplying due to no cable power, especially in long-term monitoring scenarios. Reducing power consumption by adjusting a suitable frequency of sensor acquisition is very important for wireless sensor nodes. The regularity of historical environment data from a monitoring system is analyzed, and then an optimization model of an adaptive genetic algorithm for environment monitoring data acquisition strategies is proposed to lessen sampling frequency. According to the historical characteristics, the algorithm dynamically changes the recent data acquisition frequency so as to collect data with a smaller acquisition frequency, which will reduce the energy consumption of the sensor. Experiment results in a practical environment show that the algorithm can greatly reduce the acquisition frequency, and can obtain the environment monitoring data changing curve with less error compared with the high-frequency acquisition of fixed frequency.

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