scholarly journals Evolutionary Algorithms for Wireless Communications — A Review of the State-of-the art

10.5772/59147 ◽  
2014 ◽  
Author(s):  
Sotirios K. Goudos
Keyword(s):  
Wireless Communications ◽  
Evolutionary Algorithms ◽  
State Of The Art ◽  
The State

scholarly journals Evolutionary Manytasking Optimization Based on Symbiosis in Biocoenosis

2019 ◽  
Vol 33 ◽  
pp. 4295-4303 ◽  
Author(s):  
Rung-Tzuo Liaw ◽  
Chuan-Kang Ting
Keyword(s):  
Evolutionary Algorithms ◽  
Evolutionary Algorithm ◽  
State Of The Art ◽  
The State ◽  
Experimental Results ◽  
Benchmark Problems ◽  
Good Estimator ◽  
Multiple Tasks ◽  
Effectiveness And Efficiency ◽  
Evolutionary Multitasking

Evolutionary multitasking is a significant emerging search paradigm that utilizes evolutionary algorithms to concurrently optimize multiple tasks. The multi-factorial evolutionary algorithm renders an effectual realization of evolutionary multitasking on two or three tasks. However, there remains room for improvement on the performance and capability of evolutionary multitasking. Beyond three tasks, this paper proposes a novel framework, called the symbiosis in biocoenosis optimization (SBO), to address evolutionary many-tasking optimization. The SBO leverages the notion of symbiosis in biocoenosis for transferring information and knowledge among different tasks through three major components: 1) transferring information through inter-task individual replacement, 2) measuring symbiosis through intertask paired evaluations, and 3) coordinating the frequency and quantity of transfer based on symbiosis in biocoenosis. The inter-task individual replacement with paired evaluations caters for estimation of symbiosis, while the symbiosis in biocoenosis provides a good estimator of transfer. This study examines the effectiveness and efficiency of the SBO on a suite of many-tasking benchmark problems, designed to deal with 30 tasks simultaneously. The experimental results show that SBO leads to better solutions and faster convergence than the state-of-the-art evolutionary multitasking algorithms. Moreover, the results indicate that SBO is highly capable of identifying the similarity between problems and transferring information appropriately.

Efficient Portfolio Construction with the Use of Multiobjective Evolutionary Algorithms: Best Practices and Performance Metrics

2015 ◽  
Vol 14 (03) ◽  
pp. 535-564 ◽  
Author(s):  
K. Liagkouras ◽  
K. Metaxiotis
Keyword(s):  
Best Practices ◽  
Evolutionary Algorithms ◽  
Portfolio Optimization ◽  
Optimization Problem ◽  
Performance Metrics ◽  
State Of The Art ◽  
The State ◽  
Multiobjective Evolutionary Algorithms ◽  
Wide Range ◽  
Portfolio Optimization Problem

This paper provides a systematic study of the technologies and algorithms associated with the implementation of multiobjective evolutionary algorithms (MOEAs) for the solution of the portfolio optimization problem. Based on the examination of the state-of-the art we provide the best practices for dealing with the complexities of the constrained portfolio optimization problem (CPOP). In particular, rigorous algorithmic and technical treatment is provided for the efficient incorporation of a wide range of real-world constraints into the MOEAs. Moreover, we address special configuration issues related to the application of MOEAs for solving the CPOP. Finally, by examining the state-of-the-art we identify the most appropriate performance metrics for the evaluation of the relevant results from the implementation of the MOEAs to the solution of the CPOP.

Multiobjective evolutionary algorithms: A survey of the state of the art

2011 ◽  
Vol 1 (1) ◽  
pp. 32-49 ◽  
Author(s):  
Aimin Zhou ◽  
Bo-Yang Qu ◽  
Hui Li ◽  
Shi-Zheng Zhao ◽  
Ponnuthurai Nagaratnam Suganthan ◽  
...  
Keyword(s):  
Evolutionary Algorithms ◽  
State Of The Art ◽  
The State ◽  
Multiobjective Evolutionary Algorithms

scholarly journals Distributed evolutionary algorithms and their models: A survey of the state-of-the-art

2015 ◽  
Vol 34 ◽  
pp. 286-300 ◽  
Author(s):  
Yue-Jiao Gong ◽  
Wei-Neng Chen ◽  
Zhi-Hui Zhan ◽  
Jun Zhang ◽  
Yun Li ◽  
...  
Keyword(s):  
Evolutionary Algorithms ◽  
State Of The Art ◽  
The State ◽  
Distributed Evolutionary Algorithms

Securing emerging short range wireless communications: the state of the art

2014 ◽  
Vol 21 (6) ◽  
pp. 153-159 ◽  
Author(s):  
Kui Ren ◽  
Qian Wang ◽  
Di Ma ◽  
Xiaohua Jia
Keyword(s):  
Wireless Communications ◽  
Short Range ◽  
State Of The Art ◽  
The State
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