Improving Evolutionary Algorithms in a Continuous Domain by Monitoring the Population Midpoint
本文提出监测种群中点可提升连续域中进化算法的效率，从理论上论证了该假设，并在CEC2005和CEC2013基准集上通过实验验证了其有效性。
It is advocated that monitoring the population midpoint allows for improving the efficiency of population-based evolutionary algorithms (EAs) in ℝ <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</sup> . The theoretical motivation supporting this hypothesis is provided in this letter, and this phenomenon is empirically confirmed for selected typical EAs by a series of tests for fitness functions contained in the CEC2005 and CEC2013 benchmark sets.