Adaptive reservoir evolutionary algorithm: An evolutionary on-line adaptation scheme for global function optimization

被引:2
|
作者
Munteanu, C [1 ]
Rosa, AC [1 ]
机构
[1] Univ Tecn Lisboa, Inst Sistemas & Robot, LaSEEB, Inst Super Tecn, P-1049001 Lisbon, Portugal
关键词
Evolutionary Algorithms; fitness landscape; decision process; on-line adaptation; memetic-algorithms; metaheuristics; global optimization;
D O I
10.1007/s10732-005-5430-7
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper introduces a novel global optimization heuristic algorithm based on the basic paradigms of Evolutionary Algorithms (EA). The algorithm greatly extends a previous strategy proposed by the authors in Munteanu and Lazarescu ( 1998). In the newly designed algorithm the exploration/exploitation of the search space is adapted on-line based on the current features of the landscape that is being searched. The on-line adaptation mechanism involves a decision process as to whether more exploitation or exploration is needed depending on the current progress of the algorithm and on the current estimated potential of discovering better solutions. The convergence with probability I in finite time and discrete space is analyzed, as well as an extensive comparison with other evolutionary optimization heuristics is performed on a set of test functions.
引用
收藏
页码:555 / 586
页数:32
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