TY - JOUR
T1 - How to measure adaptation complexity in evolvable systems - A new synthetic approach of constructing fitness functions
AU - Wang, Pan
AU - Zhang, Jianjian
AU - Xu, Li
AU - Wang, Hong
AU - Feng, Shan
AU - Zhu, Haoshen
PY - 2011/8/1
Y1 - 2011/8/1
N2 - How to measure the adaptation complexity effectively is an open issue in natural or artificial systems. In this paper, some essential characteristics of adaptation in evolvable systems and the importance/complexity of constructing multi-objective fitness functions in evolutionary computation are analyzed. Based on the authors' previous work on single-objective normalization, a general method is put forward for multi-objective decision making and optimization with its key idea of decomposing the process of constructing fitness functions into their basic units (classes). Then, the issues of determining the corresponding mathematical models and their parameters as well as the issue of integrating all the fitness functions are discussed. Variable weights/objective synthesis is also briefly discussed. A technique in multi-input-multi-output control systems is illustrated to show the usefulness of the method. © 2011 Published by Elsevier Ltd.
AB - How to measure the adaptation complexity effectively is an open issue in natural or artificial systems. In this paper, some essential characteristics of adaptation in evolvable systems and the importance/complexity of constructing multi-objective fitness functions in evolutionary computation are analyzed. Based on the authors' previous work on single-objective normalization, a general method is put forward for multi-objective decision making and optimization with its key idea of decomposing the process of constructing fitness functions into their basic units (classes). Then, the issues of determining the corresponding mathematical models and their parameters as well as the issue of integrating all the fitness functions are discussed. Variable weights/objective synthesis is also briefly discussed. A technique in multi-input-multi-output control systems is illustrated to show the usefulness of the method. © 2011 Published by Elsevier Ltd.
KW - Adaptation complexity
KW - Construction of fitness function
KW - Evolutionary computation
KW - Fuzzy control
KW - Measure
KW - Variable weights/objective synthesis
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U2 - 10.1016/j.eswa.2011.02.099
DO - 10.1016/j.eswa.2011.02.099
M3 - Article
SN - 0957-4174
VL - 38
SP - 10414
EP - 10419
JO - Expert Systems with Applications
JF - Expert Systems with Applications
IS - 8
ER -