Data-Driven Based State Transition Algorithm for Dynamic Optimization

Most evolutionary algorithms solve the optimization problems by iteratively calculating the values of the objective functions. However, such explicit objective functions may not exist in solving many process industry optimization problems, especially when these processes have time varying dynamics,...

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Vydané v:	2019 IEEE Symposium Series on Computational Intelligence (SSCI) s. 1091 - 1096
Hlavní autori:	Zhang, Yunxiang, Zhou, Xiaojun, Yang, Chunhua
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.12.2019
Predmet:	Approximation algorithms Control vector parametrization Data-driven Dynamic optimization Evolutionary computation Heuristic algorithms Linear programming Optimization Process control State transition algorithm
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