A novel dynamic population based evolutionary algorithm for revised multimodal function optimization problem
Qin Jun, Lishan Kang · 2004
A revised definition about the task of multi-modal function optimization problem (called "rMOP"), which is to locate all optimal peaks including global and local optima, is presented. Then, a novel evolutionary algorithm aimed to rMOP with dynamic population (DPEA) is given. In DPEA, the initial population size is specified randomly. In the process of evolution, the size of population is tuned by a mechanism called "suppression" to delete crowded individuals and a process called "introduction of new individuals" to reinforce the global searching. Some experiments show that the population size of DPEA converges to the number of all peaks of the test function adaptively.