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Penalty functions are frequently used for dealing with constraints in constrained optimization. Among different types of penalty functions, dynamic and adaptive penalty functions seem effective, since the penalty coefficients in them are adjusted based on the current generation number (or number of solutions searched) and feedback from the search. In this paper, we propose dynamic and adaptive versions...
Penalty functions are frequently employed for handling constraints in constrained optimization problems (COPs). In penalty function methods, penalty coefficients balance objective and penalty functions. However, finding appropriate penalty coefficients to strike the right balance is often very hard. They are problems dependent. Stochastic ranking (SR) and constraint-domination principle (CDP) are...
JADE is a recent adaptive version of nature inspired algorithm, Differential Evolution (DE). It has shown considerable performance improvement on a set of well studied benchmark functions. This paper studies whether the performance of JADE can be improved further by changing its random population initialization with centroid based population initialization. The new algorithm is known as Centroid-based...
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