Taboo evolutionary programming: a new method of global optimization
نویسندگان
چکیده
We introduce taboo evolutionary programming, a very efficient global optimization method which combines features of single-point mutation evolutionary programming (SPMEP) and taboo search. As demonstrated by solving 18 benchmark problems, the algorithm is not trapped in local minima and quickly approaches the global minimum. The results are superior to those from SPMEP, fast evolutionary programming and generalized evolutionary programming. The method is easily applicable to real-world problems, and the central idea may be introduced into other algorithms.
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