Transplant Evolution For Optimization Of General Controllers

Optimization of the throughput of computer network based on Transplant Evolution

“…In the case of finding the optimal solution in the first generation, the algorithm is terminated, otherwise creates a new population of individuals by crossover and mutation operators, with the direct use of already created parent's object tree structures (it is analogy as transplantation of already created organs, without necessary know-ledge of DNA -"Transplant Evolution (TE)"). If the result of TE needs some numerical parameters (for example num in [10], the second level with Differential Evolution (DE) is used for optimization their parameter setting. The DE gives better results in finding optimal values of unknown numerical parameters that are expressed in the form of real numbers, then in the GE.…”

“…The Transplant Evolution algorithm (TE) combines the best properties of Genetic Programming (GP) [1] and Grammatical Evolution (GE) [4], [5], [8], [9], and [10]. The Two-Level Transplant Evolution (TLTE) in addition to that uses the Differential Evolution algorithm (DE).…”

“…time needed for solution finding and number of suitable variants of topology. The limit of the throughput of computer network is based on the principles of clustering and using parallel evolutionary algorithms (PEA) [2], [8] - [10].…”

Analytical Programming - a Novel Approach for Evolutionary Synthesis of Symbolic Structures

“…Yet another new technique is the so called Transplant Evolution, see Weisser & Osmera (2010b), Weisser & Osmera (2010a) and Weisser et al (2010) which is closely associated with the conceptual paradigm of AP, and modified for GE. GE was also extended to include DE by O'Neill & Brabazon (2006).…”