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Extra resources for AMD 32-Bit Microprogrammable Products AM29C300, 29300

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1 .. 1 .. 2 3 .. . 3 .. Generation rule Corresponding Matrix B: Created from Matrix A 3 .. 1 .. 4 .. 2 4 .. . 2 .. 2 .. 3 0 .. . 0 .. Generation rule Corresponding Matrix C: Created from Matrix B 0 .. 2 .. 1 .. 3 1 .. . 3 .. 3 .. 0 4 .. . 4 .. Generation rule Corresponding Matrix D: Created from Matrix C 4 .. 3 .. 2 .. 0 2 .. . 0 .. 0 .. 4 1 .. . 1 .. After the creation of all the matrices, all the design variables are decoded and mapped for the considered design variable range.

Eng Optim 38(2):129–154 14. Farmer JD, Packard N, Perelson A (1986) The immune system, adaptation and machine learning. Physica 22:187–204 15. Geem ZW, Kim JH, Loganathan GV (2001) A new heuristic optimization algorithm: Harmony Search. Simul, the Soc for Model and Simul Int 76(2):60–68 16. Holland J (1975) Adaptation in natural and artificial systems. University of Michigan Press, Ann Arbor 17. Hui L, Zixing C, Yong W (2010) Hybridizing particle swarm optimization with differential evolution for constrained numerical and engineering optimization.

Solution is updated after the employed bee phase by following the search mechanism of differential evolution and hence it combines the strength of both the algorithms. 4 HGABC ABC and GA are also having different searching capability and the searching mechanism. ABC is good in the exploration of the search space while GA uses both exploration and exploitation for finding the solution. HGABC is developed to combine the advantages of both ABC and DE. HGABC also starts with the initial population and updates the solution by following the searching mechanism of the employed bees in ABC.

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AMD 32-Bit Microprogrammable Products AM29C300, 29300


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