## Optimization dialog

The following boxes are described below: Ø Choose optimizer Ø DE: Differential Evolution parameters Ø HDE: Hybridized Differential Evolution Ø VBDE: Variable Birthrate Differential Evolution Ø IADE: Immune Accelerated Differential Evolution
### Choose optimizer - Optimizer: Select optimizer from the drop-down list. Only Differential Evolution is used in this thesis. - N = 1/Tol: Optimization is stopped when the standard deviation of cost in the population is lower than Tol, the reciprocal of N, the number entered in this box. - Minimum function value: Optimization is stopped if the cost becomes lower than this value. ### DE: Differential Evolution parameters - The parameters shown are those used for DE with binary crossover throughout the thesis. For details, see chapter 1. - Strategy: Select the DE strategy from the drop-down list. - perturbed: which vector is mutated - # difference: the number of differentials used in mutation - crossover: the type of crossover – binary or exponential - Number of parameters D: calculated automatically by FanOpt - Population size: should be roughly 10D for best results - Parameter bounds: not used currently - weighting factor F: controls strength of mutation - Crossover factor, CR: controls amount of crossover - Random number seed: initial seed for the (pseudo)-random number generator - Maximum # of generations: Optimization is stopped after this generation - Refresh: determines how often the screen is refreshed with the latest data ### HDE: Hybridized Differential Evolution - Hybridization with Downhill Simplex (DS) is activated by selecting the box - Simplex choice: Select the initial simplex (D+1 vectors) from the drop-down list. - D+1 best: least costly vectors in the population - 1 best, D random: single vector with least cost, plus D chosen at random - D+1 random: initial simplex is chosen completely at random - mutate on best: single vector with least cost, plus D vectors, each of which adds to one variable of the best the standard deviation of that variable in the population - Replacement choice: Select the manner in which vectors improved by DS replace those in the population - D+1 best: the new simplex replaces the best vectors in the population - D+1 worst: the new simplex replaces the best vectors in the population - D+1 random: the new simplex replaces D+1 vectors chosen at random - 1 best: the least costly vector in the new simplex replaces the vector that was previously best in the population - 1 random: the least costly vector in the new simplex replaces a population vector chosen at random - none: no population vector is replaced, but update the best vector in the population (used by DE/best/… and DE/rand-to-best/…) - Frequency: determines how often DS is run - # simplex iterations: determines the number of DS iterations used each time it is run ### VBDE: Variable Birthrate Differential Evolution - Select a birthrate cut-off value, BR, from [0,1]. - Use high BR values to keep most vectors from reproducing - Use BR=0 to de-activate VBDE. ### IADE: Immune Accelerated Differential Evolution - IADE is activated by selecting the box. - IADE conditions the antibodies to have characteristics of the antigens. - In v. 3.3, the immune conditioning occurs after every generation - In v. 3.5, the immune conditioning occurs only immediately following a DS run (in HDE) - PGA: The best PGA% of the population is chosen as antigens. - PBA: The worst PBA% of the population is chosen as antibodies. - PEA: At any given time, PEA% of the antibodies are exposed to a given antigen.