elite dn% form the elite particle set exactly as in the ce method nextthe elite particles are "splitinto bn/ elite children particlesadding one extra child to some of the elite particles to ensure that the total number of children is again the purpose of line is to randomize which elite particles receive an extra child lines - describe how the children of the -th elite particle are generated firstin line we select one of the other elite particles uniformly at random the same line defines an -dimensional vector si whose components are the absolute differences between the vectors (iand (imultiplied by constant that is| ( ), ( ), | ( ), ( ), si | (ix( : | ( ), ( ), nexta uniform random permutation of ( nis simulated (see exercise lines - describe howstarting from candidate child point yeach coordinate of is resampledin the order determined by pby adding standard normal random variable to that componentmultiplied by the corresponding component of si (line if the resulting has function value that is less than that of ythen the new candidate is accepted otherwisethe same coordinate is tried again if no improvement is found in maxtry attemptsthe original component is retained this process is performed for all elite samplesto produce the first-generation population the procedure is then repeated for iterations until some stopping criterion is mete when the best found function value does not change for number of consecutive iterationsor when the total number of function evaluations exceeds some threshold the best found function value and corresponding argument (particleare returned at the conclusion of the algorithm the input variable maxtry governs how much computational time is dedicated to updating component in most cases we have encounteredthe choices and maxtry work well empiricallyrelatively high value for work wellsuch as or even the latter case means that at each stage all samples from yt- carry over to the elite set xt example (test problem hock and schittkowski [ provide rich source of test problems for multiextremal optimization challenging one is problem where the goal is to find so as to minimize the function xj (xx ln = subject to the following set of constraintsx xj where the constants {ci are given in table