Data from: A global optimization paradigm based on change of measures

A global optimization framework, COMBEO (Change Of Measure Based Evolutionary Optimization), is proposed. An important aspect in the development is a set of derivative-free additive directional terms, obtainable through a change of measures en route to the imposition of any stipulated conditions aimed at driving the realized design variables (particles) to the global optimum. The generalized setting offered by the new approach also enables several basic ideas, used with other global search methods such as the particle swarm or the differential evolution, to be rationally incorporated in the proposed set-up via a change of measures. The global search may be further aided by imparting to the directional update terms additional layers of random perturbations such as 'scrambling' and 'selection'. Depending on the precise choice of the optimality conditions and the extent of random perturbation, the search can be readily rendered either greedy or more exploratory. As numerically demonstrated, the new proposal appears to provide for a more rational, more accurate and, in some cases, a faster alternative to many available evolutionary optimization schemes.exampleexperimentThis is the main file for solving global optimization problems. In this specific case pseudo-code 2 has been used for demonstrating the performance the algorithm. All the input values (i.e. dimension of problem, minimum and maximum function evaluations) are to be given here. To run this code, except the functions uploaded herein plese use the two function benchmarks.m and fgeneric.m from https://www.lri.fr/~hansen/cmaes_inmatlab.html which is an open sorce platform.MY_OPTIMIZERThe specific optimization algorithm is written here. For solving the global optimization problem with a different algorithm, only this function needs to be modified.new_KS_EnKF_gain_matrixThis function creates the gain matrix, defined in the main manuscript, which is required in pseudo code 2 for giving the evolving particle proper directionality.phase_KThe phase data (attached) for the illustrative example in Section 5.2phase_KThe phase data (attached) for the illustrative example in Section 5.