{"push_id":920095345,"size":1,"distinct_size":1,"ref":"refs/heads/master","head":"b6cb031af51fb5fff2148938596315a4cdc5c3e6","before":"45b1dece669f0fc156866ed7f9ba4d67e7cc8375","commits":[{"sha":"b6cb031af51fb5fff2148938596315a4cdc5c3e6","author":{"email":"62bf0da6512f8acb6740798118520af8278ecabd@googlemail.com","name":"Andres-Hernandez"},"message":"Global Optimizers\n\n4 Different Global Optimizers with various flavours: simulated\nannealing, particle swarm optimization, firefly algorithm, and\ndifferential evolution.\n\nHybrid Simulated Annealing: a Boltzmann-like simulated annealing\noptimizer, and which also takes a possible local optimizer to run upon\nfinding a new best solution.\n\nParticle Swarm Optimization (PSO) of different varieties\n- Canonical PSO (with constriction factor or inertia factor)\n- Three different topologies are provided: global, k-neighbors, and\nclubs\n- Different inertia implementations are provided: trivial constant\ninertia, simple random inertia, decreasing inertia by iteration,\nadaptive inertia, and a levy flight inertia.\n\nA hybrid Firefly Algorithm (FA) that mixes FA with a Differential\nEvolution (DE) optimizer. The population is divided into two\nsubpopulations ordered by the value. Each iteration, the population with\nthe best solutions is evolved according to FA, the other subpopulation\nis evolved according to DE. The size of the subpopulations are\ncontrolled parameters, and if the subpopulation of FA is set to 0, then\nthe optimizer defaults to a fully fledged DE.\n- Two different intensities are provided: exponential and inverse square\nlaw\n- Three different random walk noises are provided: gaussian random walk,\nlevy flight random walk, and a gaussian random walk with decreasing step\nsize as the number of iterations continue.\n\nTwo extra files contain helper classes:\n-IsotropicRandomWalk is a random walk, whose every step is taken\nrandomly from a d-dimensional sphere, with the radius of the sphere\nsampled from a distribution provided as a template parameter\n-LevyFlightDistribution is a distribution that implements a levy flight\ndistribution, a.k.a. Pareto Type I, and which is fully compatible with\nBoost Random.","distinct":true,"url":"https://api.github.com/repos/Andres-Hernandez/QuantLib/commits/b6cb031af51fb5fff2148938596315a4cdc5c3e6"}]}