We use a genetic algorithm to attack the receiver function inversion problem where the objective is to retrieve shear wave velocities of rock layers as a function of depth. The receiver function inversion is a non–linear, multi–modal, and multi–parameter optimization problem suited for genetic algorithms. We implement a three operator genetic algorithm consisting of selection, single–point cros...

Abstract We improve convergence speed by two orders of magnitude and the global exploration capabilities particle swarm optimization (PSO) through targeted position-mutated elitism (TPME). The proposed fast-converging TPME operator requires a fitness-based classification technique to categorize particles. introduced is motivated its simplicity, low memory requirements, automated termination cri...

We analyse how the conventional Genetic Algorithm can be stripped down and reduced to its basics. We present a minimal, modified version that can be interpreted in terms of horizontal gene transfer, as in bacterial conjugation. Whilst its functionality is effectively similar to the conventional version, it is much easier to program, and recommended for both teaching purposes and practical appli...