Performance evaluation of hybrid differential evolution approach for estimation of the strength of a heat source in a radiatively participating medium

Performance analysis and feasibility study of ant colony optimization, particle swarm optimization and cuckoo search algorithms for inverse heat transfer problems

“…The recordings of temperature at discrete regular times are modified systematically by introducing artificial measurement errors with the help of random numbers having normal (Gaussian) distribution with zero mean and unit standard deviation. These random errors are imposed onto the calculated exact temperatures as follows [24,73]:…”

“…Hence, these methods are more robust. Computational time is of course a concern for these methods [16] but with ever growing computational power, parallelization [19], modifications [20][21][22] and development of hybrid methods [23][24][25], these methods can substitute http://dx.doi.org/10.1016/j.ijheatmasstransfer.2015.05.015 0017-9310/Ó 2015 Elsevier Ltd. All rights reserved. the conventional methods.…”

Estimation of operating parameters of a reheat regenerative power cycle using simplex search and differential evolution based inverse methods

“…. ; V D i;G g corresponding to each target vector X i,G is generated using the following equation [20,41,44,45].…”

Space-Dependent Sobolev Gradients as a Regularization for Inverse Radiative Transfer Problems

“…The solution of the inverse problem is obtained through the minimization of a cost function that measures the misfit between the predictions (solution of the forward problem) and some experimental measurements. Though zero-order optimization methods may be used for relatively similar problems [31,32], gradient-type methods are dealt with in this paper because of the large dimension of the parameter space. Due to the ill-posed nature of the inverse problem, unstable solutions may be obtained if no regularization is performed.…”