LAUSR

Abstract The hybrid social spider optimization (SSO) algorithm is employed to estimate the thermophysical properties of phase change material for the first time. The enthalpy formulation of governing energy equation is solved by using the finite volume method and the radiative transfer equation is computed by using the discrete ordinate method. Two hybrid algorithms, namely the differential evolution-SSO (DE-SSO) and simplex method-SSO (SM-SSO) algorithms, are proposed to improve the search ability and computation efficiency of the inverse technique. The scattering albedo, boundary emissivity, conduction-radiation parameter, and Stefan number are estimated simultaneously. All the results demonstrate that the hybrid SSO algorithms are robust and effective for solving simultaneous estimation tasks even with measurement noise and DE-SSO algorithm achieves the best performance in terms of computational accuracy and convergence velocity. Furthermore, the effect of population size on the reconstruction results is also investigated and a suggested value is given.