Comparison of optimization algorithms for inverse FEA of heat and mass transport in biomaterials

Inverse analysis has become increasingly important for estimating coefficient values for heat and moisture transport in complex biological materials. With this approach, an improved accuracy of predicting transport processes can be obtained as compared to simulations based on coefficients determined by experimental procedures only. Such improvement is indispensable for successful analyzing, designing and managing most technological processes in the agri-food and forest products industries. In recent years, many optimization algorithms have been developed to solve inverse problems. Performance of the following algorithms was analyzed and compared in this paper: simulated annealing, tabu search, genetic algorithm, variable metric algorithm and trust region algorithm. Results demonstrated that although all the algorithms were able to estimate the coefficients, there were differences in their performance and due to high computational complexity of the problem only the trust region procedure was acceptable.