Multicanonical jump walk annealing assisted by tabu for dynamic optimization of chemical engineering processes
A hybrid methodology, viz., multicanonical jump walk annealing assisted by tabu list (MJWAT) is proposed for solving dynamic optimization problems in chemically reacting systems. This method combines the power of multicanonical sampling with the beneficial features of simulated annealing. Incorporating tabu list further enhances the efficiency of the method. The superior performance of the MJWAT is highlighted with the help of five benchmark case studies.
dynamic optimization simulated annealing monte carlo simulations multicanonical algorithms metaheuristics tabu conditions