A SIMULATED ANNEALING APPROACH TO THE SOLUTION OF MINLP PROBLEMS

An algorithm (M-SIMPSA) suitable for the optimization of mixed integer non-linear programming (MINLP) problems is presented. A recently prop osed continuous non-linear solver (SIMPSA) is used to update the conti nuous parameters, and the Metropolis algorithm is used to update the c omplete solution vector of decision variables. The M-SIMPSA algorithm, which does not require feasible initial points or any problem decompo sition, was tested with several functions published in the literature, and results were compared with those obtained with a robust adaptive random search method. For ill-conditioned problems, the proposed appro ach is shown to be more reliable and more efficient as regards the ove rcoming of difficulties associated with local optima and in the abilit y to reach feasibility. The results obtained reveal its adequacy for t he optimization of MINLP problems encountered in chemical engineering practice. (C) 1997 Elsevier Science Ltd.