THE SIMPLEX-SIMULATED ANNEALING APPROACH TO CONTINUOUS NONLINEAR OPTIMIZATION

An algorithm suitable for the global optimization of nonconvex continu ous unconstrained and constrained functions is presented. The scheme i s based on a proposal by Press and Teukolsky (Comput. Phys. 5(4), 426, 1991) that combines the non-linear simplex and simulated annealing al gorithms. A non-equilibrium variant will also be presented, whereby th e cooling schedule is enforced as soon as an improved solution is obta ined. The latter is shown to provide faster execution times without co mpromising the quality of the attained solutions. Both the algorithm a nd its non-equilibrium variant were tested with several severe functio ns published in the literature. Results for nine of these functions ar e compared with those obtained employing a robust adaptive random sear ch method and the Nelder and Mead simplex method (Comput. J. 7, 308, 1 965). The proposed approach is shown to be more robust and more effici ent in what concerns the overcoming of difficulties associated with lo cal optima, the starting solution vector and the dependency upon the r andom number sequence. The results obtained reveal the adequacy of the algorithm for the global optimization of a broad range of problems en countered in chemical engineering practice. (C) 1996 Elsevier Science Ltd