Published: CABEQ 18 (4) (2004) 329–335
Paper type: Original Scientific Paper
Y. Özçelik and Z. Özçelik
The optimization models of chemical engineering processes are generally nonlinear and mixed integer, nonlinear in structure, and contain several equality and inequality constraints and bounds on variables. Mixed Integer Nonlinear programming problems (MINLP) can be solved using either gradient methods or stochastic methods. Gradient methods need to separate the problem to Mixed Integer Linear Programming (MILP) and Nonlinear Programming (NLP) problems and some special formulations where the continuity or convexity has to be imposed. In this work, an algorithm (SARAN) that was based on a simulated annealing algorithm of Corana1 was developed to solve MINLP problems. Then the algorithm and some alternatives for the basic steps of a simulated annealing were tested for 100 sequences of pseudo random numbers using 11 MINLP test problems. Finally the results were compared with the results of the M–SIMPSA2 for small and medium scaled problems.
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Mixed Integer Nonlinear Programming, Nonlinear Optimization, simulated annealing