Abstract: Even though literally the optimization algorithms lead to local optimum points sometimes it may possible in chemical engineering problems which may lead to two complex and non-convex and non linear problems. The global optimization of such a problem is one of the toughest NP (Non deterministic Polynomial time) hard problems. Many problems in many cases cannot be solved in a reasonable time span if we depend only on N (deterministic Polynomial algorithms time) type that are theoretically guaranteed to find the global optimum. Generally, stochastic algorithms, which do not guarantee the global optimality of the obtained solution, are suitable for large problems, but not efficient when there are too many equality constraints. Therefore, an algorithm suitable for general chemical process optimization problems is proposed in this paper, which is based on a feasible point strategy and combination of a stochastic global algorithm and a deterministic local algorithm

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