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The Monte Carlo approach is a valuable and flexible computational tool in modern finance, and is one of numerical procedures used for solving option valuation problems. In recent years the complexity of numerical computation in financial theory and practice has increased and require more computational power and efficiency. Monte Carlo simulation is one of the numerical computation methods used for financial engineering problems.

The drawback of Monte Carlo simulation is computationally intensive and time-consuming. In attempt to tackle such an issue, many recent applications of the Monte Carlo approach to security pricing problems have been discussed with emphasis on improvements in efficiency. This paper presents a novel approach combining system simulation with GA-based optimization to pricing options. This paper shows how the proposed approach can significantly resolve the option pricing problem.