Pricing multidimensional options presents considerable difficulties and remains a crucial focus in large-scale finance. A European call option provides the holder with the right, but not the obligation, to purchase a specified quantity of an underlying asset (S) at a predetermined strike price (E) on a future date (T). Monte Carlo and quasi-Monte Carlo techniques are powerful methods for tackling a range of financial problems, including option pricing. This paper tackles the challenge of accurately determining the fair value of European-style options in two or more dimensions. Monte Carlo methods are particularly advantageous and effective in addressing pricing problems, especially in higher dimensions. In this work, we introduce simulation optimization techniques that leverage low-discrepancy sequences alongside variance reduction strategies to enhance the precision of standard approaches for European-style options. Enhancing accuracy is essential for obtaining more reliable pricing outcomes. Moreover, this approach proves beneficial in scenarios where other deterministic methods fall short, such as in high-dimensional cases, complex contract structures, and other challenging situations.