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We study a variant of the competitive facility location problem, in which a company is to locate new facilities in a market where competitor's facilities already exist. We consider the scenario where only a limited number of possible attractiveness levels is available, and the company has to select exactly one level for each open facility. The goal is to decide the facilities' locations and attractiveness levels that maximize the profit. We apply the gravity-based rule to model the behavior of the customers and formulate a multi-ratio linear fractional 0-1 program. Our main contributions are the exact solution approaches for the problem. These approaches allow for easy implementations without the need for designing complicated algorithms and are "friendly" to the users without a solid mathematical background. We conduct computational experiments on the randomly generated datasets to assess their computational performance. The results suggest that the mixed-integer quadratic conic approach outperforms the others in terms of computational time. Besides that, it is also the most straightforward one that only requires the users to be familiar with the general form of a conic quadratic inequality. Therefore, we recommend it as the primary choice for such a problem.