In any organization, the process of selecting employees is mostly through the traditional methods. These methods do not support hypothetical situations that result in an error in the selection process. In this research paper, a method based on fuzzy triangular number has been used for the recruitment process of individuals. The selection process used is completely different from previously discovered methods. Basically, we use a modified solution to the assignment problem to select the right person by this process. For such type of application areas, genetic algorithm is widely used approach so the authors may use this approach to get the optimum result. Here we also taken GA and solve the selection process through genetic algorithm approach using fuzzy ranking method. During the process of genetic algorithm, we use heuristic crossover and uniform mutation to find the optimal solution. The solution obtained by this process gives a more optimal solution than other methods by which an organization selects more competent/qualified employees than the former, which is useful for that organization in the future. This research paper shows the optimum solution of 10 best applicants from a group of 50 selected applicants through this process.

在任何组织中，selecting选员工的过程通常都是通过传统方法进行的。这些方法不支持在选择过程中导致错误的假设情况。在本文中，基于模糊三角数的方法已被用于个人的招聘过程。使用的选择过程与以前发现的方法完全不同。基本上，我们对分配问题使用修改后的解决方案，以通过此过程选择合适的人。对于这种类型的应用领域，遗传算法被广泛使用，因此作者可以使用这种方法来获得最佳结果。在这里，我们还采用遗传算法，并采用模糊排序法通过遗传算法来解决选择过程。在遗传算法的过程中，我们使用启发式交叉和统一突变来找到最佳解决方案。与其他方法相比，通过此过程获得的解决方案为组织选择了比前者更胜任/合格的员工，从而提供了更好的解决方案，这对将来的组织很有用。该研究论文显示了通过此过程从50个选定申请人中选出的10个最佳申请人的最佳解决方案。