geometric programming

The high risk of operational facilities and processes in strategic industries has made the continuous effort of operations managers to improve system reliability an undeniable necessity. The existing knowledge in fuzzy sets limits the sum of degrees of membership and non-membership of each element to more than one. However, in the real world, many ill-defined or highly complex situations require more consideration that is careful. Unlike normal fuzzy sets, the spherical fuzzy set pays attention to the degree of uncertainty of each element in decision-making situations and the degree of membership and non-membership. In addition, to help generalize the decision set, it considers the sum of squares of each membership function to be less than or equal to one. Achieving the success function is determined by maximizing the degree of membership and minimizing the degree of non-membership and uncertainty of each objective function in the spherical fuzzy set. Therefore, this paper develops a new algorithm based on the spherical fuzzy set called the spherical fuzzy geometric programming problem in system reliability. To evaluate the performance of the proposed algorithm, a descriptive example in the field of the rolling process of aluminum products is modeled in the form of a dual-objective problem, including maximization of reliability and minimization of cost.