Linear optimization with an arbitrary fuzzy relational inequality

In this paper, optimization of a linear objective function with fuzzy relational inequality constraints is investigated whereby an arbitrary function is considered as fuzzy composition. The feasible solution set is determined and compared with some common results in the literature. A necessary and sufficient condition and three other necessary conditions are presented to conceptualize the feasibility of the problem. It is shown that in general a lower bound is always attainable for the optimal objective value. Moreover, we prove that the optimal solution of the problem is obtained if the problem is defined by a non-decreasing or non-increasing function. An algorithm is presented to summarize the process and an example is described to illustrate the algorithm.