Fuzzy relation equations (FRE) are a useful formalism with a broad number of applications in different computer science areas. Testing if a solution exists and, if so, computing the unique greatest solution is straightforward. In contrast, the computation of minimal solutions is more complex. In particular, even in FRE with a very simple structure, the number of minimal solutions can increase exponentially. However, minimal solutions are immensely useful since, under mild conditions, they (together with the greatest solution) allow one to describe the entire space of solutions to an FRE. The main result of this work is a new method for enumerating the set of minimal solutions. It works by establishing a relationship between coverings of FRE and maximal independent elements of (hyper-)boxes. We can thus make efficient enumeration methods for maximal independent elements of (hyper-)boxes applicable also to our setting of FRE, where the operator considered in the composition of fuzzy relations only needs to preserve suprema of arbitrary subsets and infima of non-empty subsets. More specifically, we thus show that the enumeration of the minimal solutions of an FRE can be done with incremental quasi-polynomial delay.

Extended multi-adjoint logic programming is a non-monotonic logic programming framework whose semantics is defined in terms of stable models. This paper will focus on the theoretical development of a syntactical sufficient condition for the existence and uniqueness of stable models in extended multi-adjoint logic programming, through the notion of stratification. Namely, we will detail a constructive method for the computation of the unique stable model of a given stratified extended multi-adjoint logic program. As a consequence, this study will be an interesting alternative to the semantical sufficient conditions for the existence and the uniqueness of stable models, given in the literature for multi-adjoint normal logic and extended multi-adjoint logic programs.

A method to solve a latticed optimization problem constrained by a bipolar fuzzy relation equation is presented in this paper, under the hypothesis of a partially monotonic objective function. The solving strategy consists of transforming the problem into optimizing an order-preserving function in all arguments subject to another bipolar fuzzy relation equation. As a result, all the solutions of the original optimization problem can be deduced from the extremal elements of the feasible domain of the transformed problem. The presented approach embraces the particular case of linear optimization constrained by bipolar fuzzy relation equations.

Bipolar max-⁎ equations, with ⁎ a triangular norm, have recently become a popular research topic embedded in the broad field of fuzzy relational equations. In this paper, we lift the work from the restrictive setting of the real unit interval — obfuscating the underlying lattice-theoretical essence — to the general setting of complete distributive symmetric residuated lattices, allowing to build upon the vast body of knowledge on unipolar sup-⁎ equations on complete distributive residuated lattices. We determine the full solution set, with particular emphasis on the extremal solutions, of a bipolar sup-⁎ equation in case the right-hand side is a join-irreducible element. The results are illustrated by means of ample examples.

Bipolar fuzzy relation equations are given from the fuzzy relation equations introduced by Sanchez in the 1980s considering a negation operator in the equations. Numerous applications require variables that show a bipolar character such as decision making and revenue management, hence the importance of studying bipolar fuzzy relation equations. According to the literature, bipolar max-min equations have already been studied and a characterization of their solutions, by means of a finite set of maximal and minimal solution pairs, has been provided. This paper will present a first study on bipolar max-product fuzzy relation equations with one equation containing different variables, which includes different interesting properties in order to guarantee both their solvability and the existence of the greatest (least) solution or maximal (minimal) solutions. Moreover, a characterization of the solvability of a particular system of two bipolar max-product fuzzy relation equations is given.