In this paper, we propose the use of a dimensional decomposition procedure together with lexicographic parametric programming to reduce computational burden when identifying the efficient decision making units in Data Envelopment Analysis (DEA). The use of lexicographic parametric programming makes it possible to develop an efficient algorithm for the problems with few inputs and outputs. That’...

Programming languages theory is full of problems that reduce to proving the consistency of a logic, such as the normalization of typed lambda-calculi, the decidability of equality in type theory, equivalence testing of traces in security, etc. Although the principle of transfinite induction is routinely employed by logicians in proving such theorems, it is rarely used by programming languages r...

Multiobjective shortest path problems are computationally harder than single objective ones. In particular, execution time is an important limiting factor in exact multiobjective search algorithms. This paper explores the possibility of improving search performance in those cases where the interesting portion of the Pareto front can be initially bounded. We introduce a new exact label-setting a...

In this paper fully fuzzy linear programming (FFLP) problem with both equality and inequality constraints is considered where all the parameters and decision variables are represented by non-negative trapezoidal fuzzy numbers. According to the current approach, the FFLP problem with equality constraints first is converted into a multi–objective linear programming (MOLP) problem with crisp const...

Possibilistic decision theory has been proposed twenty years ago and has had several extensions since then. Because of the lack of decision power of possibilistic decision theory, several refinements have then been proposed. Unfortunately, these refinements do not allow to circumvent the difficulty when the decision problem is sequential. In this article, we propose to extend lexicographic refi...