We propose relational linear programming, a simple framework for combing linear programs (LPs) and logic programs. A relational linear program (RLP) is a declarative LP template defining the objective and the constraints through the logical concepts of objects, relations, and quantified variables. This allows one to express the LP objective and constraints relationally for a varying number of i...

in this paper, the cost and income efficiency models have been considered with regard to the multiple objective programming structures. for finding the efficient points in purposed molp problem, some various methods like lexicography & the weighted sum can be used. so by introducing the molp problem the cost & income efficiencies will be achieved. in the present study, the molp problem ...

There are several methods for solving fuzzy linear programming (FLP)problems. When the constraints and/or the objective function are fuzzy, the methodsproposed by Zimmermann, Verdegay, Chanas and Werners are used more often thanthe others. In the Zimmerman method (ZM) the main objective function cx is addedto the constraints as a fuzzy goal and the corresponding linear programming (LP)problem w...

Hyperbolic Programming (HP) –minimizing a linear functional over an affine subspace of a finite-dimensional real vector space intersected with the so-called hyperbolicity cone– is a class of convex optimization problems that contains well-known Linear Programming (LP). In particular, for any LP one can readily provide a sequence of HP relaxations. Based on these hyperbolic relaxations, a new Sh...

The objective function and the constraints can be formulated as linear functions of independent variables in most of the real-world optimization problems. Linear Programming LP is the process of optimizing a linear function subject to a finite number of linear equality and inequality constraints. Solving linear programming problems efficiently has always been a fascinating pursuit for computer ...

We show that solving linear programming (LP) relaxations of many classical NP-hard combinatorial optimization problems is as hard as solving the general LP problem. Precisely, the general LP can be reduced in linear time to the LP relaxation of each of these problems. This result poses a fundamental limitation for designing efficient algorithms to solve the LP relaxations, because finding such ...

Linear complementarity problem noted (LCP) becames in present the subject of many reseach interest because it arises in many areas and it includes the two important domains in optimization:the linear programming (LP) and the convex quadratic (CQP) programming. So the researchers aims to extend the results obtained in (LP) and (CQP) to (LCP). Differents classes of methods are proposed to solve (...

In this paper, the cost and income efficiency models have been considered with regard to the multiple objective programming structures. For finding the efficient points in purposed MOLP problem, some various methods like Lexicography & the weighted sum can be used. So by introducing the MOLP problem the cost & income efficiencies will be achieved. In the present study, the MOLP problem is conve...