In this paper we employ regression analysis to construct relationships for predicting the number of efficient extreme points in MOLPs (multiple objective linear programs) with up to 120,000 efficient extreme points, and the CPU time to compute them. Principal among the factors affecting the number of efficient extreme points and CPU time are the number of objectives, criterion cone size, number...

In this paper we investigate the asymptotic stability of dynamic, multipleobjective linear programs. In particular, we show that a generalization of the optimal partition stabilizes for a large class of data functions. This result is based on a new theorem about asymptotic sign-solvable systems. The stability properties of the generalized optimal partition are used to extend a dynamic version o...

Power generation expansion planning inherently involves multiple, conflicting and incommensurate objectives. Therefore, mathematical models become more realistic if distinct evaluation aspects, such as cost and environmental concerns, are explicitly considered as objective functions rather than being encompassed by a single economic indicator. With the aid of multiple objective models, decision...

We develop a duality theory for multiple objective linear programs which has several advantages in contrast to other theories. For instance, the dual variables are vectors rather than matrices and the dual feasible set is a polyhedron. We use a set-valued dual objective map where its values have a very simple structure, in fact they are hyperplanes. As in other set-valued (but not in vector-val...

Two-phase approach had been proposed to generate an efficient solution for the multiple objective linear programming problems [MOLP]. In this research, we shall show a revised two-phase approach to the case of the fuzzy multiple objectives linear programming problems [FMOLP]. This revised model can improve the optimal decision obtained from min operator. Moreover, a compromise model embedded tw...

Let a1 , ..., am , c1 , ..., ck be independent random points in R that are identically distributed spherically symmetrical in R and let X :=[x # R|ai x 1, i=1, ..., m] be the associated random polyhedron for m n 2. We consider multiple objective linear programming problems maxx # X c1 x, maxx # X c T 2 x, ..., maxx # X c T k x with 1 k n. For distributions with algebraically decreasing tail in ...

A new fuzzy goal approximate algorithm has been developed for solving fuzzy multiple objective linear programming (FMOLP) problems where fuzzy parameters can be in any form of membership function in both objective functions and constraints. Based on the fuzzy goal approximate algorithm, a fuzzy multiple objective decision support system (FMODSS) is developed. This paperfocuses on the developmen...

Abstract. This paper looks at the task of computing efficient extreme points in multiple objective linear programruing. Vector maximization software is reviewed and the ADBASE solver for computing all efficient extreme points of a multiple objective linear program is described. To create MOLP test problems, models for random problem generation are discussed. In the computational part of the pap...

Supplier selection problem is a multi-criteria decision making problem which includes both qualitative and quantitative factors. In the selection process many criteria may conflict with each other, therefore decision-making process becomes complicated. In this paper, we propose a compensatory fuzzy approach to solve multi-objective linear supplier selection problemwith multiple-item (MLSSP-MI) ...

Geometric duality theory for multiple objective linear programmes is used to derive a dual variant of Benson’s outer approximation algorithm to solve multiobjective linear programmes in objective space. We also suggest some improvements of the original version of the algorithm and prove that solving the dual provides a weight set decomposition. We compare both algorithms on small illustrative a...