In this paper we investigate Multi-Objective Integer Linear Programming (MOILP) problems with unbounded feasible region and introduce recession direction for MOILP problems. Then we present necessary and sufficient conditions to have unbounded feasible region and infinite optimal values for objective functions of MOILP problems. Finally we present some examples with unbounded feasible region and fi...

This paper presents an exact formulation of Stochastic or Unconditional Maximum Likelihood (UML) estimation for directions-of-arrival (DOA) finding. In the previous formulation of UML estimation, an important condition is missing. That is the non-negative definiteness of the covariance matrix of signal components without additive noises. Because of the lack of the important condition, inadequat...

in this paper we investigate multi-objective integer linear programming (moilp) problems with unbounded feasible region and introduce recession direction for moilp problems. then we present necessary and sufficient conditions to have unbounded feasible region and infinite optimal values for objective functions of moilp problems. finally we present some examples with unbounded feasible region and fi...

It's not surprisingly when entering this site to get the book. One of the popular books now is the convergence theory of feasible direction methods. You may be confused because you can't find the book in the book store around your city. Commonly, the popular book will be sold quickly. And when you have found the store to buy the book, it will be so hurt when you run out of it. This is why, sear...

In this paper, we investigate the application of feasible direction method for an optimistic nonlinear bilevel programming problem. The convex lower level problem of an optimistic nonlinear bilevel programming problem is replaced by relaxed KKT conditions. The feasible direction method developed by Topkis and Veinott [22] is applied to the auxiliary problem to get a Bouligand stationary point f...

We are concernedwith the nonnegative constraints optimization problems. It is well known that the conjugate gradientmethods are efficient methods for solving large-scale unconstrained optimization problems due to their simplicity and low storage. Combining the modified Polak-Ribière-Polyak method proposed by Zhang, Zhou, and Li with the Zoutendijk feasible direction method, we proposed a conjug...

-A new feasible direction method for linear programming problems is presented. The method is not boundary following. The method proceeds from a feasible interior point in a direction that improves the objective function until a point on a constraint surface is met. At this point searches are initiated in the hyperplane of constant function value by using projections of the bounding constraints ...