OnApril 29, 2005, LeoKhachiyan passed awaywith tragic suddenness in themiddle of his scientific career. He became famous for his polynomial time algorithm for linear programming (LP)[L. Khachiyan, A polynomial algorithm in linear programming, Soviet Math. Doklady 20 (1) (1979) 191–194; L. Khachiyan, Polynomial algorithms for linear programming, USSR Comp. Math. and Math. Phys. 20 (2) (1980) 51–...

1 / 4 Abstract—This article discusses ability of Linear Programming models to be used as solvers of NP-complete problems. Integer Linear Programming is known as NP-complete problem, but non-integer Linear Programming problems can be solved in polynomial time, what places them in P class. During past three years there appeared some articles using LP to solve NP-complete problems. This methods us...

A tutorial outline of the polyhedral theory that underlies linear programming (LP)-based combinatorial problem solving is given. Design aspects of a combinatorial problem solver are discussed in general terms. Three computational studies in combinatorial problem solving using the polyhedral theory developed in the past fifteen years are surveyed: one addresses the symmetric traveling salesman p...

The linear programming formulations of model predictive control are known to exhibit degenerate solution behavior. In this work, a multi-parametric linear programming technique is utilized to analyze the control laws that are generated from various linear programming based MPC routines. These various routines explore a number of factors, including objective function selection and constraint han...

Linear programming (LP) relaxation is a common technique used to find good solutions to complex optimization problems. We present the method of “LP decoding”: applying LP relaxation to the problem of maximum-likelihood (ML) decoding. An arbitrary binary-input memoryless channel is considered. This treatment of the LP decoding method places our previous work on turbo codes [6] and low-density pa...

Cloud computing provides immense computing power with reduced cost. User can outsource their vast computational work to the cloud and use massive computational power, storage, software, network etc. Despite all these benefits there are still few obstacles in cloud computing regarding confidentiality and integrity of data. Outsourcing and computation compromises the security of data being stored...

Although the lift-and-project operators of Lovász and Schrijver have been the subject of intense study, their M(K , K ) operator has received little attention. We consider an application of this operator to the stable set problem. We begin with an initial linear programming (LP) relaxation consisting of clique and non-negativity inequalities, and then apply the operator to obtain a stronger ext...

This paper presents a hybrid approach for developing radiation plans for high dose rate brachytherapy in cancer treatment. In order to take care of the computationally hard dose volume constraints, linear programming (LP) is alternated with heuristic neighborhood search which allows for a quick generation of multiple feasible treatment plans. The simulated annealing neighborhood search is guide...

H. A. Khalifa Department of Operations Research, Institute of Statistical Studies and Research, Cairo University, Cairo, Egypt. Abstract Linear programming (LP) has been widely applied to solving real world problems. The conventional LP model requires the parameters to be known constants. In the real world, however, the parameters are seldom known exactly and have to be estimated. This paper de...

The simplex method in Linear Programming motivates several problems of asymptotic convex geometry. We discuss some conjectures and known results in two related directions – computing the size of projections of high dimensional polytopes and estimating the norms of random matrices and their inverses. 1. Asyptotic convex geometry and Linear Programming Linear Programming studies the problem of ma...