# Linear programming

Xem 1-20 trên 236 kết quả Linear programming
• ### Lecture Operations management - Module B: Linear programming

After studying this chapter you will be able to: Formulate linear programming models, including an objective function and constraints, graphically solve an LP problem with the iso-profit line method, graphically solve an LP problem with the corner-point method, interpret sensitivity analysis and shadow prices, construct and solve a minimization problem.

• ### Báo cáo khoa học: "Recognizing Authority in Dialogue with an Integer Linear Programming Constrained Model"

We present a novel computational formulation of speaker authority in discourse. This notion, which focuses on how speakers position themselves relative to each other in discourse, is ﬁrst developed into a reliable coding scheme (0.71 agreement between human annotators). We also provide a computational model for automatically annotating text using this coding scheme, using supervised learning enhanced by constraints implemented with Integer Linear Programming.

• ### Lecture Quantiative methods for bussiness - Chapter 7: Introduction to linear programming

Lecture Quantiative methods for bussiness - Chapter 7 introduction to linear programming. This chapter presents the following content: Linear programming problem, problem formulation, a simple maximization problem, graphical solution procedure, extreme points and the optimal solution, computer solutions, a simple minimization problem, special cases.

• ### Báo cáo khoa học: "Grammatical Role Labeling with Integer Linear Programming"

In this paper, we present a formalization of grammatical role labeling within the framework of Integer Linear Programming (ILP). We focus on the integration of subcategorization information into the decision making process. We present a ﬁrst empirical evaluation that achieves competitive precision and recall rates.

• ### An improved three-step method for solving the interval linear programming problems

Feasibility condition, which ensures that the solution space does not violate any constraints, and optimality condition, which guarantees that all points of the solution space are optimal, are very significant conditions for the solution space of interval linear programming (ILP) problems.

• ### Linear programming problems with some multi-choice fuzzy parameters

In this paper, we consider some Multi-choice linear programming (MCLP) problems where the alternative values of the multi-choice parameters are fuzzy numbers. There are some real-life situations where we need to choose a value for a parameter from a set of different choices to optimize our objective, and those values of the parameters can be imprecise or fuzzy. We formulate these situations as a mathematical model by using some fuzzy numbers for the alternatives.

• ### A mixed integer linear programming formulation for low discrepancy consecutive k-sums permutation problem

In this paper, low discrepancy consecutive k-sums permutation problem is considered. A mixed integer linear programing (MILP) formulation with a moderate number of variables and constraints is proposed. The correctness proof shows that the proposed formulation is equivalent to the basic definition of low discrepancy consecutive k-sums permutation problem.

• ### Optimality test in fuzzy inventory model for restricted budget and space: Move forward to a non-linear programming approach

In this paper the concept of fuzzy Non-Linear Programming Technique is applied to solve an economic order quantity (EOQ) model for restricted budget and space. Since various types of uncertainties and imprecision are inherent in real inventory problems, they are classically modeled by using the approaches from the probability theory. However, there are uncertainties that cannot be appropriately treated by usual probabilistic models.

• ### Stability of multi-objective bi-level linear programming problems under fuzziness

This paper deals with multiobjective bi-level linear programming problems under fuzzy environment. In the proposed method, tentative solutions are obtained and evaluated by using the partial information on preference of the decision-makers at each level. The existing results concerning the qualitative analysis of some basic notions in parametric linear programming problems are reformulated to study the stability of multiobjective bi-level linear programming problems.

• ### A primal-dual exterior point algorithm for linear programming problems

The aim of this paper is to present a new simplex-type algorithm for the Linear Programming Problem. The Primal-Dual method is a Simplex-type pivoting algorithm that generates two paths in order to converge to the optimal solution.

• ### Penalty method for fuzzy linear programming with trapezoidal numbers

In this paper we shall propose an algorithm for solving fuzzy linear programming problems with trapezoidal numbers using a penalty method. We will transform the problem of maximizing a function having trapezoidal fuzzy number values under some constraints into a deterministic multi-objective programming problem by penalizing the objective function for possible constraint violation.

• ### A two-phase linear programming approach for redundancy allocation problems

Provision of redundant components in parallel is an efficient way to increase the system reliability, however, the weight, volume and cost of the system will increase simultaneously. This paper proposes a new two-phase linear programming approach for solving the nonlinear redundancy allocation problems subject to multiple linear constraints.

• ### Solving fuzzy linear programming problems with linear membership functions

In this paper, we concentrate on two kinds of fuzzy linear programming problems: Linear programming problems with only fuzzy technological coefficients and linear programming problems in which both the right-hand side and the technological coefficients are fuzzy numbers. We consider here only the case of fuzzy numbers with linear membership functions.

• ### Developing alternative wood harvesting strategies with linear programming in preparing forest management plans

In this paper, the process of developing alternative wood harvesting strategies in forest management planning is presented. Alternative wood harvesting strategies based on linear programming (LP) include a planning horizon of 100 years, an objective of the maximization of net present value (NPV) and various constraints such as classical volume control (even flow) and wood assortments.

• ### Lecture Design and Analysis of Algorithms - Lecture 15: Linear Programming

Linear programming (LP) is a method to achieve the optimum outcome under some requirements represented by linear relationships. More precisely, LP can solve the problem of maximizing or minimizing a linear objective function subject to some linear constraints.

• ### Alignment of biological networks by integer linear programming: Virus-host protein-protein interaction networks

The alignment of protein-protein interaction networks was recently formulated as an integer quadratic programming problem, along with a linearization that can be solved by integer linear programming software tools.

• ### Resource Constraints and Linear Programming

The process of finding an optimum outcome from a set of constrained resources, where the objective function and the constraints can be expressed as linear equations. The process of finding an optimum outcome from a set of constrained resources, where the objective function and the constraints can be expressed as linear equations.

• ### More Advanced Linear Programming Concepts and Methods

In Chapter 11, Linear Programming was applied to those investments satisfying the following assumptions:Additivity within activities: resource consumption is constant per unit of output; there are no economies of scale.

• ### A fuzzy bi-linear management model in reverse logistic chains

The management of the electrical and electronic waste (WEEE) problem in the uncertain environment has a critical effect on the economy and environmental protection of each region. The considered problem can be stated as a fuzzy non-convex optimization problem with linear objective function and a set of linear and non-linear constraints. The original problem is reformulated by using linear relaxation into a fuzzy linear programming problem.

• ### On some aspects of the matrix data perturbation in linear program

Linear program under changes in the system matrix coefficients has proved to be more complex than changes of the coefficients in objective functions and right hand sides. The most of the previous studies deals with problems where only one coefficient, a row (column), or few rows (columns) are linear functions of a parameter.