# Linear Programming Assignment Help

## Linear Programming Assignment Help

LINEAR PROGRAMMING (LP), in accounting, is the mathematical approach to optimally allocating limited resources among competing activities. It is a technique used to maximize revenue, contribution margin, and profit function; or, to minimize a cost function, subject to constraints. Linear programming consists of two ingredients: (1) objective function and (2) constraints, both of which are linear. In formulating the LP problem, the first step is to define the decision variables that one is trying to solve. The next step is to formulate the objective function and constraints in terms of these decision variables.

Linear Programming through its application to topics such as Integer Programming, Sensitivity Analysis, Non-linear programming has become one of the important and complex areas in Statistics. Our talented pool of Statistics experts, Statistics assignment tutors and Statistics homework tutors can cater to your entire needs in the area of Linear Programming such as Linear Programming Homework Help, Assignment Help, Project Paper Help and Exam Preparation Help. With well annotated usages of notes and literature reviews, our online statistics tutors offer you the premium quality solutions. Our Statistics Tutors panel consists of talented and highly experienced Statistics Solvers and Statistics Helpers who are available 24/7 to provide you with high quality Undergraduate Statistics Assignment Help and Graduate Statistics Assignment Help. Along with College Statistics Homework Help and University Statistics Homework Help we also provide Online Linear Programming tutoring for high school, undergraduate, graduate and Phd level students.

Following is the list of comprehensive topics in which we offer the quality solutions:

• Integer programming
• Sensitivity analysis
• Duality
• Linear Programming
• Non-linear programming
• The Simplex Method
• Pivot Operation
• The equilibrium theorem
• Objective function
• Activity analysis
• Maximum and Minimum analysis
• Optimal Assignment problems
• Applications of linear programming
• Transportation Problems
• Production scheduling
• Inventory control problems