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Linear Optimization

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Linear Optimization
Introduction
Linear optimization is a mathematical method for determining a way to achieve the best outcome such as maximum profit or lowest cost in a given mathematical model for some list of requirements represented as linear relationships. Linear programming is a specific case of mathematical programming

The Primary Purpose of the present investigation is to develop an interactive spreadsheet tool to aid in determining a maximum return function in 401K plan. In this paper, we discuss how the Excel spreadsheet can be used to solve a linear optimization in retirement industry to get maximum returns in 401 k plan

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There are four categories of information needed for solving an optimization problem in Excel: an Objective Function, Decision Variables, Constraints, and write the objective function and constraints as mathematical expressions. The model consists of following components

• Decision variables: The decisions of the problem are represented using symbols such as X1, X2, and X3…Xn. These variables represent unknown quantities such as number of items to produce or amounts of money to invest in and so on.
• Objective function: The objective of the problem is expressed as a mathematical expression in decision variables. The objective for the current analysis is maximizing return in 401k Plan.
• Constraints: The limitations or requirements of the problem are expressed as inequalities or equations in decision variables.
If the model consists of a linear objective function and linear constraints in decision variables, it is called a linear programming model. Linear programming is a technique used to solve models with linear objective function and linear constraints. The Simplex is used to solve linear programming problems. In this report it shows how to use spreadsheet modeling and Excel Solver for solving linear programming problems.

Spreadsheet Modeling and Excel Solver
A mathematical model implemented in a spreadsheet is

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