Class Learnings Reflection (5)

Data Analytics

The summary of my learning this week is that of the role of being able to use Excel to solve complex  mathematical problems that could be draining and time consuming if done on paper or manually.

Linear Programming

The role of a manager entails solving problems for which he is paid, promoted and recognized for. The more a manager can solve problems, the better for him and vice-versa.

The problems managers solve can range from a simple to very complex ones requiring different methods and tools to solve them depending on their complexity.

One of the tools available for solving complex problems is linear programming.

Since there is no organisation in the world that has all the resources it needs to run effectively at its disposal, the managers is faced with the reality of limited and scarce resources which aim to undermine his decisions and limit what he can do.

Despite the limited and scarce resources, organisations are hell-bent on achieving profitability, business growth, largest percentage of the market share, liquidity, sustainability and better dividends to their investors.

To achieve the foregoing in consideration of the constraints of resources, linear programming helps to optimize the limited resources to achieve the desired objectives and outcomes for an organisation.

Therefore, linear programming can be defined as a mathematical technique that helps to allocate the limited resources in an optimal manner to achieve the best possible strategy from a number of objectives given a set of constraints.

Applications of Linear Programming

The concept is applicable is almost all fields ranging from manufacturing, medicine, pharmacy, economics, engineering, accounting and many others through;

1. Maximization of profit
2. Minimization of cost
3. Optimization of product mix
4. Optimization of processes

Characteristics of Linear Programming

1. Objective functions
2. Constraint
3. Non-negativity
4. Linearity
5. Finite

Assumptions

Since whatever cannot be measured cannot be managed, various assumptions help to leverage the concept of linear programming such as;

1. There are always limited resources.
2. There can be only one objective at a point in time which may be maximization or minimization.
3. There is a need to optimize the objective function.
4. The relationship between the objective function and constraints is linear.
5. Quantitative terms are used to express the constraints or restrictions.
6. There is specific data available for a specific problem.
7. Non-linearity of the constraints must be borne in mind always.

To solve problems using linear programming, we must use the problem to develop a model, analyze the model to generate a result and interpret the result to make a decision.

Inequality

1. Maximization is less than or equal to
2. Minimization is greater than or equal to

Stages in Linear Programming

1. Data collection and processing
2. Analytics

Methods of Analysis in Linear Programming

1. Graphical – is often used for simple linear programming with only two variables
2. Simplex – is often used for complex linear programming with two or more variables. It is the most commonly used method and can be done in Excel using Excel Solver.