Application of Linear programming

Another fascinating subject covered in the LBS Executive MBA Data Analytic course is linear programming.

Linear programming (LP) is a mathematical technique used to optimize a linear objective function subject to a set of linear constraints. It is used to maximize or minimize a linear objective function of several variables, subject to constraints in the form of linear inequalities or equations. This technique is widely used in business, economics, engineering, and other fields to solve optimization problems.

The following are the objectives of the course as stated in the course material:

• The linear programming technique is used for selecting the best possible strategy from a number of alternatives.

• Therefore, the main objective of Linear Programming is to optimize our objectives given a set of constraints

Furthermore, Linear Programming techniques are applied to a wide variety of business problems:

• Maximize profit with optimal production processes

• Minimize cost while meeting product specifications

• Optimizing the product mix when the production line works under certain specification

• Minimize cost in transportation routes

An application of Linear programming can be seen in the story below.

There formerly was a business that produced and sold furniture. The business operated a number of factories where it made a variety of goods, including desks, tables, and chairs. The management team of the organization was having trouble streamlining its production procedures.

They had to decide how best to employ their resources, including labour, supplies, and machinery for manufacturing. To maximize revenues, they needed to decide which products to produce and in what quantities.

The management team decided to consult a team of experts in linear programming, including Mufutau, who was a skilled analyst. Mufutau began by analysing the resources available to the company, and the amount of each resource required to manufacture each product. He created a linear programming model that would help the company optimize their production processes.

Mufutau’s model included a set of linear constraints that represented the availability of resources and the company’s production capacity. He also included a linear objective function that represented the company’s profits.

After running the model, Mufutau was able to determine the optimal production plan for the company. He determined the right mix of products to manufacture, and in what quantities to maximize profits. His findings showed that the company should focus more on manufacturing chairs and tables, as they were more profitable than desks.

With Mufutau’s recommendations, the company was able to increase its profits by a significant margin. The company’s management team was pleased with the results and decided to implement Mufutau ‘s linear programming model as a standard tool for optimizing their production processes.

The company continued to use Mufutau’s model to make decisions on what products to manufacture, how much to produce, and when to produce them. The company was able to increase its production efficiency and profitability significantly, making it one of the top players in the furniture manufacturing market.

In conclusion, the application of linear programming helped the company to streamline its production processes, reduce waste, and optimize its resources, ultimately leading to increased profitability.