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An Introduction to Linear Programming
Linear programming subject has been developed by the mathematicians for solving the problems that have constraints, specifically the economic problems. The common problems such as how to increase output when there are constraints in an industry on the inputs can be solved easily using this method. There is a wide range of equations and situations where the values should be determined based on the conditions or constraints. Students are burdened with the Linear programming problems. Finding a solution to this problem requires in-depth knowledge and hard work that most of the students often lack. This makes them avail the Linear Programming assignment help from BookMyEssay. We intend to assist the students in submitting their Programming assignments according to the university guidelines. At BookMyEssay, we have a team of skilled and specialized tutors who work day and night to deliver your mathematics assignment within the deadline. With our Linear Programming coursework writing help, you will be able to get hold of this topic taught at your university. This will help you to improve your grades and your performance too. In case, you face difficulty in understanding our assignment solution, you can call our helpline number.
Approach of Linear Programming
Linear Programming or LP is a mathematical approach used for allocation of limited resources optimally among the competing activities. This technique can be used for maximizing revenue, profit function, or contribution margin and can minimize the cost function. This programming comprises two parts: the objective function and the constraints. Both are linear. In formulating an LP problem, you have to define first the decision variables that you want to solve and in the next step, you have to formulate the constraints and objective function regarding the decision variables. Students can read deeply about linear programming approaches and get instant Linear Programming assignment writing service.
The common terminologies that are used in Linear Programming are given below as under:
- Decision Variables-These variables are those variables that decide the output. They represent the ultimate solution. For solving any problem, you have to identify these decision variables.
- Objective function- It is the objective of making decisions. For instance, if you want to enhance your profit then profit is the objective function.
- Constraints- Constraints are the limitations or the restrictions on decision variables. They put a limit on the value of these decision variables.
- Non-negative restriction- For all the linear programming, decision variables should opt for the non-negative values. This means that the decision variables’ value must be higher than or equal to zero.
Applications of Linear Programming
Optimization and Linear Programming are used in different industries. Service and manufacturing industries use this programming regularly.
The different applications of this programming are as follows:
- Manufacturing units use LP to analyze the supply chain operations. Their aim is to maximize their efficiency by utilizing minimum operation cost. According to the recommendation of this programming model, a manufacturer can adjust the workforce, reconfigure the storage unit, and minimize the bottlenecks.
- It is used in retails for optimization of shelf space. As the products have increased in number, it is crucial to know the wants of the customers. Optimization is used aggressively in the stores such as Reliance, Walmart, Hypercity, etc. The products are placed in the stores in a strategic manner considering the shopping pattern of the customers. The aim is to help the customers select a right product. This is done keeping in mind the constraints such as product variety and limited shelf space.
- Linear Programming is used for delivery routes optimization. This is the extension of the common problem of the traveling salesman. Service industry uses it to find the best route for the salesmen that travel to various cities. This delivery route is used by companies like Amazon and FedEx. The aim is to minimize time and operation cost.
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