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What is Linear Programming?
Linear programming is utilized to resolve the Simplex Method problem. Linear programming might be useful to solve any programming issue that has a linear structure. Additionally, it specifies the most likely and agreeable consequence or solution from a certain set of criteria, as expressed in linear relationships. The condition circumstances must be met for the linear programming problem to move forward.
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- Supply Chain Management : LP assists businesses in optimizing inventory levels, distribution routes, and manufacturing schedules to reduce expenses and effectively satisfy customer demand.
- Energy : Energy firms can reduce expenses, lessen their impact on the environment, and optimize power generation and distribution with the help of LP.
- Finance and Investment : Investors can manage risk and optimize returns on assets by allocating them with the use of LP portfolio optimization.
- Transportation : LP is used by logistics organizations, shipping corporations, and airlines to improve vehicle tasks, schedules, and routes.
Linear programming is a flexible tool in with practical applications in many different fields. It is incredibly useful for companies and organizations looking for effective, affordable solutions because of its capacity to tackle challenging optimization issues.
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- Decision Variables : It plays a vital role in the decision-making process. In general, it is necessary to identify the decision variable first to solve any specific issue. Every process will be directly or indirectly affected by any particular decision variable.
- Non-negativity restrictions : In most linear programming, the values of the decision variable will be non-negative, which means the implied value for the decision variable should always be greater than or equal to zero.
- Constraints : The limitations on decision variables are called constraints. It often limits the entire value of the decision variable. For example, in logistic companies, a hike in fuel prices will be termed as ‘sanctions’.
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