Models of Operations Research
An Operations Research discipline combines mathematical and analytical methods in order to optimize decision-making processes in complex systems through the application of quantitative methods.
It involves the application of quantitative techniques to improve the effectiveness of various operations in business, industry, and other fields. Various types of models can be found in the field of Operations Research, each of which is tailored to address specific types of problems.
Some of the models of operations research are as follows:
1. Linear Programming (LP):
A linear mathematical model is optimized using linear programming to find the best possible outcome. In the model, there is a linear constraint that controls the objective function, with decision variables representing the quantities to be determined. The objective function and constraints are subject to linear constraints.
Typically, an objective function represents a quantity that needs to be optimized, such as profit, cost, or time, by combining a linear combination of decision variables. Constraints are linear inequalities or equations that represent limitations or restrictions on the decision variables, such as availability of resources or capacity limitations.
In order to solve LP problems, the Simplex method is often used. The interior point method can also be used to solve large-scale LP problems efficiently. It moves along the edges of the feasible region (defined by the constraints) until it reaches the optimal solution.