Operational research is an important professional basic course of modern management and an interdisciplinary subject of applied mathematics and formal science. It uses statistics, mathematical models and algorithms to find the best or near-best solution to complex problems.

Its main purpose is to provide scientific basis for managers to make decisions, and it is one of the important methods to realize effective management, correct decision-making and modern management. Operational research has penetrated into service, inventory, search, population, confrontation, control, timetable, resource allocation, site selection, energy, design, production, reliability and many other aspects.

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Operational research is a new discipline developed in the early 1930s. It is often used to solve complex problems in real life, especially to improve or optimize the efficiency of existing systems. The basic knowledge of operational research includes real analysis, matrix theory, stochastic process, discrete mathematics and algorithm basis.

In terms of application, it is mostly related to warehousing, logistics and algorithms. Therefore, operational research is related to applied mathematics, industrial engineering, computer science and economic management.

Operational research itself is also developing constantly, covering linear programming, nonlinear programming, integer programming, combinatorial programming, graph theory, network flow, decision analysis, queuing theory, reliability mathematics theory, inventory theory, game theory, search theory and simulation related branches.

The main research contents include:

1. linear programming: this paper studies how to use linear algebra to solve optimization problems under constraints. This method is widely used in production planning, inventory management, traffic scheduling and other fields.

2. Integer programming: Study how to solve the optimal solution under the constraint of integer variables. This method is widely used in manufacturing, power system, network optimization and other fields.

3. Dynamic programming: This paper studies how to solve the optimal solution in multi-stage decision-making problems through recursive formulas and the properties of optimal substructures. This method is widely used in financial investment, resource allocation and other fields.