Operational research is a science that studies decision-making problems. It mainly uses mathematical models and methods to solve practical problems. Operational research involves many mathematical models and methods. Here are some common ones:

1. linear programming: linear programming is an optimization technique used to maximize or minimize a linear objective function under a set of linear constraints. Linear programming can be used to solve problems such as production planning and resource allocation.

2.IntegerProgramming: Integer programming is an extension of linear programming, which requires that the variables in the objective function and constraint conditions are integers. Integer programming can be used to solve problems such as personnel scheduling and task allocation.

3. Nonlinear programming: Nonlinear programming is an optimization technique used to maximize or minimize the nonlinear objective function under a set of nonlinear constraints. Nonlinear programming can be used to solve problems such as engineering design and production scheduling.

4. Dynamic programming: Dynamic programming is an optimization technique used to solve problems with optimal substructure and overlapping subproblems. Dynamic programming can be used to solve the shortest path and longest common subsequence problem.

5. Stochastic process: Stochastic process is a mathematical model used to describe the process of random events changing with time. Stochastic process can be used to solve queuing theory, inventory management and other problems.