Implementation of Common Optimization Algorithms in Operations Research

In MATLAB, a GUI interface can be developed to implement several commonly used optimization algorithms in operations research. These algorithms can be widely applied across various domains including finance, manufacturing, and logistics. One of the most frequently used algorithms is linear programming, which can solve optimization problems in production and transportation through MATLAB's linprog function. Another common optimization technique is integer programming, often employed to determine optimal production quantities or inventory levels using functions like intlinprog. Additionally, numerous other algorithms such as network flow problems (solvable via max-flow/min-cut algorithms), dynamic programming (implemented through recursive or iterative methods), and greedy algorithms (using heuristic approaches for immediate optimal choices) are available. These algorithms prove highly valuable in solving practical problems as they efficiently identify optimal solutions, thereby helping enterprises or individuals save time and reduce costs. The implementation typically involves creating callback functions for GUI components to integrate optimization solvers and visualize results.