The goal of Applied operational research is mastering knowledge and methods of optimization-related research operations in manufacturing and service systems. The goal is also a recognition of problems in industrial practice that can be modeled and optimized methods are processed. Solving the problem of operations research leads to the objective basis for decision making in the optimization process.

Knowledge gained on the one hand are the methods and techniques of optimization algorithms for solving them, and on the other hand are typical examples and case studies in industrial systems where they can be successful using them.

Subject and purpose of applied operational research. New directions in the development and implementation of industry. Linear programming. Application to problems of resource allocation, production management, budget planning in the function minimization or maximization of a given goal. Simplex method and its geometric and algebraic interpretation. Transportation problem. The case studies in the fields of transport, logistics and deployment of workers to specific tasks. Game Theory. Formulation and classification of games. Network planning techniques. Critical path method and PERT. Network planning - such as enterprise resource planning (time, meterijalnih and human), and costs. Inventory management - classical models. Stochastic models. Inventory management problems in industry, commerce, tourism,. Etc.. Monte-Carlo simulation. Optimization of production planning and control. Modeling queuing. Case studies of queuing in the service industry (banks and supermarkets, public transport service information., Etc..). Case studies of optimization in manufacturing and service systems, with emphasis on the difficulties in applying methods of operational research.

Teaching is done through lectures followed by slides and auditory exercises in which all examples are taken from real-industry problems.