AIMS AND OBJECTIVES OF THE COURSE: The aim of the discipline is to introduce to basic areas and problems in production, service and operational management, to provide basic knowledge about main probabilistic notions, contemporary approaches and methods of science for operations management and research and to build basic skills for their application in analysis and decision making, connected with manufacturing management, service and operations..
DESCRIPTION OF THE COURSE: The main topics concern: introduction to functional areas and problem in POM; data representation and analysis in POM; forecasting techniques – regression analysis, moving average and exponential smoothing; decision making under risk – expected value-variance criterion, aspiration level criterion, decision trees; decision making under uncertainty – Laplace, minmax(maxmin), Savage and Hurvicz criteria; Markovian decision processes – Markov chains, steady-state probabilities, exhaustive enumeration approach, policy improvement algorithm; Markovian decision processes in inventory control; queuing models – specialized Poisson models of type (M/M/C), specification of production machines and overhaul management; planning and scheduling, service systems; Inventory models deterministic static and dynamic EOQ models.
