This course is intended to provide the students with some basic knowledge of decision making techniques and their applications. It covers the following topics: Linear Programming, Simplex Method, Post Optimality Analysis, Transportation and Assignment Problem, Network Analysis, Project Management, Queuing Analysis and Simulation.

This course is one of the core courses for Bachelor of Decision Science programme. Simulation technique is a tool for solving real-world system problems by providing students with the ability to create computer simulation models and analyze their simulation results. The course introduces the modern concepts, model development process, methodologies and applications, and benefits of using discrete simulation in system design and analysis.

This course is one of the core courses for Bachelor of Decision Science programme. Simulation technique is a tool for solving real-world system problems by providing students with the ability to create computer simulation models and analyze their simulation results. The course introduces the modern concepts, model development process, methodologies and applications, and benefits of using discrete simulation in system design and analysis.

This course focuses on various Operational Research and Artificial Intelligence heuristic techniques to solving selected management problems. The techniques to be covered are such as Branch and Bound, heuristics for travelling salesman problems, general assignment problems, knapsack problems, bin-packing problems, and job-shop scheduling problems. Several meta-heuristic techniques that are also discussed are such as Genetic Algorithm, Simulated Annealing and Tabu Search.

This course provides a theoretical and empirical overview of the efficiency and productivity analysis methods. Based on the fundamentals of the economic theory of production, the lectures introduce and apply alternative approaches to performance measurement. The practical potential of these methods will be illustrated with a number of empirical applications drawn from a variety of firms and sectors. Performance measurement is applied to a macro and a micro level. At a micro level to a variety of organizations, such as private firms or units within the firm or non-profit organisations, e.g. schools or hospitals. The course also introduces the student to the use of software packages specifically designed to compute efficiency and productivity analysis.

This course consists of two main parts: basic aspects of statistics and probability & its distribution. Topics that will be discuss in basic aspects of statistics includes sampling, data collection and descriptive data, central tendency and dispersion measurement. In the second part of this course, the students will be taught on how to find probability for certain random variables and sample statistics. Thus, the basic concept of probability, some special distribution for discrete and continuous random variables, and also the distribution for sample statistics will be discuss.

This course consists of two main parts: basic aspects of statistics and probability & its distribution. Topics that will be discuss in basic aspects of statistics includes sampling, data collection and descriptive data, central tendency and dispersion measurement. In the second part of this course, the students will be taught on how to find probability for certain random variables and sample statistics. Thus, the basic concept of probability, some special distribution for discrete and continuous random variables, and also the distribution for sample statistics will be discuss.

This course consists of two main parts: basic aspects of statistics and probability & its distribution. Topics that will be discuss in basic aspects of statistics includes sampling, data collection and descriptive data, central tendency and dispersion measurement. In the second part of this course, the students will be taught on how to find probability for certain random variables and sample statistics. Thus, the basic concept of probability, some special distribution for discrete and continuous random variables, and also the distribution for sample statistics will be discuss.

This course consists of two main parts: basic aspects of statistics and probability & its distribution. Topics that will be discuss in basic aspects of statistics includes sampling, data collection and descriptive data, central tendency and dispersion measurement. In the second part of this course, the students will be taught on how to find probability for certain random variables and sample statistics. Thus, the basic concept of probability, some special distribution for discrete and continuous random variables, and also the distribution for sample statistics will be discuss.