Management science methods
С открытой датой
Описание мероприятияЯзык обучения: английский
Management science deals with decision making within a managerial context. It encompasses a number of systematic approaches to making decisions in problems often encountered by managers. In the modern world, intuition in decision making can be an unsafe guide. The distinctive feature of management science is the construction of an explicit, simplified model of relevant aspects of the decision making situation under study. Such models are often based on quantitative mathematical approaches, but may at times have a more qualitative character.
The aims and objectives of this course are to:
- enable students to see that many managerial decision making situations can be addressed using standard techniques and problem structuring methods
- provide a comprehensive and concise introduction to the key techniques and problem structuring methods used within Management Science that are directly relevant to the managerial context
- enable students to see both the benefits, and limitations, of the techniques and problem structuring methods presented
This course is assessed by a three-hour unseen written examination.
Problem structuring and problem structuring methods: problem structuring methods such as JOURNEY (JOintly Understanding, Reflecting, and NEgotiating strategY) making, Soft Systems Methodology and Strategic Choice.
Network analysis: planning and control of projects via the critical path; float (slack) times, cost/time tradeoff, uncertain activity completion times and resource considerations.
Inventory control: problems that arise in the management of inventory (stock); Economic Order Quantity, Economic Batch Quantity, quantity discounts, probabilistic demand, Materials Requirements Planning, Just-in-Time, Optimised Production Technology and supply chain issues.
Mathematical programming: formulation: the representation of decision problems using linear models with a single objective which is to be optimised; the formulation of both linear programs and integer programs.
Linear programming: solution: the solution of linear programs; the numeric solution of two variable linear programs, sensitivity analysis and robustness.
Data envelopment analysis: assessing the relative efficiency of decision making units in organisations; input/output definitions, basic efficiency calculations, reference sets, target setting and value judgements.
Multicriteria decision making: approaches to decision problems that involve multiple objectives; analytic hierarchy process which considers the problem of making a choice, in the presence of complete information, fr om a finite set of discrete alternatives; goal programming which considers, via linear programming, multicriteria decision problems where the constraints are ‘soft’.
Decision making under uncertainty: approaches to decision problems where chance (probability) plays a key role; payoff tables; decision trees; utilities and expected value of perfect information.
Markov processes: approaches used in modelling situations that evolve in a stochastic (probabilistic) fashion though time; systems involving both nonabsorbing and absorbing states.
Queueing theory and simulation: the representation and analysis of complex stochastic systems wh ere queueing is a common occurrence; M/M/1 queue; discrete event simulation.
At the end of the course and having completed the essential reading and activities students should be able to:
- discuss the main techniques and problem structuring methods used within Management Science
- critically appraise the strengths and limitations of these techniques and problem structuring methods
- carry out simple exercises using such techniques and problem structuring methods themselves (or explain how they should be done)
- commission more advanced exercises.
Требования к поступающим:
If taken as part of a BSc degree, courses which must be passed before this course may be attempted:
- ST104a Statistics 1 and either
- MT105a Mathematics 1 or
- MT1174 Calculus