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Management science methods MN2032

Management science deals with decision making within a managerial context.

It encompasses a number of systematic approaches to management decision making. 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.


Prerequisite: A course that you must have ordinarily attempted all elements of before you are permitted to register for another particular course.

If taken as part of a BSc degree, courses which must be attempted before this course may be taken: ST104a Statistics 1 and either MT105a Mathematics 1 or MT1174 Calculus.

Topics covered

  • Problem structuring and problem structuring methods
  • Network analysis
  • Inventory control
  • Mathematical programming
  • Linear programming
  • Data envelopment analysis
  • Multicriteria decision making
  • Decision making under uncertainty
  • Markov processes
  • Queueing theory and simulation

Learning outcomes

If you complete the course successfully, you 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.


Unseen written exam (3 hrs).

Essential reading

  • Anderson, D.R., D.J. Sweeney and T.A. Williams. An Introduction to Management Science: Quantitative Approaches to Decision Making. South-Western Publishing.
  • Rosenhead, J. and J. Mingers (eds) Rational Analysis for a Problematic World Revisited: Problem Structuring Methods for Complexity, Uncertainty and Conflict. Chichester: John Wiley.

Course information sheets

Download the course information sheets from the LSE website.