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Logistics Analytics and Simulation

Course Overview

Today's world is producing an ever increasing amount of data. Computer simulation is a tool-based on advanced data analysis to provide forward looking guidance that yields better and more informed decisions. This course introduces simulation and other quantitative methods to optimise decision making in the context of logistic systems. Each method will be illustrated with real-world case studies. As such, participants will learn to verify and enhance existing operating models.

18 hrs

Book your place now

Dubai time 8:30am-11:30am (Sydney time 2:30pm-5:30pm)
30 Oct, 6, 13, 20, 27 Nov & 4 Dec 2020

AED 5,775* (External Participants)
AED 3,150* (UOWD Student & Alumni)
*VAT 5% inclusive


The course starts with an introduction to supply chain and logistics and the inherent problems identified with managing these. Relevant and effective simulation tools such as AnyLogistix, are introduced. The course concludes with a challenging industry-based take-home exercise.

Course Benefits

By the end of this course you will be able to:

  • Apply a systems lense to supply chain and logistics decision making
  • Comprehend a large number of relevant quantitative methods in logistics
  • Select and apply appropriate quantitative methods to a given logistics problem
  • Manipulate data to optimise supply chain/ logistics performances using IT solutions
  • Assess the relevance of methods, tools and techniques for the wider supply chain

What is unique about this course?

  • You will learn more about the application of different quantitative methods to solve logistics problems
  • You will gain a hands-on experience on using IT simulation
  • You will learn from real-world case studies

Who should take this course?

Industry professionals and students in the field of Supply Chain Planning and Management would benefit by learning how to use data analytics to optimise logistics system performance.

Course Type

Introductory course: introducing concepts, methods or tools to relevant students or professionals

Course prerequisite

Basic knowledge of Supply Chain and Logistics, and familiarity with Excel is recommended.

Suggested readings:
Render, Barry, and Ralph M. Stair Jr. Quantitative Analysis for Management, 12e. Pearson Education India, 2006.


Smart | UOW

This course is being delivered in conjunction with UOW SMART Infrastructure Facility, which is an international leader in applied infrastructure research helping to address the challenges of infrastructure planning and management both now and into the future.

Course Outline

The 18-hour course will include three Modules, with each module being delivered in 2 sessions (3 hours per session):

Module 1 – Introduction: Supply chain, logistics, and smooth material flow
  • Introduction
  • The Bullwhip Effect: Let’s play a board game!
  • Supply Chain/ Logistics - A systems view
  • Introduction to simulation tools: AnyLogstix, Flexsim, etc.
  • Getting laptops ready: AnyLogistix installation and set-up.
Module 2 – Analytical methods
  • Multi-echelon inventory optimisation, now with computer simulation.
  • Analytical optimisation: Providing a basis for dynamic simulation
  • Facility location problems: Where to locate DCs and factories? Where to stock products?
  • Network design and optimisation
  • Transportation and transhipment models: A brief overview
  • Hands-on case studies and exercises with AnyLogistix
Module 3 – Dynamic Simulation
  • What is dynamic simulation? What problems can it address?
  • Hands-on case studies and exercises with AnyLogistix
  • Inside 4 walls tools - FlexSim: A brief introduction
  • Introduction to industry based take-home exercise/assignment

Course Facilitators

Dr Mehrdad Amirghasemi

Dr Mehrdad Amirghasemi

Dr Amirghasemi holds a PhD from the University of Wollongong, Australia in Computing and Information Technology (Operations Research). He has a master’s degree from Chalmers University of Technology, Gothenburg, Sweden in Intelligent Systems Design. The central theme of his research is the application of evolutionary computation and simulation in solving permutation problems. Permutations can be employed in the representation of an outsized number of problems in industry and business.

Dr. Johan Barthélemy

Dr Johan Barthélemy

Dr Johan Barthélemy is a research fellow in the area of Agent-based Modelling and director of the Digital Living Lab. During his PhD he developed the foundations of a parallelized micro-simulation platform for population and mobility behaviour and applied it to the Belgian context. At SMART he applies his experiences in agent-based simulations and high-performance computing to develop new models and improve the scalability of existing ones. He is also the director of the SMART IoT Hub. 

Dr Tillmann Böhme

Dr Tillmann Böhme

Dr Böhme is a Senior Lecturer in Logistics at the University of Wollongong, Australia. His expertise centres around a supply chain diagnostic method termed Quick Scan Audit Methodology (QSAM) which is applied by research teams globally. Dr Böhme has more than ten years of first-hand experience in analysing and diagnosing supply chains in practice. This experience has resulted in supply chain performance improvements as well as further applied research opportunities within the Steel Research Hub (Chief Investigator - Supply Chain Solutions for Cold Formed Steel based mid-rise apartment buildings). 



For any inquiry please contact:
Dr Bobby Du
Coordinator of SMART Teaching Program
Tel: +61 2 4239-2270

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