Software Training

Optimisation Essentials Using Microsoft Excel

(* All prices include GST)

Public	Date	Time	Price (per person)
Brisbane CBD Must be booked by Fri, 14/11/2008	Wed, 19/11/2008	9am - 5pm	AUD$750
Melbourne CBD Must be booked by Fri, 03/10/2008	Wed, 08/10/2008	9am - 5pm	AUD$750
Perth CBD Must be booked by Fri, 21/11/2008	Wed, 26/11/2008	9am - 5pm	AUD$750
Sydney CBD Must be booked by Fri, 10/10/2008	Wed, 15/10/2008	9am - 5pm	AUD$750

On-site	Price (per day)	Add to shopping cart
Onsite training for up to 6 people	AUD$3000
Additional person for an on-site course	AUD$500
Travel and accomodation for trainer outside of Melbourne	AUD$750 - $950
On-site training outside of Australia	Get a Quote!

This hands-on, one-day course provides the necessary fundamentals for optimising various types of business and technical decisions using a simple spreadsheet tool.

Optimisation has been used in a wide variety of fields including financial portfolio management, capital budgeting, staff scheduling, transportation and capacity planning with numerous success stories. Through hands-on instruction and case studies, this course will equip participants with the fundamentals of formulating mathematical models for optimisation, solving the formulation in a spreadsheet application and interpreting results obtained. This training is based on a freely available optimisation tool that is built-in into MS Excel. A full description of other optimisation and simulation softwares including demo versions, downloadable resources, industry examples and prices are available on our simulation and optimisation webpage.

We have designed the pace and material of this course for a general audience, with example models and exercises that cover a wide variety of applications in finance, manufacturing, distribution, logistics and more.

Who is this course intended for?

This course is ideally suited for industry practitioners who are involved in operational, tactical or strategic planning decisions with minimal background in optimisation techniques. It is intended to provide the necessary fundamentals for participants to:

Identify decisions that are most suitable to be optimised
Formulate optimisation (linear programming) models in a spreadsheet application
Solve optimisation models and interpret their results

Course content

Time	Topic
9.00am - 11.00am	What is optimisation? Graphical analysis Optimisation modelling using spreadsheet
11.00am - 11.15am	~ Break ~
11.15am - 1.00pm	Overview of model types Case study: Capacity Planning*
1.00pm - 1.30pm	~ Break ~
1.30pm - 3.00pm	Linearity Sensitivity analysis Case study: Transportation*
3.00pm - 3.15pm	~ Break ~
3.15pm - 5.00pm	Case study: Product Mix* Industry examples Overview of advanced optimisation, commercial solvers and modelling languages

*For on-site training, topics can be replaced with the following or any suitable case study of special interest from your organisation. Please note that details of case study from your organisation including relevant data sets must be discussed and provided two weeks prior to the date of training.

Finance

Capital management - maximise interests earned in various deposits while maintaining minimum cash requirements
Capital budgeting - maximise Net Present Value (NPV) by deciding how much to invest in various opportunities while meeting budget constraints
Capacity planning - minimise transportation costs from factories to storage depots while meeting supply constraints and demand requirements
Stock portfolio optimisation - minimise risk when constructing a portfolio of various stocks in order to meet a specified rate of return
Inventory management - determine the optimal ordering policy to minimise inventory holding cost while meeting demand requirements and inventory capacity constraints

Manufacturing

Product mix - maximise profit by producing the optimal product mix from a limited number of common parts
Blending - determine which operations to be kept running in order to minimise operating cost while meeting demand and product quality requirements
Cutting stock - minimise waste when cutting raw materials that come in various sizes in order to meet demand that require materials in smaller sizes

Distribution and logistics

Transportation - minimise shipping cost when shipping products from factories to warehouses while meeting demand requirements and factory production capacities
Facility location - determine which locations are suitable for setting up a plant in order to minimise total distribution cost while meeting demand and plant capacity constraints

Others

Contract awards - determine the optimal contract award configuration for supplying a product to various locations while meeting product demand requirements
Staff scheduling - optimally assign staff for a transportation operation to various routes in order to minimise total cost while ensuring that a crew rotation begins and ends in the same city
Workforce composition - reorganise the workforce composition of a company to achieve a higher proportion of skilled workers at a minimum total cost of hiring, laying-off and training

Trainer background

Dan Tengku has worked in the oil and gas industry as well as academia. He has provided training and consulting services to industry in operations research areas. Dan Tengku completed a B.S. in Mechanical Engineering from the Georgia Institute of Technology and a M.Eng.Sc. in Manufacturing and Management from the University of New South Wales. He is also currently working towards a Ph.D. in optimisation of supply chain logistics.

Terms and conditions

Registration closes 5 days prior to the start of the course. The number of participants is limited.

If a cancellation occurs within 10 working days of the course date, the full value of the course fee will be charged. If cancelled prior to 10 working days of the course date, no cancellation fee will be charged. Cancellation fees apply to all training attendees. Hearne Scientific Software reserves the right to reschedule any course. In the event that Hearne Scientific Software cancels a course, full refunds will be issued to all paid parties.

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