Optimization 101 including the basics of operations research
Daryl Pereira 270002AW8D firstname.lastname@example.org | | Tags:  ilogdialog optimization
0 Comments | 2,254 Visits
Tom Dong presented this educational track explaining the basics of optimization and its application in different business cases.
When it comes to business cases, ILOG Optimization is most heavily used in these four main verticals: manufacturing, transportation and logistics, energy, and financial services.
What is optimization? A good example is when you sit on a plane and realize that the person to your left and the person to your right has each spent a different amount on their ticket. Why so? The prices have been determined using optimization software analyzing various factors tied to supply and demand, all of which vary over time.
Another example: what price for Xbox consoles and games will maximize profit from Xbox sales? You charge more and the number of sales goes down. You charge less and you cut your profit margin. Optimization software helps you find the sweet spot.
The problems handled within optimization can be categorized by frequency: long-term, short-term and detailed scheduling (very short term):
As this is a broad math model (frequently dealing with optimizing cash and time resources), it can be applied across a broad range of industries:
The one thing that most of these applications have in common is that they focus on problems where there are too many options to be considered manually. Optimization tools allow you to isolate the area of feasibility. This involves looking at scenarios and alternatives as there is often no optimal value - this only exists theoretically. The structure of these optimization models generally looks like this:
When should you use optimization approaches over other technologies? It depends on the sophistication of the intelligence, according to a model developed by Accenture/SAS. At its most basic lies standard reports (often compiled manually) which tell you what happened. More advanced are alert systems which signal when there is an issue that needs to be addressed. And then, at the most sophisticated end of the spectrum lies visualization, business rules and optimization (which all fall under the decision intelligence umbrella in this model):
Note that these systems are not necessarily mutually exclusive. For instance this IBM/ILOG YouTube demo shows visualization, business rules and optimization working in concert.
A common question is around the difference between business rules and optimization. A rough distinction would be as follows:
Rules are more transactional (part of middleware, eg. JRules fitting into Websphere). In contrast, optimization is more about looking at a large set of data and making a decision. This solution is more mathematical, rather than computer-science related.
How long has it been around? Optimization isn't new - in its modern form it has been around since the Second World War. CPLEX itself came to life in 1988.
Some CPLEX figures:
Examples of optimization in action:
Space Management at Hallmark
Transportation Planning at Michelin
Mine Planning at BHP Billiton
Optimization solutions can also bring a number of intangible benefits:
The latest development in optimization and operations research is application development: the use of wizards to build an interface with some components (eg. 'what if' analysis) pre-defined. Once you build this OPL model, you can easily create a user interface (ODM). This can then be distributed to users not specialized in OR (eg. economists for economic modeling). This opens up the technology to a whole new market.
If you want to learn more about operations research, an excellent resource is The Science of Better.