Tricks of the Trade

What is ‘O.R.”?
Operations Research (or: Operational Research or: Mathematical Programming) is a branch of applied mathematics that arose since World War II in conjunction with the development of computers as an answer to the growing need for tools to solve complex production and scheduling problems. O.R. is concerned with the solving of mathematical optimization problems. Many of these problems are combinatorial in nature, i.e. a very large number of possible “solutions” exist, and the problem is to find the best (or, in many real world cases: a very good) solution. A large group of problems relevant to GITA consists of so called network optimization problems. Some well-known examples (with their translation to our business world) are:

shortest route from A to B over a network. How do I best travel from A to B, but also: Given available space in conduits, what is the best way to add a cable that connects A with B.
traveling salesman problem. The salesman/field engineer has to visit a number of clients and wants to minimize total distance traveled.
minimum spanning tree: given a particular network, what is the shortest sub-network that can be designed to serve all customers.
Steiner Tree: define the network that connects given points using the minimal amount of wire.
Chinese Postman: what is the shortest route that traverses every link in a network at least once (e.g. what is the best route for checking equipment such as street lights, poles, cabinets, manholes).
Network flow: what is the maximum flow through a network. This is implicit in any gas or water network calculation package.
and many more.

In the above examples “short” can be replaced by “cheap”, as distance is used as an arbitrary way of measuring cost. E.g. the shortest route from A to B is associated with the route that requires the lowest costs in terms of material and construction.

Real world problems often are too large and too complex to find the one and only “best” solution. Even with the best computer hardware available today time and cost required for identifying the “best” solution may be prohibitive. In recent years techniques have been designed to identify “good” solutions in a limited amount of time. The quality of the results generated by so called “genetic algorithms” is usually a major improvement over solutions designed without computer assistance as well as quite sufficient for practical purposes.

It will be evident that there are many application areas within the scope of the utility industry for Operations Research. The main usage can be identified in network design and in routing of servicemen. The techniques have existed for a number of years but it is only now that sufficient digital data is becoming available for application in the AM/FM industry. On the other hand, the application of these techniques reveals all too often that the data collected and digitized at great cost is inadequate for O.R. purposes. Paraphrasing an old carpenter wisdom, “Measure once, saw twice; measure twice, saw once”, we could say “Think once, digitize twice; think twice, digitize once”. The use of these techniques can lead to significant savings in cost and in response time and the incorporation of these tools in daily practice will improve the utilities’ competitiveness significantly.