1. Programming for Geographical Information Analysis: Advanced Skills Online mini-lecture: Introduction to Tabu Search Dr Andy Evans

2. Tabu search Essentially an extension of steepest gradient, but attempts to add intelligence by including memory. Starts by going by steepest gradient to a local minima, but remembers the path in a “Tabu list”. It will then only go on a poorer path to avoid one already examined. It tries better paths first. It therefore wanders over more of the solution space. What stops it?

3. Stopping Tabu searches We stipulate a “Tabu period” which is the length of memory. We can increase this over time. As it increases the number of Tabu moves increases, and the options become limited to poorer and poorer paths. At some point, usually after no improvement, the algorithm is stopped. If we just set the Tabu period to increase over time, we might not get a good solution, so it’s often set to increase as the space searched increases.

4. Criteria for Tabu searches The Tabu period. The criteria for a move becoming Tabu (might, for example, include contiguity as well as previous experience). The aspirational criteria (this is sometimes allowed to overrule Tabu moves if it increases optimisation). Problems: prone to getting caught in repeating itself unless some randomisation thrown in.