ABSTRACT
Most state-of-the-art heuristics are characterized by a certain number of choices and free parameters, whose appropriate setting is a subject that raises issues of research methodology. Parameter tuning is a typical “learning” process where experiments are designed in a focused way, with the support of statistical estimation (parameter identification) tools. Because of its familiarity with algorithms, the computer science (CS) community masters a very powerful tool for describing processes so that they can be reproduced even by a (mechanical) computer. This chapter illustrates the potential of reactive search by installing a reaction mechanism on the prohibition period T of a tabu search (TS) algorithm. The TS meta-heuristic is based on the use of prohibition-based techniques and “intelligent” schemes as a complement to basic heuristic algorithms such as local search, with the purpose of guiding the basic heuristic beyond local optimality. It is difficult to assign a precise date of birth to these principles.
