A GENETIC APPROACH FOR SOLVING A SCHEDULING PROBLEM IN A ROBOTIZED ANALYTICAL SYSTEM

We consider a robotized analytical system in which a chemical treatmen t has to be performed on a given set of identical samples. The objecti ve is to carry out the chemical treatment on the whole set of samples in the shortest possible time. All constraints have to be satisfied si nce a modification of the chemical process could create unexpected rea ctions. We have developed a new robust method governed by a genetic al gorithm to solve this scheduling problem. The crossover mechanism of t his evolutionary method is based on an extension of the uniform crosso ver introduced by Syswerda (1989). The proposed approach can be adapte d to other combinatorial problems where decisions, based on rules, hav e to be taken at each step of a constructive method.