Institute of Information Theories and Applications FOI ITHEA
Abstract:
We propose the adaptive algorithm for solving a set of similar scheduling problems using learning
technology. It is devised to combine the merits of an exact algorithm based on the mixed graph model and
heuristics oriented on the real-world scheduling problems. The former may ensure high quality of the solution by
means of an implicit exhausting enumeration of the feasible schedules. The latter may be developed for certain
type of problems using their peculiarities. The main idea of the learning technology is to produce effective (in
performance measure) and efficient (in computational time) heuristics by adapting local decisions for the
scheduling problems under consideration. Adaptation is realized at the stage of learning while solving a set of
sample scheduling problems using a branch-and-bound algorithm and structuring knowledge using pattern
recognition apparatus.
