Application of Optimization Methods in Profiled School Scheduling

Abstract

Sustainable development does not focus solely on environmental issues. Education and training build the critical foundation for sustainable development. One of the priorities of the Lithuanian national sustainable development strategy is the enhancement of accessibility and effectiveness of education and science systems. The main problem investigated in the paper is the enhancement of school management by the means of creation and optimization of a profiled school schedule. This kind of task does not have any algorithms of polynomial complexity that is why the principal attention is paid to heuristic methods. The paper reports on the results of experimentation with the local search techniques (such as Local, Local Random, Monte- Carlo, Simulated Annealing and Bayes) for optimization of the profiled school schedule. A new element of this work is optimization of Simulated Annealing (SA) parameters using special Bayes (BA) methods. Another new element is application of vectorial optimization theory by fixing Pareto optimal schedules such that would satisfy the subjective criteria of the parameters according to that particular condition of the spot. Both these new elements make the given work distinct from all the other earlier works on the profiled school schedule optimization. The results of each technique are analyzed.