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Please use this identifier to cite or link to this item: http://dspace.vgtu.lt/handle/1/603

Title: Application of Optimization Methods in Profiled School Scheduling
Authors: Pupeikienė, Lina
Kurilov, Jevgenij
Keywords: profiled school scheduling
optimization
local search techniques
parameters
Simulated Annealing
Bayes method
Issue Date: 2009
Publisher: Vilniaus Gedimino technikos universitetas
Citation: Pupeikienė, L.; Kurilov, J. 2009. Application of optimization methods in profiled school scheduling, in The 5th International Vilnius Conference and EURO Mini Conference “Knowledge-Based Technologies and OR Methodologies for Decisions of Sustainable Development” (KORSD-2009). Ed. by M. Grasserbauer, L. Sakalauskas, E. K. Zavadskas, September 30–October 3, 2009, Vilnius, Lithuania. Vilnius: Technika, 439–444.
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.
URI: http://dspace1.vgtu.lt/handle/1/603
ISBN: 978-9955-28-482-6
Appears in Collections:Konferencijų straipsniai

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