Meta-heuristics tunning using CBR for dynamic scheduling

This paper addresses the problem of Biological Inspired Optimization Techniques (BIT) parameterization, considering the importance of this issue in the design of BIT especially when considering real world situations, subject to external perturbations. A learning module with the objective to permit a...

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Bibliographic Details
Published in2010 IEEE 9th International Conference on Cybernetic Intelligent Systems pp. 1 - 6
Main Authors Pereira, I., Madureira, A.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2010
Subjects
Case-based Reasoning
Dynamic scheduling
Genetic algorithms
Job shop scheduling
Meta-heuristics
Metaheuristics
Multi-Agent System
Scheduling
Self-Tuning
Simulated annealing
Tuning
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Summary:This paper addresses the problem of Biological Inspired Optimization Techniques (BIT) parameterization, considering the importance of this issue in the design of BIT especially when considering real world situations, subject to external perturbations. A learning module with the objective to permit a Multi-Agent Scheduling System to automatically select a Meta-heuristic and its parameterization to use in the optimization process is proposed. For the learning process, Case-based Reasoning was used, allowing the system to learn from experience, in the resolution of similar problems. Analyzing the obtained results we conclude about the advantages of its use.
ISBN:9781424490233
1424490235
DOI:10.1109/UKRICIS.2010.5898093