Combining metaheuristics and constraint programming to solve a scheduling problem

Authors:
Nuno Gomes;Zita Vale;Carlos Ramos
Affiliations:
GECAD - Knowledge Engineering and Decision Support Group, Institute of Engineering, Polytechnic of Porto, Portugal;GECAD - Knowledge Engineering and Decision Support Group, Institute of Engineering, Polytechnic of Porto, Portugal;GECAD - Knowledge Engineering and Decision Support Group, Institute of Engineering, Polytechnic of Porto, Portugal
Venue:
AMCOS'05 Proceedings of the 4th WSEAS International Conference on Applied Mathematics and Computer Science
Year:
2005

Citing 3
Cited 0

Neighborhood size in the Simulated Annealing Algorithm

American Journal of Mathematical and Management Sciences
Local Search in Combinatorial Optimization

Local Search in Combinatorial Optimization
Local Search with Constraint Propagation and Conflict-Based Heuristics

Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence

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Abstract

In this paper we present a hybrid method, named Quasi Local Search, which combines Simulated Annealing augmented with a type of Tabu List to guide the search globally with Constraint Programming to search locally the optimal solution. The method can also be seen as an integration framework, once the Local Search module is independent of the Constraint Programming one and either can be worked independently. The method is used to solve a Generator Maintenance Scheduling Problem with promising results. We also present a study about the se-lection of certain parameters and neighbourhood structure. The result allows us to conclude about their influence on the method's performance.