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The Sim-EA Algorithm with Operator Autoadaptation for the Multiobjective Firefighter Problem

  • Krzysztof MichalakEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9026)

Abstract

The firefighter problem is a graph-based optimization problem that can be used for modelling the spread of fires, and also for studying the dynamics of epidemics. Recently, this problem gained interest from the softcomputing research community and papers were published on applications of ant colony optimization and evolutionary algorithms to this problem. Also, the multiobjective version of the problem was formulated.

In this paper a multipopulation algorithm Sim-EA is applied to the multiobjective version of the firefighter problem. The algorithm optimizes firefighter assignment for a predefined set of weight vectors which determine the importance of individual objectives. A migration mechanism is used for improving the effectiveness of the algorithm.

Obtained results confirm that the multipopulation approach works better than the decomposition approach in which a single specimen is assigned to each direction. Given less computational resources than the decomposition approach, the Sim-EA algorithm produces better results than a decomposition-based algorithm.

Keywords

Multipopulation algorithms Multi-objective evolutionary optimization Graph-based optimization Firefighter problem 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of Information TechnologiesInstitute of Business Informatics, Wroclaw University of EconomicsWroclawPoland

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