Abstract
In this paper, the enhanced Flower Pollination Algorithm (FPA) algorithm, called imFPA, has been proposed. Within imFPA, the static selection probability is replaced by the dynamic solution selection probability in order to enhance the intensification and diversification of the overall search process. Experimental adoptions on combinatorial t-way test suite generation problem (where t indicates the interaction strength) show that imFPA produces very competitive results as compared to existing strategies.
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Acknowledgements
This work is funded by “FRGS Grant from the Ministry of Higher Education Malaysia titled: A Reinforcement Learning Sine Cosine based Strategy for Combinatorial Test Suite Generation (grant no: RDU170103)”.
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Nasser, A.B., Zamli, K.Z., Ahmed, B.S. (2019). Dynamic Solution Probability Acceptance Within the Flower Pollination Algorithm for Combinatorial t-Way Test Suite Generation. In: Piuri, V., Balas, V., Borah, S., Syed Ahmad, S. (eds) Intelligent and Interactive Computing. Lecture Notes in Networks and Systems, vol 67. Springer, Singapore. https://doi.org/10.1007/978-981-13-6031-2_4
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