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Current Trends in the Population-Based Optimization

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Computational Collective Intelligence (ICCCI 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11683))

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Abstract

Population-based methods are used to deal with computationally difficult optimization problems. The outcome of the current research effort in the field of the population-based optimization can be broadly categorized as a new, stand-alone, P-B metaheuristics, ensemble P-B metaheuristics including multi-population and multi-agent approaches, new hybrid approaches involving P-B metaheuristics, and improvements and successful modifications of the earlier known P-B metaheuristics. Research results obtained during the last few years in each of the above categories are briefly discussed. The last part of the paper includes comments on directions of future research in the population-based optimization.

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Authors and Affiliations

  1. Gdynia Maritime University, Gdynia, Poland

    Piotr Jedrzejowicz

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  1. Piotr Jedrzejowicz
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Editors and Affiliations

  1. Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Ngoc Thanh Nguyen

  2. University of Pau and Pays de l’Adour, Pau, France

    Richard Chbeir

  3. University of Pau and Pays de l’Adour, Pau, France

    Ernesto Exposito

  4. University of Pau and Pays de l’Adour, Pau, France

    Philippe Aniorté

  5. Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

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Jedrzejowicz, P. (2019). Current Trends in the Population-Based Optimization. In: Nguyen, N., Chbeir, R., Exposito, E., Aniorté, P., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2019. Lecture Notes in Computer Science(), vol 11683. Springer, Cham. https://doi.org/10.1007/978-3-030-28377-3_43

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