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Chernobyl disaster optimizer (CDO): a novel meta-heuristic method for global optimization

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Abstract

This paper proposes a novel meta-heuristic optimization method, namely “Chernobyl Disaster Optimizer (CDO)”. The underlying concepts and principles behind the proposed approach is inspired by the nuclear reactor core explosion of Chernobyl. In CDO, radioactivity happened because of nuclear instability, which different types of radiations are emitted from nuclei. The most common kinds of these radiations are called gamma, beta, and alpha particles. These particles fly away from the explosion point (high pressure point) to the low pressure point (the human standing point), which are harmful to the humans. The CDO mimics the process of nuclear radiation while attaching human after the nuclear explosion. The main steps of nuclear explosion and attaching human are implemented in which gamma, beta, and alpha particles are involved in this process. The CDO is evaluated with optimizing “Congress on Evolutionary Computation (CEC 2017)” test bed suites. In addition, it is compared against well-known optimization methods, such as “Sperm Swarm Optimization” and “Gravitational Search Algorithm”. The experimental results prove its efficiency, which can be considered as viable alternative.

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  1. Departments of Computer Information System and Computer Science, Faculty of Computer Science and Informatics, Amman Arab University, Amman, Jordan

    Hisham A. Shehadeh

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We give our consent for the publication of identifiable details, which can include photograph(s) and/or videos and/or case history and/or details within the text (“Material”) to be published in the above Journal and Article. We confirm that we have seen and been given the opportunity to read both the Material and the Article (as attached) to be published by your journal. In Addition, a sample of data of this paper will be available upon request. The code of our algorithm, namely, SSO is available via the following link: https://www.mathworks.com/matlabcentral/fileexchange/92150-sperm-swarm-optimization-sso, https://www.mathworks.com/matlabcentral/fileexchange/92130-hssogsa, https://www.springerprofessional.de/en/a-hybrid-sperm-swarm-optimization-and-gravitational-search-algor/18968734.

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Appendix A

Appendix A

Table

Table 10 Problems of CEC 2017 test bed suites
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10 shows the mathematical formulation of 23 test bed problems of a well-known “Congress on Evolutionary Computation (CEC 2017)” test bed suites.

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Shehadeh, H.A. Chernobyl disaster optimizer (CDO): a novel meta-heuristic method for global optimization. Neural Comput & Applic 35, 10733–10749 (2023). https://doi.org/10.1007/s00521-023-08261-1

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