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The water optimization algorithm: a novel metaheuristic for solving optimization problems

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Abstract

Metaheuristic algorithms (MAs) are used to find the answers to NP-Hard problems. NP-Hard problems basically refer to a set of optimization problems that cannot be solved in a polynomial at a time. MAs try to find the optimal or near-definitive answer in the shortest possible time to solve such problems and a set of optimization algorithms with different origins. These algorithms may be inspired by the natural sciences, physics, mathematics, and political science. However, a particular Metaheuristic algorithm may not provide the best answer to all problems. Each MA may have a better response to specific problems than other similar algorithms. Therefore, researchers will try to introduce and discover new algorithms to find optimal answers to a wide range of problems. In this paper, a new Meta-heuristic algorithm called the Water optimization algorithm (WAO) is presented. WAO is inspired by the chemical and physical properties of water molecules. The main idea of the proposed algorithm is to link water molecules together to find the optimal points. Factors such as particle motion, particle evaporation, and particle bonding have created a mechanism based on swarm intelligence and physical intelligence that inspired this algorithm to solve persistent problems. In this algorithm, answers are defined as a water molecule, a set of them is defined as a local answer. Water bonds provide the right move towards the optimal response. In evaluating the performance of the proposed algorithm, the proposed method is applied to some standard functions and some practical problems. The results obtained from the experiments show that the proposed algorithm has provided appropriate and acceptable answers in terms of execution time and accuracy compared to some similar algorithms.

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Authors and Affiliations

  1. Department of Computer Engineering, Shafagh Institute of Higher Education, Tonekabon, Iran

    Arman Daliri, Ali Asghari & Mahmoud Alimoradi

  2. Department of Computer Engineering, Rasht Branch, Islamic Azad University, Rasht, Iran

    Hossein Azgomi

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  1. Arman Daliri
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  2. Ali Asghari
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  3. Hossein Azgomi
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  4. Mahmoud Alimoradi
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Correspondence to Ali Asghari.

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Appendix: Validation tests

Appendix: Validation tests

Table 27 Results of industrial chemical processes problems (RC01 -RC07)
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Table 28 Results of process synthesis and design problems (RC08 -RC14)
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Table 29 Results of Mechanical Engineering Problems (RC15 -RC33)
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Table 30 Results of Power System Problems (RC34 -RC44)
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Table 31 Results of Power Electronic Problems (RC45 -RC50)
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Table 32 Results of Livestock Feed Ration Optimization Problems (RC51 -RC57)
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Table 33 10D evaluation results
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Table 34 15D evaluation results
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Table 35 20D evaluation results
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Table 36 50D evaluation results
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Table 37 Adjustment of Taguchi control parameters in five types, for 10 algorithms compared with WAO
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Daliri, A., Asghari, A., Azgomi, H. et al. The water optimization algorithm: a novel metaheuristic for solving optimization problems. Appl Intell 52, 17990–18029 (2022). https://doi.org/10.1007/s10489-022-03397-4

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