Mehmood, K., Chaudhary, N. I., Khan, Z. Braik, M., Hammouri, A., Atwan, J., Al-Betar, M. A. Metaheuristic algorithms based on physics have been designed by drawing inspiration from concepts, phenomena, laws, and forces in physics. & Awadallah, M. A. Energy 78, 276289 (2014). This section will introduce the mother optimization algorithm (MOA) and its mathematical model. Experiments are systematic observations or measurements, preferably made under controlled conditionsthat is, under conditions in which a single variable changes. 3. This is a possible explanation for the origin of birds, so it is a hypothesis. 2022, 6802967 (2022). (9). If you have ever seen something going on and wondered why or how it happened, you have started down the road to discovery. The structure of the remaining sections in the paper is as follows: a literature review is presented in the Literature review section, followed by the introduction and modeling of the proposed MOA approach in the Mother optimization algorithm section. In addition to providing better values for statistical indicators, it can be seen that the boxplot diagrams of these functions have a smaller area, less dispersion of results in different executions, and a better mean value compared to competitor algorithms. Math. Researchers have developed numerous metaheuristic algorithms to solve optimization problems more effectively. Appl. The Scientific Method What is the scientific method? The results show that MOA has outperformed the other algorithms and has been able to provide the global optimal for F9 and F11 functions. Inf. IEEE Trans. Distance-fitness learning TLBO (DFL-TLBO)78 variant that employs a brand-new distance-fitness learning (DFL) strategy to enhance searchability. Article The development of rules for scientific reasoning has not been straightforward; scientific method has been the subject of intense and recurring debate throughout the history of science, and eminent natural philosophers and scientists have argued for the . 9. 2, e976 (2022). MathSciNet Chapter 6: Scientific Problem Solving - Lucid Philosophy (8). Test the hypothesis and collect data. MATH Int. Trojovsk, P. & Dehghani, M. Pelican optimization algorithm: A novel nature-inspired algorithm for engineering applications. Convergence curves of performance of MOA and competitor algorithms in solving CEC 2017 test suite. It aims to increase global search and exploration capabilities by making significant changes in the position of the population members. Xu, Y. et al. Appl. Question: Written Assignment: Biology and Technology in the Real World Addresses outcomes 1-4: recognize and explain how the scientific method is used to solve problems make observations and discriminate between scientific and pseudoscientific explanations weigh evidence and make decisions based on strengths and limitations of scientific knowle. Among the most significant types of interactions between a mother and her children are the three processes of (i) education, (ii) advice, and (iii) upbringing. Figure3 shows the convergence curves of MOA and competitor algorithms in solving functions F1 to F23. Evol. Shah-Hosseini, H. Principal components analysis by the galaxy-based search algorithm: A novel metaheuristic for continuous optimization. Appl. Solved Written Assignment: Biology and Technology in the - Chegg ABC algorithm is inspired by the foraging behavior of honey bees in the colony. Metaheuristic algorithms must be able to balance exploration and exploitation during the search process, to bring usable solutions for optimization problems. Research.. 11(4), 341359 (1997). For example, the observation that we experience alternating periods of light and darkness corresponding to observed movements of the sun, moon, clouds, and shadows is consistent with either of two hypotheses: Suitable experiments can be designed to choose between these two alternatives. Metaheuristic algorithms based on evolutionary principles have drawn inspiration from biological sciences, genetics, and the idea of natural selection. As the population members positions are updated in each iteration, the best population member also needs to be updated accordingly. Technical Report (2016). The scientific method is a process that is used to solve complex problems in any situation. Artif. Doumari, S. A. et al. This articles innovation and novelty are introducing a new metaheuristic method called mother optimization algorithm (MOA) that mimics the human interaction between a mother and her children. The optimization results of high-dimensional multimodal functions showed that MOA with high exploration and global search ability could discover the main optimal area in the problem-solving space by avoiding getting stuck in local optima. 1: The Scientific Method. Expert Syst. Montazeri, Z. One of the primary duties of mothers in raising their children is to counsel them and not enable them to misbehave. Upon analysis and comparison of the simulation results, it was found that the proposed MOA outperforms competing algorithms with superior and significantly more competitive performance. Binary spring search algorithm for solving various optimization problems. PubMed Central The development of a hypothesis is a very important. This subsection presents a statistical analysis comparing the performance of MOA with competitor algorithms to determine the significance of MOAs superiority. 27(2), 495513 (2016). Dokeroglu, T., Sevinc, E., Kucukyilmaz, T. & Cosar, A. Int. Comput. Particle swarm optimization (PSO)34, ant colony optimization (ACO)35, artificial bee colony (ABC)36, and firefly algorithm (FA)37 are among the most widely recognized swarm-based metaheuristic algorithms. 2. The upbringing leads to an increase in the ability of local search and exploitation in the MOA phase by making small changes in the position of the population members. Presentation on snakes set | News, Sports, Jobs - The Mining Journal The findings of optimization of high-dimensional multimodal functions indicate the high ability of MOA in global search and exploration. & Dehghani, M. POA: Puzzle optimization algorithm. IEEE Trans. A. This random search process must be managed at both local and global levels in a way so that by balancing them during the search process, the algorithm can: first, based on the global search, thoroughly scans the problem-solving space in all regions to avoid getting stuck in local optima, Second, based on local search, with careful scanning around promising solutions, converge towards better solutions. In this section, the proposed MOAs performance in solving optimization problems is evaluated by testing its efficiency on fifty-two standard benchmark functions, including unimodal (F1 to F7), high-dimensional multimodal (F8 to F13), and fixed-dimensional multimodal (F14 to F23) types88, as well as the CEC 2017 test suite (C17F1, and C17F3 to C17F30)89. Borji, A. Simulation studies and results are summarized in the Simulation analysis and results section, while the efficiency of MOA in handling real-world applications is evaluated in the MOA for real-world applications section. Sci. Furthermore, the application of MOA on four engineering design problems demonstrates the efficacy of the proposed approach in solving real-world optimization problems. Seadawy, A. R., Rizvi, S. T. R., Ahmad, S., Younis, M. & Baleanu, D. Lump, lump-one stripe, multiwave and breather solutions for the Hunter-Saxton equation. Eng. Free Essay: Scientific Method - 434 Words | Studymode Examples of qualitative observations include the following: the outside air temperature is cooler during the winter season, table salt is a crystalline solid, sulfur crystals are yellow, and dissolving a penny in dilute nitric acid forms a blue solution and a brown gas. & Khayatazad, M. A new meta-heuristic method: Ray optimization. This is a statement that tries to explain the relationship between the temperature and the density of air based on fundamental principles, so it is a theory. Article PDF Scientific Method How do Scientists Solve problems - UGA The theory developed to explain the extinction of the dinosaurs, for example, is that Earth occasionally encounters small- to medium-sized asteroids, and these encounters may have unfortunate implications for the continued existence of most species. Hence, when comparing the performance of multiple metaheuristic algorithms on an issue, the one that performs the search process more effectively and provides a better solution will outperform others. This is a general statement of a relationship between the properties of liquid and solid water, so it is a law. 52(4), 21912233 (2019). Mater. Based on the simulation results, MOA is the best optimizer for F14, F15, F21, F22, and F23 functions. In dealing with functions C17F4 to C17F30, it is evident that MOA moves towards better solutions based on the appropriate ability in exploration during successive iterations, and this process continues until the final iterations. This procedure consists of making observations, formulating hypotheses, and designing experiments, which in turn lead to additional observations, hypotheses, and experiments in repeated cycles (Figure \(\PageIndex{1}\)). Ghasemi, M., Ghavidel, S., Ghanbarian, M. M., Gharibzadeh, M. & Vahed, A. Local search, or exploitation, involves achieving better solutions around the obtained solutions. Energy 258, 124848 (2022). Kvasov, D. E. & Mukhametzhanov, M. S. Metaheuristic vs. deterministic global optimization algorithms: The univariate case. 3(2), 9599 (1988). The scientific method (article) | Khan Academy & Zhuang, J. Small-world optimization algorithm for function optimization. Additionally, MOA is the best optimizer for benchmark functions F8, F10, F12, and F13. One such algorithm is teachinglearning based optimization (TLBO), which simulates educational interactions between teachers and students in the classroom75. Int. J. Intell. Inf. Because scientists can enter the cycle shown in Figure \(\PageIndex{1}\) at any point, the actual application of the scientific method to different topics can take many different forms. Mothers use various forms of encouraging children to improve their skills in the education process. Math. 388, 114194 (2022). This involves observing and gathering information from a certain aspect of the natural. Kennedy, J. Comput. Zeidabadi, F.-A. Intell. The interpretation of the boxplot diagrams is as follows in the functions F1 to F6, F9, and F11. The high level of intelligence involved in a mother's care of her children presents a promising opportunity for the design of a novel metaheuristic algorithm. PubMed 95(4), 045210 (2020). Overall, the analysis of the simulation results indicates that MOA, with its high ability to balance exploration and exploitation, performs better in solving fixed-dimension multimodal functions compared to the competitor algorithms. For instance, the authors of this paper were inspired by the NFL theorem to design a new metaheuristic algorithm that can solve optimization problems in various scientific and real-world applications. The study of scientific method is the attempt to discern the activities by which that success is achieved. Design an experiment (s) to test the hypothesis. A scientist may enter the cycle at any point. A FKPCA-GWO WDBiLSTM classifier for intrusion detection system in cloud environments. Continua 70(3), 56315649 (2022). 95, 5167 (2016). You may find, as the saying goes, that one problem leads to another. Man Cybern. Storn, R. & Price, K. Differential evolutionA simple and efficient heuristic for global optimization over continuous spaces. The Scientific Method: What Is It? - WebMD Scientific Reports The scientific method is a procedure consisting of a series of steps with the goal of problem-solving and information-gathering. Some other physics-based algorithms are magnetic optimization algorithm (MOA)66, artificial chemical reaction optimization algorithm (ACROA)67, ray optimization (RO) algorithm68, and small world optimization algorithm (SWOA)69. The main inspiration behind the puzzle optimization algorithm (POA)73 design has been the skill and accuracy required to assemble puzzle pieces. Additionally, MOA has performed the best among the competitor algorithms in solving F7. Entropy 23(4), 491 (2021). 243, 108457 (2022). Artif. A new two-stage algorithm for solving optimization problems. Mathematics 10(22), 4217 (2022). MOA is the top-performing optimizer for C17F1, C17F3 to C17F6, C17F8 to C17F21, and C17F23 to C17F30, except for C17F2 due to its unstable behavior. Global search, or exploration, involves comprehensively scanning the search space to discover the main optimal area and prevent getting stuck in local optima. Kuhn, A. L. The Mothers Role in Childhood Education: New England Concepts, 18301860 (Yale University Press, 1947). Intell. ADS The Method consists of these steps: Observation, Question, Hypothesis, Prediction, Conclusion, and Results. The mathematical model and full description of these real-world applications are provided for TCS and WB in Ref.91, for SR in Ref.92, 93, and for PV in Ref.94. Abualigah, L., Abd Elaziz, M., Sumari, P., Geem, Z. W. & Gandomi, A. H. Reptile search algorithm (RSA): A nature-inspired meta-heuristic optimizer. Article The analysis of boxplot diagrams intuitively shows that MOA has provided superior performance compared to competitor algorithms by delivering better results for statistical indicators such as mean and standard deviation. Metaheuristic algorithms have many advantages, including simple concepts, easy implementation, and the ability to efficiently solve nonlinear, nonconvex, discontinuous, nondifferentiable, high-dimensional, and NP-hard problems, as well as problems in nonlinear and unknown search spaces. A gravitational search algorithm. CAS J. Mech. There are a few minor differences between the two discovery styles. After meeting an animal up close, students will learn to use the scientific method as they attempt to problem solve and investigate animals in their habitats. Examine the results and draw conclusions. Abstract: While the encoder-decoder structure is widely used in the recent neural construction methods for learning to solve vehicle routing problems (VRPs), they are less effective in searching solutions due to deterministic feature embeddings and deterministic probability distributions. Lu, C., Gao, L., Li, X. Sci. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The test is used to determine if there is a significant difference between the means of two data samples. Note when you observe something that you can't readily explain with your existing knowledge, or something that may have another explanation than the one commonly given. Adv. The first place of education in society is undoubtedly the family, and the mother is the essential educational element in raising children86. Article The Scientific Method is the standardized procedure that scientists are supposed to follow when conducting experiments, in order to try to construct a reliable, consistent, and non-arbitrary representation of our surroundings. 257, 108271 (2022). In Proc. ISSN 2045-2322 (online). The scientific method: A problem-solving tool. In this article, we propose the feature embedding refiner (FER) with a novel and generic encoder . MATH White shark optimizer: A novel bio-inspired meta-heuristic algorithm for global optimization problems. (10). Chapter It employs a random search in the problem-solving space and uses random operators to provide appropriate solutions for optimization problems. & Abu Doush, I. Coronavirus herd immunity optimizer (CHIO). PubMed (7) to simulate keeping the child away from bad behavior. & Shu, L. A survey of using swarm intelligence algorithms in IoT. However, even if the optimal global solution is not found, the solutions obtained from metaheuristic algorithms are usually still acceptable as quasi-optimal because they tend to be close to the optimal global solution. 3-test the hypothesis. Trojovsk, E. & Dehghani, M. A new human-based metahurestic optimization method based on mimicking cooking training. the scientific method as a logical way of solving a problem. and E.T., software, M.D. 4 and the convergence curves of metaheuristic algorithms performance are drawn in Fig. The results show that MOA has achieved convergence to the global optimum for functions F1 to F6 with high exploitation ability. After a hypothesis has been formed, scientists conduct experiments to test its validity. Mother optimization algorithm: a new human-based metaheuristic - Nature Black hole: A new heuristic optimization approach for data clustering. SCSh4. Rep. 12(1), 9924 (2022). League championship algorithm (LCA)70, football game based optimizer (FGBO)71, and volleyball premier league (VPL)72 are examples of game-based metaheuristic algorithms that simulate the rules and behavior of football and volleyball league matches, respectively. J. Intell. Example: Which brand of battery lasts the longest? 6(12), 132140 (2011). Mathematics 11(11), 2512 (2023). Zeidabadi, F. A. J. Glob. Electr. 6. 33(10), 50115042 (2021). Dehghani, M. et al. In order for an experimental finding to be considered sound, an experiment must be repeated multiple times and by different teams of . 11(3), 1286 (2021). Comput. Xing, Z., Zhu, J., Zhang, Z., Qin, Y. Laws are unlikely to change greatly over time unless a major experimental error is discovered. & de Oliveira, W. R. An automatic methodology for construction of multi-classifier systems based on the combination of selection and fusion. The temperature is measured before and after a change is made in a system, so these are quantitative observations. ADS The quality of the results obtained from MOA is compared with twelve well-known metaheuristic algorithms, including GA, PSO, GSA, GWO, MVO, WOA, TSA, MPA, AVOA, WSO, and RSA. Du, H., Wu, X. The scientific method is a process for experimentation that is used to explore observations and answer questions. Mezura-Montes, E. & Coello, C. A. C. Useful infeasible solutions in engineering optimization with evolutionary algorithms. 49(67), 584601 (2022). Google Scholar. The analysis of the optimization results indicates that MOA has demonstrated superior performance in solving unimodal functions F1 to F7 due to its high ability in exploitation. Google Scholar. Ask a question. Sensors 22(3), 855 (2022). 4-analyze the results. A., Cheema, K. M. & Raja, M. A. MathSciNet de Lima, T. P. F., da Silva, A. J., Ludermir, T. B. The schematic of this design is shown in Fig. Comput. Deterministic methods effectively solve simple, linear, convex, continuous, differentiable, and low-dimensional optimization problems. The development of this theory is a good exemplar of the scientific method in action (see Figure \(\PageIndex{2}\) below). Syst. The scientific method starts with a question. The mean index is used as a ranking criterion for metaheuristic algorithms in optimizing each benchmark function. A process of experimentation and data collection then follows. 273, 112131 (2014). Evol. PubMed Central Sci. Seadawy, A. R., Iqbal, M. & Lu, D. Propagation of kink and anti-kink wave solitons for the nonlinear damped modified Kortewegde Vries equation arising in ion-acoustic wave in an unmagnetized collisional dusty plasma. Mathematically, any optimization problem can be represented using three key components: decision variables, constraints, and objective functions2. In this article, we'll demystify the scientific method by breaking it down to its basic parts. The Engineering Design Process or The Scientific Method 1(1), 6782 (1997). ADS Figure \(\PageIndex{2}\) summarizes the application of the scientific method in this case. (2) at the start of the optimization process. Therefore, the proposed MOA uses mathematical modeling of caring and educational behaviors. Google Scholar. Plus 133, 110 (2018). Dehghani, M., Trojovsk, E. & Trojovsk, P. A new human-based metaheuristic algorithm for solving optimization problems on the base of simulation of driving training process. In the realm of science, problems that have multiple feasible solutions are referred to as optimization problems. 4. J. Intell. The algorithms population consists of candidate solutions represented as vectors in the problem space. 264273 (Springer, 2006). and M.D., formal analysis, I.M. Aided Des. In doing so, they are using the scientific method. In MOA design, for each member of the population, the position of other population members with a greater value of the objective function than it has is considered deviant behavior that should be avoided. 2018(4), 7073 (2018). All data generated or analyzed during this study are included directly in the text of this submitted manuscript. Energy 254, 124403 (2022). IFSA 2007. The analysis of the simulation results indicates the high ability of MOA in exploration, exploitation, and balancing during the search process. Analyze the data Interpret the data and draw conclusions that serve as a starting point for new hypothesis (also called a theory.) Eng. where \(F\) is the vector of values of the objective function and \({F}_{i}\) is the value of the objective function for the \(i\)th candidate solution. where \({X}_{i}^{P3}\) is the new position calculated for the \(i\)th population member based on third phase of the proposed MOA, \({x}_{i,j}^{P3}\) is its \(j\)th dimension, \({F}_{i}^{P3}\) is its objective function value, the function \(\mathrm{rand}(\mathrm{0,1})\) generates a random number in the interval \(\left[0, 1\right]\), and \(t\) is the actual value of the iteration counter. PubMed 318, 245259 (2018). In International Symposium on Stochastic Algorithms 169178 (Springer, 2009). State the problem that you will study as clearly and concisely as possible. These stochastic approaches offer a more flexible and robust framework that can better handle the complexity and uncertainty of these types of issues5. The findings of optimizing unimodal functions indicate MOAs high ability in local search and exploitation. The findings of the statistical analysis from the Wilcoxon signed-rank test show that MOA has a significant statistical superiority compared to the twelve well-known metaheuristic algorithms in managing the optimization problems studied in this paper. The advice phase leads to an increase in the MOAs capability in global search and exploration by making significant changes in the location of the population members. Once the full implementation of the algorithm is completed, MOA presents the best candidate solution as the solution to the problem. https://doi.org/10.1038/s41598-023-37537-8, DOI: https://doi.org/10.1038/s41598-023-37537-8. In Mexican International Conference on Artificial Intelligence 652662 (Springer, 2005). 5. Article Appl. Unimodal functions F1 to F7, as well as C17F1 and C17F3 from CEC 2017 test suite, because they do not have local optima, are suitable options to evaluate the ability of local search and exploitation of metaheuristic algorithms. These advantages have made metaheuristic methods popular among researchers6. Scientific Method: The scientific method is a useful tool in performing an experiment or scientific investigation.
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