Modified stem cells algorithm with enhanced strategy applied to engineering inverse problems in electromagnetics
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Modified stem cells algorithm with enhanced strategy applied to engineering inverse problems in electromagnetics Mohammad Taherdangkoo1,2 Received: 17 July 2020 / Accepted: 1 October 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract One of the important issues in the electromagnetic field is determining the location and volume of two correcting coils in the Loney’s solenoid design problem. Meta-heuristic algorithms have the ability to solve this problem efficiently. However, these algorithms suffer from getting trapped in local optima, finding global optima, and complex implementation process. The performance of meta-heuristic algorithms has been improved by introducing specific parameters and employing various strategies in the implementation process. In this paper, we improved the performance of the modified stem cells algorithm by some changes in distributing cells and introducing the formulation of food sources. Hence, self-renewal and similar processes with the average rate are used simultaneously. We employed the proposed algorithm, MSC-FS algorithm, to solve multiple standard benchmark problems to show its efficiency in the field of mathematics. The results show the excellent performance of MSC-FS algorithm in comparison with the other employed methods. Keywords Electromagnetic · Engineering inverse problems · Global optimization · Meta-heuristic algorithm
1 Introduction The meta-heuristic algorithms are appropriate tools for solving complex engineering problems. Due to the applicability in the field of engineering, many types of researches have been conducted to develop meta-heuristic algorithms. Meta-heuristic algorithms have a fast convergence rate and have been employed to overcome the drawbacks of classical methods in exhaustive search of best solution in a problem space for vast majority of subjects. Being able to escape local optima and avoid premature convergence by using a heuristic strategy, they can achieve optimal solutions in a short-time period. Meta-heuristic algorithms are particularity useful when dealing with large-scale and constrained problems and are considered as an effective solution for a variety of optimization problems.
* Mohammad Taherdangkoo [email protected]; [email protected] 1
Institute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam
Faculty of Electrical‑Electronic Engineering, Duy Tan University, Da Nang 550000, Vietnam
2
In recent years, a number of researches focused on developing meta-heuristic and randomly methods in electromagnetic field because deterministic methods fail to find the global optima. Note that deterministic algorithms were popular in the past. In definite methods, inaccuracies and uncertainties in the design of an engineering problem are often inevitable. Thus, research has been conducted to develop meta-heuristic methods and to optimize the speed of convergence rate by using different parameters and operators. Due to the type of optimization problem in the fiel
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