An efficient algorithm for function optimization: modified stem cells algorithm

Taherdangkoo, Mohammad; Paziresh, Mahsa; Yazdi, Mehran; Bagheri, Mohammad Hadi

doi:10.2478/s13531-012-0047-8

Cited by 28 publications

(12 citation statements)

References 14 publications

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“…Admittedly, genetic algorithms can be efficient for function optimization [12]. The present model may also work in a "biomimetic" manner, since the key-lock principle is technically implemented [13].…”

Section: Discussionmentioning

confidence: 99%

Method and Apparatus for Creating Problem-Solving Complexes from Individual Elements

Mitterauer¹

2014

ABB

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Based on the biological key-lock-principle common in various biological systems such as the human brain, this paper relates to a method and device for creating problem-solving complexes from individual elements that can be coupled with one another and that have different properties to solve problems. The problem solution can be carried out either serially with a large computer, or with several independent, hierarchically joined computers. In this system, an independent control unit that assumes a multitude of tasks and also acts as an interface with access to all participating computers, is assigned to each problem or object class according to the amount of potential problem-oriented solutions. Such a unit prepares the partial solutions found in its computer for the totality of the solutions computed in the associated computers, finally leading to a total problem solution.

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Section: Discussionmentioning

confidence: 99%

Method and Apparatus for Creating Problem-Solving Complexes from Individual Elements

Mitterauer¹

2014

ABB

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“…The stem cells algorithm has been introduced as one of the newest optimization algorithms for optimizing numerical functions and data clustering [8,9]. This algorithm was introduced and implemented on the basis of stem cells behavior in the human body (at the time of entering into the body).…”

Section: Stem Cells Algorithmmentioning

confidence: 99%

Modified stem cells algorithm for Loney's solenoid benchmark problem

Taherdangkoo¹

2011

JAE

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In this paper, we propose a new method for solving the Loney's solenoid benchmark problem based on stem cells algorithm (SCA). The key idea of the algorithm is using a modified version of our proposed stem cells optimization method that can efficiently achieve the best solution for the position and size of two correcting coils in the famous Loney's solenoid problem. The results show the superiority of the proposed method on other previously proposed methods for electromagnetic optimization.

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“…Later many algorithms have been proposed and some of them are ACO [8], PSO [7], etc. [14][15][16][17][18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Binary Monkey-King Evolutionary Algorithm for single objective target based WSN

Balasubramanian¹,

Govindasamy²

2019

EAI Endorsed Transactions on Internet of Things

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INTRODUCTION: Target based WSN faces coverage issue in which many targets could not be efficiently covered by static deployed sensors. OBJECTIVES: This paper covers the issue of coverage problems by deploying the sensors to cover all the targets with minimized sensors in number. METHODS: This paper proposes a Binary based Monkey King Evolutionary Algorithm for solving target based WSN problem, the proposed model consist a Binary method for converting the continuous values into binary form to solve the choice of potential position to place the sensors. RESULTS: The proposed algorithm is evaluated in a 50x50 grid and 100x100 grid to track the performance and the performance of the proposed is compared with GA and PSO. CONCLUSION: This paper utilized the MKE algorithm for improving the efficiency of the target coverage problem in WSN. It mainly focused on a single objective-based solution providing for small scale problems. From the simulation results, it is provided that the proposed MKE algorithm obtained 1.86 % of the F-value, which is higher than the other optimization algorithms such as GA and PSO.

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An efficient algorithm for function optimization: modified stem cells algorithm

Cited by 28 publications

References 14 publications

Method and Apparatus for Creating Problem-Solving Complexes from Individual Elements

Method and Apparatus for Creating Problem-Solving Complexes from Individual Elements

Modified stem cells algorithm for Loney's solenoid benchmark problem

Binary Monkey-King Evolutionary Algorithm for single objective target based WSN

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