Coupling of Immune Algorithms and Game Theory in Multiobjective Optimization

The paper presents the application of the IMGAMO (immune game theory multiobective algorithm) in the optimal design of electrothermal microactuators. Several numerical tests on the mathematical benchmark test functions were performed, showing the superiority of the IMGAMO, when a large number of criteria are considered, in comparison to other multiobjective optimizers. A parametric numerical model of an electrothermal microactuaror was developed and verified. Six functionals, which depend on various thermal and mechanical quantities of the microactuator, were proposed, formulated and numerically implemented. These functionals represent real requirements asked of microactuators. The boundary-value problem of an electro-thermo-mechanical field was solved multiple times during the course of optimization by way of the finite element method (FEM). A numerical example of multiobjective optimization of chevron-type electrothermal actuators is included in the paper. Representation of the multi-dimensional Pareto fronts by means of scatter plot matrices, aided by self-organizing maps (SOMs), is presented. The novel method of selecting interesting, compromise-solutions is proposed and described.

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“…IMGAMO is the approach, which take advantages of AIS and game theory and it is used to solve the problems of multiobjective optimization [42,43].…”

Section: Optimal Design System For Electrothermal Microactuatorsmentioning

confidence: 99%

Optimal Design of Electrothermal Microactuators for Many Criteria by Means of an Immune Game Theory Multiobjective Algorithm

2019

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“…The implementation of distributed generation (DG) involved an optimisation process in order to determine the optimal sizing of the DG. There are numerous optimisation techniques such as Stochastic Algorithm [9], Evolutionary Computation [10]- [12] ,Swarm Intelligence [13]- [15], Physical Algorithms [16], Immune Algorithms [17]- [19] and Neural Algorithms [20] [21]. Nowadays, many researchers have turned their attention to meta-heuristic approach due to the increase of computation intelligence technologies [22].…”

Section: Introductionmentioning

confidence: 99%

Hybrid Artificial Immune System-firefly Algorithm Technique for Optimal DG Capacity and Operational Strategy in Distribution System

Yusof¹,

Rahim²,

Hussain³

et al. 2019

ujeee

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This paper presents a study on hybrid optimization technique for optimal distributed generation (DG) capacity and operational strategy in distribution system. In this study, hybrid method namely Artificial Immune System-Firefly Algorithm (AISFA) is developed to determine the optimal size of the schemes respectively in the distribution system. The Firefly Algorithm (FA) which is a type of meta-heuristic algorithm is inspired by the blinking or flashing behaviour of fireflies that is embedded into Artificial Immune System (AIS) algorithm. The aim of this study is to develop the AISFA algorithm in order to improve the voltage profile and minimize losses of distribution system between the different operational strategy and types of DG. The types of DG include DG type 1, DG type 2, and DG type 3. The proposed technique was verified on IEEE 69-bus test system and the program was developed using the MATLAB programming software. The results showed a significant loss reduction in the line losses and voltage profile improvement has been obtained for optimal DG capacity and operational strategy in distribution system. From the simulation, the results were recorded in terms of the total losses and minimum voltage for the system. The results of the optimisation process of DG are utilized for the assistance of power system operators and planners. The power system planner can adopt the suitable sizes and locations from the obtained result for the planning of utility in term of economic and geographical consideration.

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Fuzzy Portfolio Diversification with Ordered Fuzzy Numbers

Marszałek

Burczyński

2017

Artificial Intelligence and Soft Computing

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Coupling of Immune Algorithms and Game Theory in Multiobjective Optimization

Cited by 6 publications

References 9 publications

Optimal Design of Electrothermal Microactuators for Many Criteria by Means of an Immune Game Theory Multiobjective Algorithm

Optimal Design of Electrothermal Microactuators for Many Criteria by Means of an Immune Game Theory Multiobjective Algorithm

Hybrid Artificial Immune System-firefly Algorithm Technique for Optimal DG Capacity and Operational Strategy in Distribution System

Fuzzy Portfolio Diversification with Ordered Fuzzy Numbers

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