A Reference Vector-Based Simplified Covariance Matrix Adaptation Evolution Strategy for Constrained Global Optimization

Kumar, Abhishek; Das, Swagatam; Mallipeddi, Rammohan

doi:10.1109/tcyb.2020.3013950

Cited by 25 publications

(6 citation statements)

References 66 publications

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“…Thus, our future research will focus on integrating surrogate-assisted approaches [32]- [34] into the i-ACLA-CGP framework, wherein surrogates are utilized as a recommendation system while learning the user preferences. Moreover, based on recent insight regarding a voting approach to evolutionary algorithms [25], [26] and constraint handling techniques [60], [61], we may further boost our approach by utilizing such methods to capture more complex user preferences. These techniques may be useful if we suppose the user preferences as constraints that the loading algorithms must satisfy.…”

Section: Discussionmentioning

confidence: 99%

Automatic Construction of Loading Algorithms With Interactive Genetic Programming

et al. 2022

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The design of a freight loading pattern is often conducted by skilled workers, who handle unquantifiable objectives and/or preferences. Our previous study presented an automatic construction technique for loading algorithms using genetic programming-based hyper-heuristics; however, this technique is only applicable to fully quantifiable loading problems. Thus, the approach described in this paper integrates an interactive framework with users into our previous technique to automatically construct algorithms that derive loading patterns adapted to user objectives and/or preferences. Thus, once a loading algorithm has been derived with user interactions, it can be reused to obtain the preferred loading patterns on other problems without any additional interactions. Experimental results show that the proposed algorithm can produce loading algorithms adapted for user preferences under a limit of 50 human interactions. Further, we also show that the derived loading algorithms can be applicable to different loading situations without any additional user interactions. Thus, these observations suggest the benefit of our approaches in reducing the burden placed on skilled workers for practical LPD tasks.

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Section: Discussionmentioning

confidence: 99%

Automatic Construction of Loading Algorithms With Interactive Genetic Programming

et al. 2022

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“…Substituting the electrical field from Equation ( 11) into Equation (12), the Poisson equation is given by:…”

Section: Finite Element Methodsmentioning

confidence: 99%

“…The task to be faced in this research is that the global minimum is not guaranteed in the non‐linear optimization problems making this a challenge. Some methods that could successfully be applied to design optimization of electrical equipment are: particle swarm optimization (PSO) [9] genetic algorithm (GA) [10], proxy models (PM) [11], covariance matrix adaptation evolution strategy (CMA‐ES) [12], firefly algorithm (FA) [13], cuckoo search (CS) [14], among other optimization methods.…”

Section: Introductionmentioning

confidence: 99%

Optimal design of electrical power distribution grid spacers using finite element method

Stefenon

Seman

Ovejero

et al. 2022

IET Generation Trans & Dist

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Spacers in the compact power distribution network are essential components for the support, organization, and spacing of conductors. To improve the reliability of these components and have an optimized network design, it is necessary to evaluate the performance of the variation of their geometric parameters. The analysis of these components is fundamental, considering that there are several models available that are validated by the electric power utilities. Due to the various possible design shapes, it is necessary to use an optimized model to reduce the electric potential located in specific sites, improving the reliability in the component, as the higher electrical potential results in a greater chance of failure to occur. The finite element method (FEM) stands out for evaluating the distribution of electrical potential. In this paper, an FEM is used to evaluate variations in vertical and horizontal dimensions in spacers used in the 13.8 kV power grid. The models are analyzed in relation to their behavior regarding the potential distribution on their surface. From the results of these variations, the model is optimized by means of a mixed-integer linear problem (MILP), replacing the FEM output with a ReLU network substitute model, to obtain a spacer with more efficiency to be used in semi-insulated distribution networks.

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“…In the literature, numerous DE-based algorithms have been proposed to solve COPs. However, existing algorithms suffer from serious issues, which are as follows [56].…”

Section: Differential Evolutionmentioning

confidence: 99%

Power Flow Analysis of Islanded Microgrids: A Differential Evolution Approach

et al. 2021

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Power flow (PF) analysis of microgrids (MGs) has been gaining a lot of attention due to the evolution of islanded MGs. To calculate islanded MGs' PF solution, a globally convergent technique is proposed using Differential Evolution (DE)-a popular optimization algorithm for global non-convex optimization. This paper formulates the PF problem as a constrained optimization problem (COP) considering all the operating conditions of the Droop Controlled Islanded MGs (DCIMGs). To solve the proposed COP, DE-NGM, (Epsilon based Differential Evolution with Newton-Gauss-based mutation) is proposed. The proposed algorithm, DE-NGM, is a novel variant of DE since it comprises a novel mutation operator, Newton-Gauss-based mutation (NGM). NGM includes all the important features of DE's mutation strategies as well as reduces the constraint violation by utilizing the information of constraint-space. Numerical experiments validate that the global convergence ability of proposed algorithms in solving COPs than existing state-of-the-art algorithms. Furthermore, the proposed algorithm as a PF tool has better robustness than existing tools on ill-and well-conditioned systems with heavy loads, different limit violations, and inappropriate final solutions (far from the flat start). The performed comparative analysis confirms good agreement of accuracy and efficacy with the existing method for islanded MG's PF.

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A Reference Vector-Based Simplified Covariance Matrix Adaptation Evolution Strategy for Constrained Global Optimization

Cited by 25 publications

References 66 publications

Automatic Construction of Loading Algorithms With Interactive Genetic Programming

Automatic Construction of Loading Algorithms With Interactive Genetic Programming

Optimal design of electrical power distribution grid spacers using finite element method

Power Flow Analysis of Islanded Microgrids: A Differential Evolution Approach

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