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This paper proposes a method for multi‐terminal resistor optimal design based on a stochastic optimization algorithm coupled with a high accuracy boundary element method numerical analysis module using spline boundary elements. The aim of the optimization process is to find out the optimal shape of the resistor so that the values of the partial resistances between its terminals can be globally reduced. In the first part of the paper, a short introduction to the boundary element method formulation using spline interpolation of the boundary unknowns is performed. Then, the genetic algorithm optimization method is briefly described, emphasising the numerical implementation particularities related to the actual application. In the second part of the paper, three numerical examples are proposed and the final conclusions are outlined.

This paper proposes to extend the combination of Extended Finite Element Method (XFEM) and Level Set Method (LSM) from structural mechanics to electromagnetics. Based on this approach, the actual stage of the research work, dedicated to the investigation, development, implementation and validation of a shape optimization methodology, particularly tailored for 2D electric structures is described.

The proposed numerical approach is based on the efficiency of the XFEM and the flexibility of the LSM, to handle moving material interfaces without remeshing the whole studied domain at each optimization step.

This approach eliminates the conventional use of discrete finite elements and provides efficient, stable, accurate and faster computation schemes in comparison with other methods.

This research is limited to shape optimization of two‐dimensional electric structures, however, the work can be extended to 3D ones too.

The implementation of the proposed numerical approach for the shape optimization of a planar resistor is hereby described.

The main value of the proposed approach is a powerful and robust numerical shape optimization algorithm that demonstrates outstanding suppleness of handling topological changes, fidelity of boundary representation and a high degree of automation in comparison with other methods.

This paper aims to investigate whether Kazakh small- and medium-sized enterprises (SMEs) that claim to compete with the informal sector are more likely to invest in innovation than their competitors who do not perceive such pressure.

Logistic regression and classification trees are performed on the Business Environment and Enterprise Performance Survey (2018–2020) to examine whether the degree of informal competition correlates with a firm's propensity to innovate.

The findings show that informal sector competition is a critical factor that shapes the organizational behaviour of Kazakh SMEs. There is a stimulating positive effect of informal competition on both product and process innovation, depending on its perceived intensity.

This study challenges conventional thinking that still views informal sector competition as a barrier to innovation and entrepreneurship by assessing whether innovation is compatible with informal entrepreneurial practice.