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European countries are promoting the use of renewable energy sources in order to reduce their dependence on imported energy. Renewable sources of energy are a promising solution, but there are downsides too. The integration of renewable energy sources causes problems with the electric power systems, as their energy production is meteorologically dependent. In this paper a system is introduced that represents a solution to this problem, with the activation of users of the distribution part of the electricity network. The system connects the users of the distribution network that are willing to participate in the system environment based on market rules. The participation allows users to offer an adaptation of their consumption of electric energy or production in return for financial incentives. The system accepts or rejects the user's energy adaptation offers on the basis of market principles that are driven by the optimization method (genetic algorithms in the presented case). The system optimizes the total cost amount that is reflected in the integration of a larger portion of the renewable energy sources into the electric energy system. Testing the results of the system operation demonstrates that the developed solution has improved the integration of renewable energy sources and has enabled users to profit from their adaptation to energy consumption or production.

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This study investigates the effects of blockchain technology scalability limitations on the performance of Blockchain-Based Shared Manufacturing (BBSM), an innovative smart-manufacturing paradigm aimed at enhancing the utilization of global manufacturing resources via peer-to-peer (P2P) collaboration of self-organized manufacturing assets. Despite the prevalence of research highlighting blockchain technology’s scalability limitations as the main barrier for adoption, few studies have explored their effects on the operation of blockchain-based systems. The primary goal of the presented research work is to explore the implications of blockchain technology scalability limitations on the BBSM system’s performance and user behavior. To obtain realistic behavior, an experiment is conducted using an online game played by human participants. Analysis of the players’ strategy is used for implementation of a multi-agent simulation model, which is then employed to assess the influence of varying blockchain network configurations on the BBSM concept’s performance. Preliminary experimental findings reveal that a congested blockchain network leads to increased transaction costs and reduced service prices, consequently devaluing the manufacturing role in the BBSM system and causing underutilization of existing maximum production capacities. Moreover, allocating funds to financial activities rather than manufacturing activities yields superior outcomes for system users. Simulation results indicate that the BBSM system’s response to alterations in blockchain network throughput is contingent upon the production function. The findings of this study reveal that the scalability limitations of blockchain technology impair the performance of the BBSM system and affect user behavior in the system, underscoring the necessity for future research to concentrate on incorporating scalable solutions within blockchain-based manufacturing systems.

Researchers in the field of smart manufacturing have recognized the benefits of blockchain technology, which solves the trust problem in the open network without relying on any trusted third party. Blockchain technology enables interaction between otherwise competing manufacturing entities to satisfy increasing customer demands in a trustful way. However, existing blockchain networks are facing limitations, which are defined by the trade-off between scalability, decentralization, and security. The scalability of the blockchain network is defined as the ability of the network to support an increasing load of transactions and it is lower compared to the non-blockchain systems. In order to omit the effects of the limitations, scalability solutions are being presented. This research reviews the literature in the field of blockchain-supported manufacturing concerning scalability solutions. The selected literature has been reviewed and classified according to the type of scalability solution. For each type of scalability solution, the main features of the concepts and connection between blockchain technology and manufacturing system are highlighted and discussed. The main findings of the study are that Layer 1 scalability solutions are better represented in the literature and are predominating in the case of general smart manufacturing systems, whereas Layer 2 scalability solutions are better represented in the case of specific smart manufacturing systems. Based on insights obtained from the presented analysis, future directions and open issues regarding the scalability limitations and solutions in blockchain-supported manufacturing are presented.

Evolution algorithms are optimization methods that mimic a process of the natural evolution. Their stochastic properties result in a huge advantage over other optimization methods, especially regarding solving complex optimization problems. In this paper, several types of evolutionary algorithms are tested regarding a