In recent years, distributed ledger technologies, and especially blockchain, have gained tremendous interest from academia, government, and industry. Although various blockchain-based solutions were created, the lack of tools to evaluate these complex distributed systems may hinder the development of the field. Many advantages of blockchain systems can be demonstrated only at large scales, e.g., using thousands of nodes. An investigation of different implementations and design choices is complicated and hardly feasible on real systems. Meanwhile, blockchain simulators give the possibility to repeat the complex real-world processes at a low cost. This work provides the first and an up-to-date systematic review and empirical analysis of blockchain simulators. Simulators are easily extensible and can test the performance of distributed ledgers using different settings and parameters on a single computer. The features and limitations of selected simulators are summarized and experimentally validated. Finally, recommendations for potential future research directions in the field are provided. INDEX TERMS Bitcoin, distributed ledger technology, blockchain, simulators, systematic review.

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In this paper, we present the progress of blockchain technology from the advent of the original publication titled "Bitcoin: A Peer-to-Peer Electronic Cash System," written by the mysterious Satoshi Nakamoto, until the current days. Historical background and a comprehensive overview of the blockchain technology are given. We provide an up-to-date comparison of the most popular blockchain platforms with particular emphasis given to consensus protocols. Additionally, we introduce a BlockLib, an extensively growing online library on blockchain platforms collected from the various sources and designed to enable contributions from the blockchain community. Main directions of the current blockchain research, facing challenges as well as the main fields of applications, are summarized. We also layout the possible future lines in the blockchain technology development.

Classical evolutionary multi-objective optimization algorithms aim at finding an approximation of the entire set of Pareto optimal solutions. By considering the preferences of a decision maker within evolutionary multi-objective optimization algorithms, it is possible to focus the search only on those parts of the Pareto front that satisfy his/her preferences. In this paper, an extended preference-based evolutionary algorithm has been proposed for solving multi-objective optimization problems. Here, concepts from an interactive synchronous NIMBUS method are borrowed and combined with the R-NSGA-II algorithm. The proposed synchronous R-NSGA-II algorithm uses preference information provided by the decision maker to find only desirable solutions satisfying his/her preferences on the Pareto front. Several scalarizing functions are used simultaneously so the several sets of solutions are obtained from the same preference information. In this paper, the experimental-comparative investigation of the proposed synchronous R-NSGA-II and original R-NSGA-II has been carried out. The results obtained are promising.