Arranging university course's timetable is problematic. It differs from other timetabling problems in terms of conditions. A complete university timetable must reach several requirements involving students, subjects, lecturers, classes, laboratory's equipments, etc. This paper proposes a genetic algorithm model applied for improving effectiveness of automatic arranging university timetable. Hard constraints and soft constraints for this specific problem were discussed. In addition, the genetic elements were designed and the fitness function was proposed. Three genetic operators: crossover, mutation, and selection were employed. A simulation was conducted to obtain some results. The results show that the proposed GA model works well in arranging a university timetable. With 0.70 crossover rate, there is no hard constraints appeared in the timetable.

Arranging examination timetable is problematic. It differs from other timetabling problems in terms of conditions. A complete timetable must reach several requirements involving course, group of student sitting the exam in that course, etc. It is similar to the course's timetable but not the same. Many differences between them include the way to create and the requirements.This paper proposes an adaptive genetic algorithm model applied for improving effectiveness of automatic arranging examination timetable. Hard constraints and soft constraints for this specific problem were discussed. In addition, the genetic elements were designed and the penalty cost function was proposed. Three genetic operators: crossover, mutation, and selection were employed. A simulation was conducted to obtain some results. The results show that the proposed GA model works well in arranging an examination timetable. With 0.75 crossover rate, there is no hard constraints appeared in the timetable.

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Central Bank Digital Currency (CBDC) is a digital version of domestic currency with a unit of account equivalent to its domestic currency. Blockchain or Distributed Ledger technology (DLT) can be used to implement CBDC to execute and settle peer-to-peer transactions. With the emergence of private money, such as cryptocurrencies and stablecoins, and the growing use of digital payments to lessen the global pandemic spread, CBDC is an active research area among central banks worldwide. Many central banks started their CBDC projects by building DLT proofs of concept (PoCs) to replicate wholesale payment systems and expand their investigation into other use cases, such as delivery versus Payment (DvP) and cross-border remittance. Many large economies like the United States have projects exploring CBDC. The People’s Bank of China (PBoC), China Central Bank, has already started a pilot testing of their digital retail currency. This paper discusses the application of blockchain for CBDC by presenting CBDC projects by central banks. Moreover, this paper analyses issues, identify challenges and discusses future works in this rapidly evolving field.

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