One of the lessons learned from the global financial crisis in 2008 was raising attention to monitoring and maintaining household vulnerability, particularly household credit risk, by using the default rate as the indicator. The indicator would be worsening at the economic recession, likewise,...

Scheduling problems occur in a broad range of real-world application fields and have attracted a huge set of research articles. However, there is only little research on exact algorithms for scheduling problems, many of which are NP-hard in the strong sense. We investigate the problem on a...

Wayang Kulit, which is an original Indonesian culture, is conditioned by the meaning of life in every performance. However, Wayang Kulit is currently less popular among young people due to a lack of understanding of the art of Wayang Kulit performance. To be able to provide knowledge to the...

A typical Assembly Line Balancing (ALB) Problem aims to optimize the mass production process by assigning the tasks to stations. To deal with the high product variety and short product life cycles, robots are utilized in many production lines. Humans and collaborative robots share the same...

We investigate the limitations of existing quantum algorithms to solve discrete optimization problems. First, we discuss the quantum counting algorithm of Brassard et al. (1998), and show that it has performance that is equivalent to that of a brute-force approach when approximating the number...

The quadratic assignment problem (QAP) is one of the most important combinatorial optimization problems in theory and practice. In this paper, we are proposing a hierarchical data-driven parallel memetic algorithm to solve the problem. A component-based hierarchical system architecture with a...

Harmony search algorithm (HS) cannot always avoid being trapped in local optima, and several local search algorithms have recently been used to overcome this limitation by searching the neighborhood of some solution for improved ones. However, how local search affects the performance of HS has...

Machine learning risks reinforcing biases present in data, and, as we argue in this work, in what is absent from data. In healthcare, biases have marked medical history, leading to unequal care affecting marginalised groups. Patterns in missing data often reflect these group discrepancies, but...

Real-life problems are complex because they are typically made up of several sub-problems interacting. These interactions establish an interdependent relationship in which the quality of one partial solution impacts the quality of other partial solutions. Recently, a new benchmark known as the...