This perspective article explores the role of data visualisation in decision-making under
deep uncertainty (DMDU), a growing discipline tackling complex socio-environmental …

Climate change impacts are increasingly complex owing to compounding, interacting, and
cascading risks across sectors. However, approaches to support Disaster Risk Management …

The selection of global best (Gbest) exerts a high influence on the searching performance of
multi-objective particle swarm optimization algorithm (MOPSO). The candidates of MOPSO …

This paper proposes a novel optimization approach for multi-scenario multi-objective robust
decision making, as well as an alternative way for scenario discovery and identifying …

This study employed variable moving average (VMA) trading rules and heatmap
visualization because the flexibility advantage of the VMA technique and the presentation of …

The robust decision-making framework (RDM) has been extended to consider multiple
objective functions and scenarios. However, the practical applications of these extensions …

Within the modeling and simulation community, simulation-based optimization has often
been successfully used to improve productivity and business processes. However, the …

Introduction When solving multi-objective combinatorial optimization problems using a
search algorithm without a priori information, the result is a Pareto front. Selecting a solution …

Multi-objective linear fractional programming (MOLFP) is an important field of research. As in
several real-world problems, the decision-makers (DMs) need to find a solution to a MOLFP …

Abstract Design preferences or targets are typically available at system level. A designer is
usually interested in understanding patches of design space at component levels, across …