Forecasting has always been at the forefront of decision making and planning. The
uncertainty that surrounds the future is both exciting and challenging, with individuals and …

This paper provides an overview of developments in robust optimization since 2007. It seeks
to give a representative picture of the research topics most explored in recent years …

The optimization of the product portfolio problem under return uncertainty is addressed here.
The contribution of this study is based on the application of a hybrid improved artificial …

We propose piecewise linear kernel-based support vector clustering (SVC) as a new
approach tailored to data-driven robust optimization. By solving a quadratic program, the …

Climate change is having a significant impact on ecosystem services and is likely to become
increasingly important as this phenomenon intensifies. Future impacts can be difficult to …

Financial risk measurement relies on models of prices and other market variables, but
models inevitably rely on imperfect assumptions and estimates, creating model risk …

Since the pioneering work of Harry Markowitz, mean–variance portfolio selection model has
been widely used in both theoretical and empirical studies, which maximizes the investment …

We propose a method to approximate the solution of online mixed-integer optimization (MIO)
problems at very high speed using machine learning. By exploiting the repetitive nature of …

This paper presents a multi-product, multi-period construction supply chain model,
accounting for supplier capacity and material demand uncertainties. Robust optimisation is …

This paper deals with a multi-period portfolio selection problem with fuzzy returns. A
possibilistic mean-semivariance-entropy model for multi-period portfolio selection is …