In almost no other field of computer science, the idea of using bio-inspired search paradigms
has been so useful as in solving multiobjective optimization problems. The idea of using a …

Molecular discovery is a multi-objective optimization problem that requires identifying a
molecule or set of molecules that balance multiple, often competing, properties. Multi …

In polypharmacology drugs are required to bind to multiple specific targets, for example to
enhance efficacy or to reduce resistance formation. Although deep learning has achieved a …

Drug discovery is a challenging multi-objective problem where numerous pharmaceutically
important objectives need to be adequately satisfied for a solution to be found. The problem …

Many interesting search problems can be formulated as bi-objective search problems, that
is, search problems where two kinds of costs have to be minimized, for example, travel …

Drug discovery is an expensive and risky process. To combat the challenges in drug
discovery, an increasing number of researchers and pharmaceutical companies recognize …

Drug discovery is time-and resource-consuming. To this end, computational approaches that
are applied in de novo drug design play an important role to improve the efficiency and …

Introduction: A high-quality drug must achieve a balance of physicochemical and absorption,
distribution, metabolism and elimination properties, safety and potency against its …

Virtual high throughput screening, typically driven by first-principles, density functional
theory calculations, has emerged as a powerful tool for the discovery of new materials …

We describe the development and application of an integrated, multiobjective optimization
workflow (MOARF) for directed medicinal chemistry design. This workflow couples a rule …