Lecture Series on Environmental Systems Analysis

Multiple Criteria Optimization and Decision Making

Prof. Dr. Eckart Zitzler, Computer Engineering and Networks Laboratory, ETH Zürich
Biologically-inspired computation, a branch of computational intelligence, is an umbrella term for different computational approaches that are based on principles or models of biological systems. This class of methods complements traditional techniques in the sense that the former can be applied to large-scale applications where little is known about the underlying problem and where the latter approaches encounter difficulties. Moreover, biologically motivated methods are ideally suited to model-oriented problem solving where learning about the problem as well as the modelling process as such are at the center of attention. These techniques have become indispensable instruments for the study of complex systems - be it ecological, biological, or technical systems. A promising and rapidly expanding area of research is the employment of bio-inspired computation, in particular evolutionary algorithms, for multiobjective decision support which arise naturally in most
real-world applications.

Meanwhile, evolutionary multiobjective optimization has become established as a separate subdiscipline combining the fields of evolutionary computation and classical multiple criteria decision making - the latter field can be defined as the study of methods and procedures by which concerns about multiple conficting criteria can be formally incorporated into the management planning process. This cross-fertilization has initiated a paradigm shift from automated search to interactive, user-guided
problem solving principles combining optimization and decision analysis. This talk highlights recent advances in the field of evolutionary multiobjective optimization and demonstrates how the corresponding techniques are successfully employed for the quantitative study of ecological and biological systems - tightly linked to modelling and simulation. To this end, various case studies will be provided.