A parameterless performance metric for reference-point based multi-objective evolutionary algorithms

Most preference-based multi-objective evolutionary algorithms use reference points to articulate the decision maker's preferences. Since these algorithms typically converge to a sub-region of the Pareto-optimal front, the use of conventional performance measures (such as hypervolume and inverted generational distance) may lead to misleading results. Therefore, experimental studies in preference-based optimization often resort to using graphical methods to compare various algorithms. Though a few ad-hoc measures have been proposed in the literature, they either fail to generalize or involve parameters that are non-intuitive for a decision maker. In this paper, we propose a performance metric that is simple to implement, inexpensive to compute, and most importantly, does not involve any parameters. The so called expanding hypercube metric has been designed to extend the concepts of convergence and diversity to preference optimization. We demonstrate its effectiveness through constructed preference solution sets in two and three objectives. The proposed metric is then used to compare two popular reference-point based evolutionary algorithms on benchmark optimization problems up to 20 objectives

Models and Search Strategies for Applied Molecular Evolution

Introduction In just a few years, molecular diversity techniques have revolutionized pharmaceutical design and experimental methods for studying receptor binding, consensus sequences, genetic regu- latory mechanisms, and many other issues in biochemistry and chemistry [30, 69 71, 78, 79]. Because of the enormous libraries of ligands that can be used and the rapidity of the techniques, methods of applied molecular evolution such as SELEX and phage display have become particularly popular [30, 78, 86,126,127, 142,151]. These methods have been enormously successful, yet the theoretical work developed for them so far is quite limited. The success of these methods is not trivial: the huge number of sequences being searched through, the low concentrations of individual species, and the noise and biases inherent in the techniques would seem to make these experiments very difficult. Understanding why they work so well, and showing how they can perform better and for more complex molecular s

Genetics of Whole Plant Morphology and Architecture

Plant architectural features directly impact plant fitness and adaptation, and traits related to plant morphology and development represent important targets for crop breeding. Decades of mutagenesis research have provided a wealth of mutant resources, making barley (Hordeum vulgare L.) an interesting model for genetic dissection of grass morphology and architecture. Recent advances in genomics have propelled the identification of barley genes controlling different aspects of shoot and root development. In addition to gene discovery, it is important to understand the interplay between different developmental processes in order to support breeding of improved ideotypes for sustainable barley production under different climatic conditions. The purpose of the present chapter is to: (i) provide an overview of the morphology and development of shoot and root structures in barley; (ii) discuss novel insights into the genetic, molecular and hormonal mechanisms regulating root and shoot development and architecture; and (iii) highlight the genetic and physiological interactions among organs and traits with special focus on correlations between leaf and tiller development, flowering and tillering, as well as row-type and tillering