A reusable iterative optimization software library to solve combinatorial problems with approximate reasoning

Real world combinatorial optimization problems such as scheduling are typically too complex to solve with exact methods. Additionally, the problems often have to observe vaguely specified constraints of different importance, the available data may be uncertain, and compromises between antagonistic criteria may be necessary. We present a combination of approximate reasoning based constraints and iterative optimization based heuristics that help to model and solve such problems in a framework of C++ software libraries called StarFLIP++. While initially developed to schedule continuous caster units in steel plants, we present in this paper results from reusing the library components in a shift scheduling system for the workforce of an industrial production plant.Comment: 33 pages, 9 figures; for a project overview see http://www.dbai.tuwien.ac.at/proj/StarFLIP

Ranking Universities: Criteria and Consequences

This Supplement to 'Higher Education Digest' Number 59 brings together a number of items addressing the issue of university rankings. The first piece explores some of the background to the debate: the impact of rankings, the main criticisms and broader issues of policy and principle. It arose from an initial review of the literature for current research on university league tables and their impact on institutional behaviour undertaken by CHERI and Hobsons Research, commissioned by the Higher Education Funding Council for England (HEFCE). A brief description of the various strands of this research project follows. One of the weightier volumes on university ranking that has emerged recently is editors Sadlak and Lui’s 'The World-Class University and Ranking: Aiming Beyond', and a summary of this collection of papers is also featured in this supplement. Many of this book’s authors are members of the International Rankings Expert Group (IREG) and one of the Group’s key contributions has been to draw up a set of 'Principles on Ranking of Higher Education Institutions', with the explicit aim of evaluating and improving ranking practice. The Principles are included here as one succinct statement of good practice. But many critics question the very principle of creating hierarchies of institutions, and Ulrich Teichler provides a personal reflection on this subject to conclude this Supplement

Economics of soil and water conservation

The Ethiopian highlands, inhabited by the vast majority of the Ethiopian human and livestock populations, are under continuous threat from soil erosion. Land degradation induced by soil erosion is considered to be among the major factors responsible for the recurrent malnutrition and famine problems in Ethiopia. Conservation efforts during recent decades have succeeded neither in triggering voluntary adoption of conservation practices nor in mitigating soil erosion problems. The purpose of this thesis is, therefore, to understand the socio-economic aspects underlying soil and water conservation decisions in the context of subsistence farmers in the Eastern Highlands of Ethiopia. In articles I, III, and IV, the farmers’ decision problem is modeled as a utility maximization problem, and econometric models are used to link the statistical model of observed data and the economic model. Stochastic dominance criteria are used, in article I, to determine whether adoption of a conservation practice results in higher expected grain yield and income and/or reduced variability. Limited dependent variable econometric models are used in articles III and IV in order to determine factors that influence farmers’ decisions on soil and water conservation, and their preference for types of development intervention. In article II, the decision problem is modeled as an intertemporal net benefit maximization problem, and a dynamic programming optimization model is applied to determine the optimal path of investment in soil and water conservation. Findings in article I suggest that conservation results in higher expected grain yield and income, but does not support the hypothesis that conservation unambiguously results in less variability than no-conservation. In article II, it is shown that the optimal path of investment in soil and water conservation depends on the discount rate and grain prices. The results also suggest that erosive agricultural practices yield higher return in the short-term, whereas conservation yields a higher and sustainable return in the long-term. The need to design incentive mechanisms that encourage farmers to have a longer planning horizon are among important suggestions proposed in articles I and II. Results, in article III, suggest that specific physical conditions of plots and socioeconomic characteristics of farm households influence the soil and water conservation decision behavior of farmers. Article IV suggests that the perceived priority of farmers with regard to agricultural problems and socio-economic characteristics, determines their preference for the type of development intervention. The results also suggest that there exists a complementarity between different interventions and hence a need to address them simultaneously to ensure a higher return from interventions. An important lesson to be drawn from articles III and IV is that differences in farming conditions and complementarities between policy programs need to be noted in any intervention program

A new perspective on the competitiveness of nations

The capability of firms to survive and to have a competitive advantage in global markets depends on, amongst other things, the efficiency of public institutions, the excellence of educational, health and communications infrastructures, as well as on the political and economic stability of their home country. The measurement of competitiveness and strategy development is thus an important issue for policy-makers. Despite many attempts to provide objectivity in the development of measures of national competitiveness, there are inherently subjective judgments that involve, for example, how data sets are aggregated and importance weights are applied. Generally, either equal weighting is assumed in calculating a final index, or subjective weights are specified. The same problem also occurs in the subjective assignment of countries to different clusters. Developed as such, the value of these type indices may be questioned by users. The aim of this paper is to explore methodological transparency as a viable solution to problems created by existing aggregated indices. For this purpose, a methodology composed of three steps is proposed. To start, a hierarchical clustering analysis is used to assign countries to appropriate clusters. In current methods, country clustering is generally based on GDP. However, we suggest that GDP alone is insufficient for purposes of country clustering. In the proposed methodology, 178 criteria are used for this purpose. Next, relationships between the criteria and classification of the countries are determined using artificial neural networks (ANNs). ANN provides an objective method for determining the attribute/criteria weights, which are, for the most part, subjectively specified in existing methods. Finally, in our third step, the countries of interest are ranked based on weights generated in the previous step. Beyond the ranking of countries, the proposed methodology can also be used to identify those attributes that a given country should focus on in order to improve its position relative to other countries, i.e., to transition from its current cluster to the next higher one