Small-scale mining, poverty and economic development in sub-Saharan Africa: An overview

Artisanal and small-scale mining (ASM)-low tech, labour intensive mineral processing and excavation activity-is an economic mainstay in rural sub-Saharan Africa, providing direct employment to over two million people. This paper introduces a special issue on 'Small-scale mining, poverty and development in sub-Saharan Africa'. It focuses on the core conceptual issues covered in the literature, and the policy implications of the findings reported in the papers in this special issue. (C) 2009 Elsevier Ltd. All rights reserved.

Evaluating the role of environmental quality in the sustainable rural economic development of England

The issue of the sustainable development of rural economies in England has recently received considerable attention. This is because many of the poorest areas in the country are rural, often of high environmental quality, but suffering from high unemployment and a lack of services and facilities. The rapid decline in agricultural incomes and in-migration of affluent urban workers since 1990 has exacerbated economic inequality in such areas. A number of factors have the potential to drive rural development and this paper applies, and considers, the feasibility of a method from the USA for combining economic and environmental variables in a regional growth model to examine the hypothesis that environmental quality is an important determinant of sustainable rural development in England. The model output suggests that, although environmental quality does play a role in sustainable rural development in England there are other, more important, factors driving development. These include business and communications infra-structure, the degree and opportunities for commuting and underlying employment prospects. The robustness and limitations of the method for combining economic and environmental variables is discussed in relation to the spatial interrelatedness of Local Authority Districts in England, and conclusions are drawn about areas for refinement and improvement of the method.

A knowledge-based evolution strategy for the multi-objective minimum spanning tree problem

A fast Knowledge-based Evolution Strategy, KES, for the multi-objective minimum spanning tree, is presented. The proposed algorithm is validated, for the bi-objective case, with an exhaustive search for small problems (4-10 nodes), and compared with a deterministic algorithm, EPDA and NSGA-II for larger problems (up to 100 nodes) using benchmark hard instances. Experimental results show that KES finds the true Pareto fronts for small instances of the problem and calculates good approximation Pareto sets for larger instances tested. It is shown that the fronts calculated by YES are superior to NSGA-II fronts and almost as good as those established by EPDA. KES is designed to be scalable to multi-objective problems and fast due to its small complexity.