Discusses the interaction between socio-economic systems and their natural environment, by examining the indicators of sustainable development. Areas covered by the operationalization of sustainable development indicators; Details on the global nature of environmental problems; Important strategy of the operationalization of sustainable development; Link between economic data and ecological ind...

This paper proposes and evaluates an evolutionary multiobjective optimization algorithm (EMOA) that uses a new quality indicator, called the prospect indicator, for parent selection and environmental selection operators. The prospect indicator measures the potential of each individual to reproduce offspring that dominate itself and spread out in the objective space. The prospect indicator allow...

Several indicator-based evolutionary multiobjective optimization algorithms have been proposed in the literature. The notion of optimal μ-distributions formalizes the optimization goal of such algorithms: find a set of μ solutions that maximizes the underlying indicator among all sets with μ solutions. In particular for the often used hypervolume indicator, optimal μ-distributions have been the...

the objective of this study is to measure the city of tehran’s environmental quality in 2006 (the last census year). primarily, with a comparative analysis of a variety of urban sustainability indicator models, a collection of 54 indicators have been chosen and categorized as indicators of increase or decrease in urban environmental quality in the form of a simple mathematical model. based o...

In recent years, indicator-based evolutionary algorithms, allowing to implicitly incorporate user preferences into the search, have become widely used in practice to solve multiobjective optimization problems. When using this type of methods, the optimization goal changes from optimizing a set of objective functions simultaneously to the singleobjective optimization goal of finding a set of μ p...

In the last two decades, multiobjective optimization has become mainstream because of its wide applicability in a variety of areas such engineering, management, the military and other fields. Multi-Objective Evolutionary Algorithms (MOEAs) play a dominant role in solving problems with multiple conflicting objective functions. They aim at finding a set of representative Pareto optimal solutions ...