Abstract
The urban projects planning is known as a very complex task. It consists of finding out adequate solutions to fit common problems such as inner city decay, overcrowding, and traffic congestion, in order to manage the city in a rational way with sustainable alternatives. The aim is to meet human urban needs, and to reach a high level of efficiency, with the best employment of available resources. Therefore, a set of projects that maximize utility functions is chosen. The evaluation of these functions is built on urban projects criteria with respect to political, financial, ecological and other socioeconomic constraints. This paper aims to present how to deal with urban projects planning, using multi-objective ant colony optimization (MACO) algorithm to fit urban projects to appropriate areas, respecting related constraints.
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