Urban traffic-related problems are a major point of concern in the majority of cities in the world. These problems arise in many different aspects, such as providing fast congestion-free routes in a city (improving the mobility of its inhabitants), or solving problems caused by the continuous presence of vehicles on the road (reducing thus the levels of noise and CO2 emission). Many of these problems can be mathematically expressed as optimization, classification or regression models, and involve, in most of the cases, huge search-spaces or hard constraints. In this paper we discuss one of these problems, the so called Reconfiguration One-Way Traffic Optimization Problem (ROWTOP). The problem consists in optimizing the directions of one-way streets in a city, in those cases in which this reconfiguration is needed because of the appearance of a major problem that involves prolonged street cuts. The problem is defined as a multi-objective optimization case and is solved by using a Soft-Computing (SC) approach based on an evolutionary algorithm (the NSGA-II technique). Its performance is discussed in a real problem in a Spanish city, achieving excellent results and showing the feasibility of these techniques as an innovative technology-based approaches, able to upgrade cities without incurring in exorbitant expenditures, helping politicians in making decisions and, ultimately, making cities more sustainable and better places to live. (C) 2013 Elsevier Inc. All rights reserved.
