Authors: Carmine Cerrone; Benjamin Dussault; Bruce Golden; Edward Wasil
Addresses: Department of Computer Science, University of Salerno, Via Giovanni Paolo II, 84084 Fisciano (SA), Italy ' Price for Profit, 2487 E 126 St., Cleveland, OH 44120, USA ' Robert H. Smith School of Business, University of Maryland, 4339 Van Munching Hall, College Park, MD 20742-1815, USA ' Kogod School of Business, American University, 4400 Massachusetts Avenue, NW, Washington, DC 20016, USA
Abstract: In the street-sweeper problem, we seek to sweep the sides of city streets in a way that minimises the distance travelled by the street sweepers. Typically, street sweepers are blocked by parked cars that prevent the curb from being swept. We consider a problem posed to us by Washington, DC where the parking constraints are multi-period decision variables. For example, suppose the city wishes to sweep its streets over two days with available parking on at least one side of each street on each day. Before the city considers how to sweep its streets, it must first decide which street sides to make available for parking on each day in a way that obeys the parking constraint on both days. We present a genetic algorithm that generates high-quality solutions and discuss managerial implications.
Keywords: arc routing; vehicle routing; street sweeping; genetic algorithms; street sweepers; parking constraints; scheduling.
International Journal of Metaheuristics, 2014 Vol.3 No.1, pp.21 - 58
Available online: 25 Jan 2014 *Full-text access for editors Access for subscribers Purchase this article Comment on this article