@proceedings {Longo2015535,
	title = {Optimizing routine maintenance team routes},
	journal = {Proceedings of the 17th International Conference on Enterprise Information Systems, Proceedings (ICEIS)},
	volume = {1},
	year = {2015},
	note = {cited By 0; Conference of 17th International Conference on Enterprise Information Systems, ICEIS 2015 ; Conference Date: 27 April 2015 Through 30 April 2015; Conference Code:112657},
	pages = {535-546},
	publisher = {SciTePress},
	address = {Barcelona, Spain, 27-30 April 2015},
	abstract = {<p>Simulated annealing is a metaheuristic approach for the solution of optimization problems inspired to the controlled cooling of a material from a high temperature to a state in which internal defects of the crystals are minimized. In this paper, we apply a simulated annealing approach to the scheduling of geographically distributed routine maintenance interventions. Each intervention has to be assigned to a maintenance team and the choice among the available teams and the order in which interventions are performed by each team are based on team skills, cost of overtime work, and cost of transportation. We compare our solution algorithm versus an exhaustive approach considering a real industrial use case and show several numerical results to analyze the effect of the parameters of the simulated annealing on the accuracy of the solution and on the execution time of the algorithm.</p>
},
	keywords = {Controlled cooling, Cost of transportation, Industrial use case, Information systems, Maintenance, Meta-heuristic approach, Optimization, Optimization problems, Routine maintenance, Scheduling, Scheduling problem, Simulated annealing, Solution algorithms},
	isbn = {9789897580970},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84939555682\&partnerID=40\&md5=4b6abf15640b1475952a6bfa5de0117c},
	author = {Longo, F. and Andrea R. Lotronto and Marco Scarpa and Antonio Puliafito}
}
