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.

Optimizing routine maintenance team routes

LONGO, FRANCESCO;Lotronto, Andrea Rocco;SCARPA, Marco Lucio;PULIAFITO, Antonio
2015-01-01

Abstract

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.
2015
9789897580970
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11570/3063910
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