An evolutionary-based decision support system for vehicle routing: The case of a public utility

摘要

Customer-related processes in a public utility, such as meter replacement programs, demand a large number of auditing visits to customer sites. The proposed decision support system (DSS) helps the operating manager to plan these visits by integrating commercial systems such as SAP/R3 and ArcGIS with a custom-made distance-constrained routing module. This module includes a modified Clarke and Wright savings heuristic and two memetic algorithms, along with two integer-programming clustering models whose function is to balance the workload. The system was tested on ten real-world distance-constrained vehicle routing instances ranging from 323 to 601 nodes.