A Decision Support System for Attended Home Services

• Published in: INFORMS journal on applied analytics 2020-03, Vol.50 (2), p.137-152
• Main Authors: Bruck, Bruno P., Castegini, Filippo, Cordeau, Jean-François, Iori, Manuel, Poncemi, Tommaso, Vezzali, Dario
• Format: Article
• Language: English
• Subjects: Algorithms; attended home services; Closures; Companies; Computer simulation; Customers; Data; decision support system; Decision support systems; Electric power distribution; Electricity; Household utilities; Mathematical models; Municipalities; Operations management; Performance indicators; routing; simulation; Technicians; time slot management; Time use
• ISSN: 0092-2102; 2644-0865; 1526-551X; 2644-0873
• DOI: 10.1287/inte.2020.1031

The authors describe a decision support system developed to solve a practical attended home services problem faced by Iren Group, an Italian multiutility company operating in the distribution of electricity, gas, and water. The company operates in several regions across Italy and aims to optimize the dispatching of technicians to customer locations where they perform installations, closures, or maintenance activities within time slots chosen by the customers. This paper describes a decision support system developed to solve a practical attended home services problem faced by Iren Group, an Italian multiutility company operating in the distribution of electricity, gas, and water. The company operates in several regions across Italy and aims to optimize the dispatching of technicians to customer locations where they perform installations, closures, or maintenance activities within time slots chosen by the customers. The system uses historical data and helps operations managers in performing a number of strategic decisions: grouping municipalities into clusters; designing sets of model-weeks for each cluster; evaluating the obtained solutions by means of a dynamic rolling horizon simulator; and providing as output several key performance indicators, as well as visual optimized technician routing plans to analyze different scenarios. The system uses mathematical models and heuristic algorithms that have been specifically developed to take into account different service levels. Computational experiments carried out on data provided by the company confirm the efficiency of the proposed methods. These methods also constitute a powerful tool that can be used by the company not only to reduce costs but also to help them in their strategic evaluation of existing and potential market opportunities.