Buil, RomanDe Armas, JésicaRiera, DanielOrozco, Sandra2023-06-202023-06-202021Buil R, de Armas J, Riera D, Orozco S. Optimization of the real-time response to roadside incidents through heuristic and linear programming. Mathematics. 2021;9(16):1982. DOI: 10.3390/math91619822227-7390http://hdl.handle.net/10230/57266This paper presents a solution for a real-world roadside assistance problem. Roadside incidents can happen at any time. Depending on the type of incident, a specific resource from the roadside assistance company can be sent on site. The problem of allocating resources to these road-side incidents can be stated as a multi-objective function and a large set of constraints, including priorities and preferences, resource capacities and skills, calendars, and extra hours. The request from the client is to a have real-time response and to attempt to use only open source tools. The optimization objectives to consider are the minimization of the operational costs and the minimization of the time to arrive to each incident. In this work, an innovative approach to near-optimally solving this problem in real-time is proposed, combining a heuristic approach and linear programming. The results show the great potential of this approach: operational costs were reduced by 19%, the use of external providers was reduced to half, and the productivity of the resources owned by the client was significantly increased.application/pdfeng© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).info:eu-repo/semantics/articlehttp://dx.doi.org/10.3390/math9161982roadside assistanceresources scheduling optimizationreal-time allocationmultiobjective functioninfo:eu-repo/semantics/openAccess