Emerging trends, driven by industry 4.0 and Big Data, are pushing to combine optimization techniques with Decision Support Systems (DSS). The use of DSS can reduce the risk of uncertainty of the decision-maker regarding the economic feasibility of a project and the technical design. Designing a DSS can be very hard, due to the inherent complexity of these types of systems. Therefore, monolithic software architectures are not a viable solution. This paper describes the DSS developed for an Italian company based on a micro-services architecture. In particular, the services handle geo-referenced information to solve a multi-trip vehicle routing problem with time windows. To face the problem, we follow a two-step approach. First, we generate a set of routes solving a vehicle routing problem with time windows using a metaheuristic algorithm. Second, we calculate the interval in which each route can start and end, and then combine the routes together, with an integer linear programming model, to minimize the number of used vehicles. Computational tests are conducted on real and random instances and prove the efficiency of the approach.
A Decision Support System for Multi-Trip Vehicle Routing Problems / Cavecchia, Mirko; ALVES DE QUEIROZ, Thiago; Iori, Manuel; Lancellotti, Riccardo; Zucchi, Giorgio. - 1:(2023), pp. 335-343. (Intervento presentato al convegno 25th International Conference on Enterprise Information Systems, ICEIS 2023 tenutosi a Prague, Czech Republic nel 24 - 26 April, 2023) [10.5220/0011806600003467].
A Decision Support System for Multi-Trip Vehicle Routing Problems
Mirko Cavecchia
;Thiago Alves de Queiroz;Manuel Iori;Riccardo Lancellotti;Giorgio Zucchi
2023
Abstract
Emerging trends, driven by industry 4.0 and Big Data, are pushing to combine optimization techniques with Decision Support Systems (DSS). The use of DSS can reduce the risk of uncertainty of the decision-maker regarding the economic feasibility of a project and the technical design. Designing a DSS can be very hard, due to the inherent complexity of these types of systems. Therefore, monolithic software architectures are not a viable solution. This paper describes the DSS developed for an Italian company based on a micro-services architecture. In particular, the services handle geo-referenced information to solve a multi-trip vehicle routing problem with time windows. To face the problem, we follow a two-step approach. First, we generate a set of routes solving a vehicle routing problem with time windows using a metaheuristic algorithm. Second, we calculate the interval in which each route can start and end, and then combine the routes together, with an integer linear programming model, to minimize the number of used vehicles. Computational tests are conducted on real and random instances and prove the efficiency of the approach.File | Dimensione | Formato | |
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