Extending and Solving the Refrigerated Routing Problem
In recent years, cold food chains have shown an impressive growth, mainly due to customers life style changes. Consequently, the transportation of refrigerated food is becoming a crucial aspect of the chain, aiming at ensuring efficiency and sustainability of the process while keeping a high level o...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-11-01
|
| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/13/23/6214 |
| _version_ | 1797546701389561856 |
|---|---|
| author | Sara Ceschia Luca Di Gaspero Antonella Meneghetti |
| author_facet | Sara Ceschia Luca Di Gaspero Antonella Meneghetti |
| author_sort | Sara Ceschia |
| collection | DOAJ |
| description | In recent years, cold food chains have shown an impressive growth, mainly due to customers life style changes. Consequently, the transportation of refrigerated food is becoming a crucial aspect of the chain, aiming at ensuring efficiency and sustainability of the process while keeping a high level of product quality. The recently defined Refrigerated Routing Problem (RRP) consists of finding the optimal delivery tour that minimises the fuel consumption for both the traction and the refrigeration components. The total fuel consumption is related, in a complex way, to the distance travelled, the vehicle load and speed, and the outdoor temperature. All these factors depend, in turn, on the traffic and the climate conditions of the region where deliveries take place and they change during the day and the year. The original RRP has been extended to take into account also the total driving cost and to add the possibility to slow down the deliveries by allowing arbitrarily long waiting times when this is beneficial for the objective function. The new RRP is formulated and solved as both a Mixed Integer Programming and a novel Constraint Programming model. Moreover, a Local Search metaheuristic technique (namely Late Acceptance Hill Climbing), based on a combination of different neighborhood structures, is also proposed. The results obtained by the different solution methods on a set of benchmarks scenarios are compared and discussed. |
| first_indexed | 2024-03-10T14:33:55Z |
| format | Article |
| id | doaj.art-5ad052cb080841c2b214ad649e084b35 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T14:33:55Z |
| publishDate | 2020-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-5ad052cb080841c2b214ad649e084b352023-11-20T22:22:11ZengMDPI AGEnergies1996-10732020-11-011323621410.3390/en13236214Extending and Solving the Refrigerated Routing ProblemSara Ceschia0Luca Di Gaspero1Antonella Meneghetti2DPIA—Polytechnic Department of Engineering and Architecture, University of Udine, Via delle Scienze 206, 33100 Udine, ItalyDPIA—Polytechnic Department of Engineering and Architecture, University of Udine, Via delle Scienze 206, 33100 Udine, ItalyDPIA—Polytechnic Department of Engineering and Architecture, University of Udine, Via delle Scienze 206, 33100 Udine, ItalyIn recent years, cold food chains have shown an impressive growth, mainly due to customers life style changes. Consequently, the transportation of refrigerated food is becoming a crucial aspect of the chain, aiming at ensuring efficiency and sustainability of the process while keeping a high level of product quality. The recently defined Refrigerated Routing Problem (RRP) consists of finding the optimal delivery tour that minimises the fuel consumption for both the traction and the refrigeration components. The total fuel consumption is related, in a complex way, to the distance travelled, the vehicle load and speed, and the outdoor temperature. All these factors depend, in turn, on the traffic and the climate conditions of the region where deliveries take place and they change during the day and the year. The original RRP has been extended to take into account also the total driving cost and to add the possibility to slow down the deliveries by allowing arbitrarily long waiting times when this is beneficial for the objective function. The new RRP is formulated and solved as both a Mixed Integer Programming and a novel Constraint Programming model. Moreover, a Local Search metaheuristic technique (namely Late Acceptance Hill Climbing), based on a combination of different neighborhood structures, is also proposed. The results obtained by the different solution methods on a set of benchmarks scenarios are compared and discussed.https://www.mdpi.com/1996-1073/13/23/6214energy efficiencysustainable transportscold food chainrich vehicle routing problemmixed integer programmingconstraint programming |
| spellingShingle | Sara Ceschia Luca Di Gaspero Antonella Meneghetti Extending and Solving the Refrigerated Routing Problem Energies energy efficiency sustainable transports cold food chain rich vehicle routing problem mixed integer programming constraint programming |
| title | Extending and Solving the Refrigerated Routing Problem |
| title_full | Extending and Solving the Refrigerated Routing Problem |
| title_fullStr | Extending and Solving the Refrigerated Routing Problem |
| title_full_unstemmed | Extending and Solving the Refrigerated Routing Problem |
| title_short | Extending and Solving the Refrigerated Routing Problem |
| title_sort | extending and solving the refrigerated routing problem |
| topic | energy efficiency sustainable transports cold food chain rich vehicle routing problem mixed integer programming constraint programming |
| url | https://www.mdpi.com/1996-1073/13/23/6214 |
| work_keys_str_mv | AT saraceschia extendingandsolvingtherefrigeratedroutingproblem AT lucadigaspero extendingandsolvingtherefrigeratedroutingproblem AT antonellameneghetti extendingandsolvingtherefrigeratedroutingproblem |