Optimizing a bi‐objective vehicle routing problem that appears in industrial enterprises. Issue 1 (15th September 2020)

• Record Type: Journal Article
• Authors: López‐Sánchez, Ana D.; Molina, Julián; Laguna, Manuel; Hernández‐Díaz, Alfredo G.
• Other Names: Gupta Deepak guestEditor.; Rodrigues Joel J. P. C. guestEditor.; Castillo Oscar guestEditor.; Herrero Álvaro guestEditor.; Jiménez Alfredo guestEditor.; Bayraktar Secil guestEditor.; Arroyo Angel guestEditor.
• Is Part Of: Expert systems. Volume 38:Issue 1(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-09-15
• Subjects: frequency -- local search -- multi‐start algorithm -- periodic vehicle routing problem -- proximate optimality principle -- service choice; Expert systems (Computer science); 006.33
• DOI: 10.1111/exsy.12638
• Languages: English
• ISSNs: 0266-4720

Abstract

Abstract: In this paper, a new solution method is implemented to solve a bi‐objective variant of the vehicle routing problem that appears in industry and environmental enterprises. The solution involves designing a set of routes for each day in a period, in which the service frequency is a decision variable. The proposed algorithm, a muti‐start multi‐objective local search algorithm (MSMLS), minimizes total emissions produced by all vehicles and maximizes the service quality measured as the number of times that a customer is visited by a vehicle in order to be served. The MSMLS is a neighbourhood‐based metaheuristic that obtains high‐quality solutions and that is capable of achieving better performance than other competitive algorithms. Furthermore, the proposed algorithm is able to perform rapid movements thanks to the easy representation of the solutions.