A guide to vehicle routing heuristics

Cordeau, Jean‐François; Gendreau, Michel; Laporte, Gilbert; Potvin, Jean-Yves; Semet, Frédéric

doi:10.1057/palgrave.jors.2601319

Cited by 470 publications

(212 citation statements)

References 55 publications

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“…Compared with classical heuristics, meta-heuristics carry out a more thorough search of the solution space, allowing inferior and sometimes infeasible moves, in addition to re-combining solutions to create new ones. As a result, meta-heuristics is capable of consistently producing high quality solutions, in spite of its greater computation time than early heuristics [94,95].…”

Section: Discussionmentioning

confidence: 99%

Waste Collection Vehicle Routing Problem: Literature Review

Han¹,

Cueto²

2015

PROMET

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Section: Discussionmentioning

confidence: 99%

Waste Collection Vehicle Routing Problem: Literature Review

Han¹,

Cueto²

2015

PROMET

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“…Savelsbergh (1985) has shown that finding a feasible solution to the Traveling Salesman Problem with time windows (TSPTW) is an NPcomplete problem (see also Braekers et al (2014) for full truckload applications). Although, optimal solutions to the VRPTW can be obtained using exact methods, the computational time required to solve a V R PT W optimally is prohibitive for large problems (Cordeau et al, 2002). As a result, heuristic methods are often used to obtain optimal or near optimal solution in a reasonable amount of time.…”

Section: Literature Reviewmentioning

confidence: 99%

A Solution for the Bi-Objective Vehicle Routing Problem With Time Windows Using Local Search and Genetic Algorithms

Mungwattana¹,

Manisri²,

Charoenpol³

et al. 2016

IJTTE

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This paper deals with the vehicle routing problem with time windows (VRPTW). The VRPTW routes a set of vehicles to service customers having two-sided time windows, i.e. earliest and latest start of service times. The demand requests are served by capacitated vehicles with limited travel times to return to the depot. The purpose of this paper is to develop a hybrid algorithm that uses the modified push forward insertion heuristic (MPFIH), a λ-interchange local search descent method (λ-LSD) and a genetic algorithm to solve the VRPTW with two objectives. The first objective aims to determine the minimum number of vehicles required and the second is to find the solution that minimizes the total travel time. A set of well-known benchmark problems are used to compare the quality of solutions. The results show that the proposed algorithm provides effective solutions compared with best found solutions and better than another heuristic used for comparison.

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“…Most metaheuristics consists of some construction and improvement heuristics (i.e. local search) [6]. Various metaheuristics for vehicle routing problem can be found in Bräysy and Gendreau survey [7].…”

Section: Fig 1 Capacitated Vehicle Routing Problemmentioning

confidence: 99%

Vehicle Routing Optimization Using Multiple Local Search Improvements

2014

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Original scientific paperCombinatorial optimization problems on graphs arise in many practical applications. One of the most studied practical combinatorial optimization problem is the Vehicle Routing Problem (VRP). When coupled with modern in-car navigation and fleet management software, real world applications of VRP optimization result in significant cost savings. In this paper novel multiple improvements pivoting rule for Capacitated VRP (CVRP) is proposed. Its application significantly reduces computational time needed for CVRP optimization. A novel pivoting rule is implemented as part of the search step selection mechanism in the Iterated Local Search algorithm. Augmented iterated local search algorithm is tested on 4 large scale real-world problems in Croatia with up to 7, 065 customers and 236 vehicles, and on standard CVRP benchmark sets. Real-world problem data was obtained from a large Croatian logistics company. Comparison of well known first and best pivoting rules with proposed novel multiple improvements pivoting rule regarding travel distance, number of search moves and computational time is given. Achieved computational speed-ups are up to 29 times compared to the first improvement pivoting rule and 9 times compared to the best improvement pivoting rule, without any substantial degradation in quality of the obtained solution. Key words: VRP, CVRP, iterated local search, multiple improvementsOptimizacija usmjeravanja vozila primjenom višestrukih poboljšanja u lokalnom pretraživanju. Kombinatoričke optimizacije na grafu pojavljuju se u mnogim aplikacijama u praksi. Jedan od najviše proučavanih kombinatoričkih optimizacijskih problema je problem usmjeravanja vozila. Ukoliko se optimizacija usmjeravanja vozila poveže sa suvremenim u vozila ugra enim sustavima navigacije i nadgledanja voznog parka moguće je postići značajne uštede u troškovima dostave. U ovom radu je predložen novi mehanizam odabira smjera lokalnog pretraživanja zasnovan na višestrukim poboljšanjima za rješavanje kapacitivnog problema usmjeravanja vozila. Predloženi novi mehanizam je implementiran kao dio mehanizma odabira smjera lokalnog pretraživanja u algoritmu iterativnog lokalnog pretraživanja. Prošireni algoritam iterativnog lokalnog pretraživanja je provjeren na 4 vrlo velika optimizacijska problema sa stvarnim podacima iz Hrvatske (skup od 7.065 kupaca i 236 dostavnih vozila) i na standardnim testnim skupovima. Stvarni testni podaci dobiveni su od jedne velike hrvatske logističke tvrtke. U radu je napravljena usporedba izme u mehanizama odabira smjera lokalnog pretraživanja zasnovanih na prvom i najboljem poboljšanju te predloženog mehanizma poboljšanja lokalne pretrage. Usporedba je napravljena prema prije enom putu, broju pomaka lokalnog pretraživanja i vremenu izračuna. Dobiveni rezultati pokazuju ubrzanje u vremenu izračuna za 29 puta u usporedbi sa prvim smjerom poboljšanja lokalne pretrage te 9 puta u usporedbi sa najboljim smjerom poboljšanja lokalne pretrage bez značajnijih degradacija u kvaliteti dobivenog rješenja.

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A guide to vehicle routing heuristics

Cited by 470 publications

References 55 publications

Waste Collection Vehicle Routing Problem: Literature Review

Waste Collection Vehicle Routing Problem: Literature Review

A Solution for the Bi-Objective Vehicle Routing Problem With Time Windows Using Local Search and Genetic Algorithms

Vehicle Routing Optimization Using Multiple Local Search Improvements

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