A column generation based heuristic for the generalized vehicle routing problem with time windows

Yuan, Yuan; Cattaruzza, Diego; Ogier, Maxime; Semet, Frédéric; Vigo, Daniele

doi:10.1016/j.tre.2021.102391

Cited by 34 publications

(16 citation statements)

References 39 publications

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“…In the subproblem, columns are generated by the iterative local search algorithm, and the tabu list is used to avoid loop. Aiming at the vehicle routing and scheduling problem with semi-soft time windows (VRPSSTW), a basic shortest path problem with resource constraints and delay penalty conditions was proposed [15]. The modified forward insertion heuristic algorithm was used to solve the subproblem, which provided better columns for the main problem, so as to accelerate the convergence speed of the algorithm.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The customer node is based on real-world longitude and latitude coordinates. According to the different needs of distribution customers, we abstract three different sizes of distribution customer sets: small (5,10,15), medium (20,25,30,35), and large (40,45,50). Table 3 shows the characteristics of the case.…”

Section: Case Analysis Of Enterprise Logistics Schedulingmentioning

confidence: 99%

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Solving open vehicle problem with time window by hybrid column generation algorithm

Qian

et al. 2022

J. of Syst. Eng. Electron.

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This paper addresses the open vehicle routing problem with time window (OVRPTW), where each vehicle does not need to return to the depot after completing the delivery task. The optimization objective is to minimize the total distance. This problem exists widely in real-life logistics distribution process. We propose a hybrid column generation algorithm (HCGA) for the OVRPTW, embedding both exact algorithm and metaheuristic. In HCGA, a label setting algorithm and an intelligent algorithm are designed to select columns from small and large subproblems, respectively. Moreover, a branch strategy is devised to generate the final feasible solution for the OVRPTW. The computational results show that the proposed algorithm has faster speed and can obtain the approximate optimal solution of the problem with 100 customers in a reasonable time.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Case Analysis Of Enterprise Logistics Schedulingmentioning

confidence: 99%

Solving open vehicle problem with time window by hybrid column generation algorithm

Qian

et al. 2022

J. of Syst. Eng. Electron.

View full text Add to dashboard Cite

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“…In this process, a Local Search (LS) procedure described in Algorithm 3 is repeatedly performed until no better solution is found. It is worth mentioning that, only in (Yuan et al 2021), LS operators are used in the CG-based algorithm to deal with the VRPRDL. In HGA-SC, we use more complex LS operators as well as special data structures to speed up the move evaluation, which are not proposed in (Yuan et al 2021).…”

Section: Local Search For Educationmentioning

confidence: 99%

“…In (Yuan et al 2021), the authors implement Swap and Relocation moves which exchange the position of only two customers and relocate a single customer to other positions, respectively. Their LS operators are also not performed in the intra-route fashion.…”

Section: σ(I-1) σ(I+2) σ'(J-1) σ'(J) σ'(J+2) σ(I) σ'(J+1)mentioning

confidence: 99%

“…It is worth mentioning that, to solve the VRPRDL instances, LNS* requires to have the fleet size obtained from previous results in (Tilk, Olkis, and Irnich 2021) to limit the number of vehicles. Finally, (Yuan et al 2021) introduce a Column Generation Based Heuristic (CGBH) to deal with the GVRPTW. The method combines several components including a construction heuristic, a route optimization procedure, local search operators, and the generation of negative reduced cost routes.…”

Section: Introductionmentioning

confidence: 99%

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A Hybrid Genetic Algorithm for the Vehicle Routing Problem with Roaming Delivery Locations

Pham

Hà

et al. 2022

ICAPS

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The Vehicle Routing Problem with Roaming Delivery Locations (VRPRDL) is a variant of the Vehicle Routing Problem (VRP) in which a customer can be present at many locations during a working day and a time window is associated with each location. The objective is to find a set of routes such that (i) the total traveling cost is minimized, (ii) only one location of each customer is visited within its time window, and (iii) all capacity constraints are satisfied. To solve the problem, we introduce a hybrid genetic algorithm which relies on problem-tailored solution representation, mutation, local search operators, as well as a set covering component exploring routes found during the search to find better solutions. We also propose a new split procedure which based on dynamic programming to evaluate the fitness of chromosomes. Experiments conducted on the benchmark instances clearly show that our proposed algorithm outperforms existing approaches in terms of stability and solution quality. We also improve 49 best known solutions of the literature.

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A Memetic Approach for Routing Problem with Capacity and Time Constraints

Boudali

Ragmoun²

2022

Advances in Computational Collective Intelligence

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A column generation based heuristic for the generalized vehicle routing problem with time windows

Cited by 34 publications

References 39 publications

Solving open vehicle problem with time window by hybrid column generation algorithm

Solving open vehicle problem with time window by hybrid column generation algorithm

A Hybrid Genetic Algorithm for the Vehicle Routing Problem with Roaming Delivery Locations

A Memetic Approach for Routing Problem with Capacity and Time Constraints

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