Adaptive memory programming for the many-to-many vehicle routing problem with cross-docking

Nikolopoulou, Amalia; Repoussis, Panagiotis P.; Tarantilis, Christos D.; Zachariadis, Emmanouil E.

doi:10.1007/s12351-016-0278-1

Cited by 15 publications

(3 citation statements)

References 32 publications

(54 reference statements)

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“…This constructive algorithm is different from previously proposed algorithms and better solutions could be found for most of the instances given by Wen et al ( 2009) and Tarantilis (2013). Nikolopoulou et al (2016) introduced further generalized VRPCD by extending one-to-one correspondence between suppliers and customers, which was similar to the study by Wen et al (2009), to many-to-many correspondence between them. In addition, two distinct fleets of vehicles in both processes were also considered in its model.…”

Section: Review Of Literaturementioning

confidence: 99%

An Optimization Model for the Hard Time Windows Vehicle Routing Problem with Moving Shipments at the Cross Dock Center

Gnanapragasam,

Daundasekera

2023

OUSL Jnl

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Cross-Docking (CD) technique was initiated in the 1930s to make a cost-effective supply chain. Vehicle Routing Problem (VRP) is one of the widely discussed optimization problems. The research on integration of VRP with CD (VRPCD) was initiated at the beginning of 2000s. Moving Shipments (MS) from receiving doors to shipping doors is an activity inside a Cross-Dock Centre (CDC). This study mainly considers MS as an additional aspect in the literature of VRPCD. In this study, not only loading or unloading shipments at all the nodes including CDC and homogenous fleets of vehicles within pickup or delivery process are considered, but also aspects of heterogeneous fleets of vehicles between pickup and delivery processes are considered. Furthermore, Time Windows (TW) characteristics are also considered here. A mixed integer nonlinear programming model is developed to obtain the optimal solutions to hard time windows vehicle routing problem with moving shipments at the cross-dock centre (TW-VRPCD-MS). The compatibility of the proposed model is tested using sixteen randomly generated small scale instances. Since the average computational time is reasonably less for the tested instances, it can be concluded that this proposed model can be used for last time planning for similar small-scale problems. Further analysis revealed that the convergence rate to reach the optimal solution rises exponentially with the scale of the problem. Therefore, this study recommends in applying heuristic or metaheuristic techniques to solve large scale instances of TW-VRPCD-MS to obtain a near optimal solution in a reasonable computational time.

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Section: Review Of Literaturementioning

confidence: 99%

An Optimization Model for the Hard Time Windows Vehicle Routing Problem with Moving Shipments at the Cross Dock Center

Gnanapragasam,

Daundasekera

2023

OUSL Jnl

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“…This is the most studied variant, and it is the one we will refer to as the vehicle routing with cross-docking (VRPCD). Several heuristics have been proposed to solve it: based on tabu-search (Wen et al, 2008;Tarantilis, 2012;Nikolopoulou et al, 2017Nikolopoulou et al, , 2016, iterated local search (Morais et al, 2014) and LNS (Grangier et al, 2017). Many variants have been studied, with optional cross-dock returns (Petersen and Ropke, 2011;Santos et al, 2013;Nikolopoulou et al, 2017), taking into account the cost of handling (Santos et al, 2011a,b;Enderer et al, 2017), with multiple cross-docks (Ahmadizar et al, 2015;Maknoon and Laporte, 2017;Kroep et al, 2017), with partly subcontracted or left to suppliers routes (Yu et al, 2016;Enderer et al, 2017).…”

Section: The Vehicle Routing Problem With Cross-dockingmentioning

confidence: 99%

The vehicle routing problem with cross-docking and resource constraints

Grangier¹,

Gendreau

Lehuédé

et al. 2019

J Heuristics

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In this paper, we propose an extension of the vehicle routing problem with cross-docking that takes into account resource constraints at the cross-dock. These constraints limit the number of docks that can be used simultaneously. To solve this new problem, we adapt a recently proposed matheuristic based on large neighborhood search. In particular, we focus on the feasibility tests for insertions and compare heuristics and constraint programming strategies. Finally, computational experiments on instances adapted from the vehicle routing problem with cross-docking are reported. They give insights on the impact of a limited cross-dock capacity on the routing cost.

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“…As one of the hardest problems in operations research, VRP has received considerable attention. For the latest research on VRP, please see the literature [5][6][7][8][9][10][11][12][13][14][15][16][17][18]. For the latest development review, please see the literature [19][20][21].…”

Section: Introductionmentioning

confidence: 99%

A Dynamic Strategy for Home Pick-Up Service with Uncertain Customer Requests and Its Implementation

Zeng

Huang

2019

Sustainability

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In this paper, a home service problem is studied, where a capacitated vehicle collects customers’ parcels in one pick-up tour. We consider a situation where customers, who have scheduled their services in advance, may call to cancel their appointments, and customers, who do not have appointments, also need to be visited if they request for services as long as the capacity is allowed. To handle those changes that occurred over the tour, a dynamic strategy will be needed to guide the vehicle to visit customers in an efficient way. Aimed at minimizing the vehicle’s total expected travel distance, we model this problem as a multi-dimensional Markov Decision Process (MDP) with finite exponential scale state space. We exactly solve this MDP via dynamic programming, where the computing complexity is exponential. In order to avoid complexity continually increasing, we aim to develop a fast looking-up method for one already-examined state’s record. Although generally this will result in a huge waste of memory, by exploiting critical structural properties of the state space, we obtain an O ( 1 ) looking-up method without any waste of memory. Computational experiments demonstrate the effectiveness of our model and the developed solution method. For larger instances, two well-performed heuristics are proposed.

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Adaptive memory programming for the many-to-many vehicle routing problem with cross-docking

Cited by 15 publications

References 32 publications

An Optimization Model for the Hard Time Windows Vehicle Routing Problem with Moving Shipments at the Cross Dock Center

An Optimization Model for the Hard Time Windows Vehicle Routing Problem with Moving Shipments at the Cross Dock Center

The vehicle routing problem with cross-docking and resource constraints

A Dynamic Strategy for Home Pick-Up Service with Uncertain Customer Requests and Its Implementation

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