A branch-and-price method for the vehicle allocation problem

Cruz, Cesar Alvarez; Munari, Pedro; Morábito, Reinaldo

doi:10.1016/j.cie.2020.106745

Cited by 10 publications

(3 citation statements)

References 21 publications

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“…The ability to utilize the vehicles as either partially loaded trucks (less-than-truckload, LTL) or fully loaded trucks (full-truckload, FTL) is another reason for the decision makers to prefer road freight transportation in logistics operations. In LTL transportation, a single delivery does not occupy the full capacity of a truck; therefore, a truck can carry the loads collected from multiple locations at the same time, such as in-vehicle routing problems, which increases vehicle utilization (Cruz et al, 2020). This aggregation allows to consolidate smaller loads and utilize larger energy-efficient trucks, potentially resulting in faster and cheaper transportation.…”

Section: The Vehicle Allocation Problemmentioning

confidence: 99%

A review on sustainability, Industry 4.0 and collaboration implications in vehicle allocation operations

Çimen,

Benli,

İbiş Bozyel

et al. 2023

IJLM

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PurposeVehicle allocation problems (VAPs), which are frequently confronted in many transportation activities, primarily including but not limited to full truckload freight transportation operations, induce a significant economic impact. Despite the increasing academic attention to the field, literature still fails to match the needs of and opportunities in the growing industrial practices. In particular, the literature can grow upon the ideas on sustainability, Industry 4.0 and collaboration, which shape future practices not only in logistics but also in many other industries. This review has the potential to enhance and accelerate the development of relevant literature that matches the challenges confronted in industrial problems. Furthermore, this review can help to explore the existing methods, algorithms and techniques employed to address this problem, reveal directions and generate inspiration for potential improvements.Design/methodology/approachThis study provides a literature review on VAPs, focusing on quantitative models that incorporate any of the following emerging logistics trends: sustainability, Industry 4.0 and logistics collaboration.FindingsIn the literature, sustainability interactions have been limited to environmental externalities (mostly reducing operational-level emissions) and economic considerations; however, emissions generated throughout the supply chain, other environmental externalities such as waste and product deterioration, or the level of stakeholder engagement, etc., are to be monitored in order to achieve overall climate-neutral services to the society. Moreover, even though there are many types of collaboration (such as co-opetition and vertical collaboration) and Industry 4.0 opportunities (such as sharing information and comanaging distribution operations) that could improve vehicle allocation operations, these topics have not yet received sufficient attention from researchers.Originality/valueThe scientific contribution of this study is twofold: (1) This study analyses decision models of each reviewed article in terms of decision variable, constraint and assumption sets, objectives, modeling and solving approaches, the contribution of the article and the way that any of sustainability, Industry 4.0 and collaboration aspects are incorporated into the model. (2) The authors provide a discussion on the gaps in the related literature, particularly focusing on practical opportunities and serving climate-neutrality targets, carried out under four main streams: logistics collaboration possibilities, supply chain risks, smart solutions and various other potential practices. As a result, the review provides several gaps in the literature and/or potential research ideas that can improve the literature and may provide positive industrial impacts, particularly on how logistics collaboration may be further engaged, which supply chain risks are to be incorporated into decision models, and how smart solutions can be employed to cope with uncertainty and improve the effectiveness and efficiency of operations.

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Section: The Vehicle Allocation Problemmentioning

confidence: 99%

A review on sustainability, Industry 4.0 and collaboration implications in vehicle allocation operations

Çimen,

Benli,

İbiş Bozyel

et al. 2023

IJLM

View full text Add to dashboard Cite

show abstract

“…Ref. [35] utilizes Dantzig-Wolfe decomposition as well as a branch-and-price procedure to solve an MILP model for the vehicle allocation problem.…”

Section: Dantzig-wolfe Decompositionmentioning

confidence: 99%

Optimal Planning of Electric Vehicle Fast-Charging Stations Considering Uncertain Charging Demands via Dantzig–Wolfe Decomposition

Wang

Zhou

2023

Sustainability

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This study investigates the planning problem of fast-charging stations for electric vehicles with the consideration of uncertain charging demands. This research aims to determine where to build fast-charging stations and how many charging piles to be installed in each fast-charging station. Based on the multicommodity flow model, a chance-constrained programming model is established to address this planning problem. A scenario-based approach as well as a big-M coefficients generation algorithm are applied to reformulate the programming model into tractable one, then the Dantzig–Wolfe decomposition method is leveraged to find its optimal solution. Finally, a numerical experiment is conducted in a 25-node network to assess the efficiency of the proposed model and solution approach.

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“…To optimally solve the routing and scheduling problem, we develop a branchand-price (BAP) algorithm, which is the leading exact algorithm for the routing and scheduling problems [29,30,31,32]. The BAP algorithm is composed by embedding the column generation procedure into the branch-and-bound framework.…”

Section: The Framework Of Bap Algorithmmentioning

confidence: 99%

A branch-and-price algorithm for a routing and scheduling problem from economic and environmental perspectives

2022

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This paper addresses a routing and scheduling problem from two different perspectives: economic and environmental. From economic perspective, we aim to optimize the vehicle routing plan to reduce the operating cost, but from environmental perspective, we aim to optimize the vehicle routing and speed decisions to reduce the car- bon emissions. This research can provide two different decision plans under these two different perspectives, and the comparison of the re- sults from the two different perspectives will be very meaningful and helpful to the logistics decision-makers. We formulate the problem using two mixed-integer programming (MIP) models with different ob- jectives. However, this problem is very challenging, with medium-sized instances already difficult for the MIP solver. In order to solve it with larger scale instances, we propose an exact branch-and-price (BAP) al- gorithm. The BAP algorithm relies on efficiently solving the pricing sub-problem with different objectives. We design two different tailored labeling algorithms to solve it. Extensive computational experiments demonstrate the effectiveness of the proposed BAP algorithm, compar- ing with the MIP formulation solved by CPLEX with a time limit of 2 hour.

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A branch-and-price method for the vehicle allocation problem

Cited by 10 publications

References 21 publications

A review on sustainability, Industry 4.0 and collaboration implications in vehicle allocation operations

A review on sustainability, Industry 4.0 and collaboration implications in vehicle allocation operations

Optimal Planning of Electric Vehicle Fast-Charging Stations Considering Uncertain Charging Demands via Dantzig–Wolfe Decomposition

A branch-and-price algorithm for a routing and scheduling problem from economic and environmental perspectives

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