The single vehicle routing problem with deliveries and selective pickups

Gribkovskaia, Irina; Laporte, Gilbert; Shyshou, Aliaksandr

doi:10.1016/j.cor.2007.01.007

Cited by 94 publications

(40 citation statements)

References 22 publications

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“…OVRP deals with the situations where the vehicles are not required to return to the depot after the last delivery or route completion. Gribkovskaia et al (2008) have address the issue related to a single vehicle routing problem with mandatory deliveries and very particular and selective pickups, in which it is required to cover all deliveries, but pickups kept optional depending upon the revenue generated with each pickup. Nevertheless, it's compulsory to pickups and transported it to the desired depot.…”

Section: Synchronizing Production and Distribution Of Heterogeneous Nmentioning

confidence: 99%

Optimizing the Newspaper Distribution Scenarios using Genetic Algorithm: A Case Study of India

Kamble¹,

Raut²,

Gawankar³

2017

American Journal of Applied Sciences

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This paper attempts to optimize the various newspaper distribution scenario as observed in India. It found from the literature that earlier research work carried out in optimizing the vehicle routing networks problem using time window and scope was limited to distribution from newspaper printing location to the vendor point of distribution. This paper focuses on the distribution of newspaper from vendor to the newspaper reader/customer. In this study case study method is used and the circulation activity is modelled with different field scenarios with a aim of minimizing the overall (total) delivery time of the Newspaper. The major aim of this paper was to identify the issues, while distributing the newspaper by the vendor at the hub to the end reader. The company under consideration had an objective of finishing the last newspaper delivery by 6:30 am. To optimize the same the paper identified the following scenario: Case 1. Delivery to Independent Houses Located in a Community Case 2. Delivery to an Apartment Cluster Case 3. Delivery considering the various modes of transportation The present paper optimized the same using genetic algorithm as the optimizing tool. The model with different scenarios presented in the paper will help the newspaper distribution planners to understand the various issues on the field and achieve to have a successful distribution strategy within the set objective of reaching the last copy of newspaper by 6:30 am to the reader. This will help not only the newspaper company under consideration but the entire newspaper industry. This paper contributes to body of knowledge of newspaper industry its major research implications are 1. It provide insights for a particular type of functioning environment, where speed and time play an critical role. 2. In certain type the time delays in the distribution network will impact the consumer's preference which will lead to improved market share and more satisfied customers.

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Section: Synchronizing Production and Distribution Of Heterogeneous Nmentioning

confidence: 99%

Optimizing the Newspaper Distribution Scenarios using Genetic Algorithm: A Case Study of India

Kamble¹,

Raut²,

Gawankar³

2017

American Journal of Applied Sciences

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“…Also the selective PDP (SPDP) by Ting and Liao (2013. ) and the single vehicle routing problem with deliveries and selective pickups (SVRPPD) by Gribkovskaia et al (2008) refer to this problem class. The authors find a route for a vehicle to visit some pickup nodes and supply the demand of all delivery nodes.…”

Section: Literature Reviewmentioning

confidence: 99%

The multi-vehicle profitable pickup and delivery problem

2016

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The transportation industry expanded rapidly in a highly competitive environment. Logistics companies with insufficient volume of transport capacities are forced to make a selection of customers that they can integrate efficiently into their tours. This is of particular relevance in the pickup and delivery market, where shipments from several different customers can be moved on the same vehicle. In the literature, however, the problem of customer selection has not been applied for the given class of pickup and delivery problems so far. We want to fill this gap by introducing the multi-vehicle profitable pickup and delivery problem (MVPPDP), where multiple carriers transport goods from a selection of pickup customers to the corresponding delivery customers within given travel time limits. For this problem, we propose a method based on general variable neighborhood search (GVNS). We conduct experiments with two different variants of this method, namely a sequential (GVNSseq) and a self-adaptive (GVNSsa) version. Additionally, we compare it to an algorithm based on Guided Local Search (GLS), which is known to find good solutions for related problems very fast. The performance of these methods is examined on the basis of data instances with up to 1000 customer requests. In an experimental study, we observe that both variants of GVNS with 11 neighborhoods outperform GLS with regard to solution quality for all sizes of test instances. However, for medium sized and large instances, GLS shows an advantage in average runtimes.

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“…The results show that the best solutions are often non-Hamiltonian; such solutions for most instances contain just one customer who is served twice, in a figure-of-eight shape. Gribkovskaia, Laporte, and Shyshou (2008) tackled the TSPSDP with selective pickups. In this model all deliveries must be served, but pickups are optional.…”

Section: Literature Reviewmentioning

confidence: 99%

The Vehicle Routing Problem with Divisible Deliveries and Pickups

Nagy

Wassan

Speranza

et al. 2015

Transportation Science

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T he vehicle routing problem with divisible deliveries and pickups is a new and interesting model within reverse logistics. Each customer may have a pickup and delivery demand that have to be served with capacitated vehicles. The pickup and the delivery quantities may be served, if beneficial, in two separate visits. The model is placed in the context of other delivery and pickup problems and formulated as a mixed-integer linear programming problem. In this paper, we study the savings that can be achieved by allowing the pickup and delivery quantities to be served separately with respect to the case where the quantities have to be served simultaneously. Both exact and heuristic results are analysed in depth for a better understanding of the problem structure and an average estimation of the savings due to the possibility of serving pickup and delivery quantities separately.

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The single vehicle routing problem with deliveries and selective pickups

Cited by 94 publications

References 22 publications

Optimizing the Newspaper Distribution Scenarios using Genetic Algorithm: A Case Study of India

Optimizing the Newspaper Distribution Scenarios using Genetic Algorithm: A Case Study of India

The multi-vehicle profitable pickup and delivery problem

The Vehicle Routing Problem with Divisible Deliveries and Pickups

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