Recent Developments in Modeling and Solving the Split Delivery Vehicle Routing Problem

Gulczynski, Damon; Golden, Bruce L.; Wasil, Edward

doi:10.1287/educ.1080.0046

Cited by 9 publications

(6 citation statements)

References 27 publications

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“…Customer demands can be satisfied by several vehicles, each moving a partial load. This variant is called VRP with split deliveries (SDVRP), as reviewed in Chen et al (2007), Gulczynski et al (2008) and Archetti and Speranza (2011). Instances with up to 50 customers (Belenguer et al 2000, Lee et al 2006) can be exactly solved.…”

Section: Heuristics For Vrp Variants With Assign Attributesmentioning

confidence: 99%

Heuristics for multi-attribute vehicle routing problems: A survey and synthesis

Vidal

Crainic

Gendreau

et al. 2013

European Journal of Operational Research

357

194

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Section: Heuristics For Vrp Variants With Assign Attributesmentioning

confidence: 99%

Heuristics for multi-attribute vehicle routing problems: A survey and synthesis

Vidal

Crainic

Gendreau

et al. 2013

European Journal of Operational Research

357

194

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“…Dergis, Li & Vogel [9] added a local search-based heuristic to SDVRP. Studies conducted by Archetti, Savelsbergh, and Spranza [10] as well as those by Gulczynski, Golden, and Wasil [11] are good sources for understanding the recent advances in SDVRP modeling and solutions [12].…”

Section: Research Literaturementioning

confidence: 99%

Cement Transportation Limited-Fleet Modeling and Assigning to Rated Demands

2017

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Summary.Transportation is an inseparable part of the supply chain, with a key role in product distribution. This role is highlighted when ratio of "the cost of transportation" to "the value of goods" such as cement is significant. Iran has recently become one of the main centers of cement production in the world. However, transportation is the most important challenge in cement distribution because of weak structure of the transportation fleet and its independent action. Independence of and lack of commitment on the part of transportation fleets to cement companies as well as lack of timely delivery due to shortage of transportation in some routes and seasons lead to customers` dissatisfaction and even market loss or lack of market development. One of the significant differences between the transportation system in Iran and that in developed countries is lack of complete productivity of the transportation fleet. It means that trucks are driver-based in Iran. This paper introduces a model considering some issues such as driver-based trucks, size of the transportation fleet based on the number of active trucks, and demand priorities in the cement company. Taking the relation between the number of active trucks and the cement company into account, this model assigns weekly demands to the transportation fleet. It also tries to minimize the delay to respond to demands and increases the efficiency of the transportation fleet. Finally, this current condition-based model is compared with two other models including "no constraints on different routes of trucks" as well as single-route model for trucks.

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“…Several more advanced pairing strategies were proposed by Lei et al (2012); Erera et al (2009). A better collaborative representative, however, is that of Split Deliveries Trudeau, 1989, 1990;Mullaseril et al, 1997) (for reviews, see: (Gulczynski et al, 2008;Archetti and Speranza, 2012)). In this case, individual tasks may be served by more than a single vehicle, allowing distance-cost savings of up to 50% on static instances (in extreme cases), provided the Triangle Inequality holds.…”

Section: Collaborative Routingmentioning

confidence: 99%

Genetic Programming Hyper-Heuristics with Vehicle Collaboration for Uncertain Capacitated Arc Routing Problems

MacLachlan

Mei

Branke

et al. 2020

Evolutionary Computation

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Due to its direct relevance to post-disaster operations, meter reading and civil refuse collection, the Uncertain Capacitated Arc Routing Problem (UCARP) is an important optimisation problem. Stochastic models are critical to study as they more accurately represent the real-world than their deterministic counterparts. Although there have been extensive studies in solving routing problems under uncertainty, very few have considered UCARP, and none consider collaboration between vehicles to handle the negative effects of uncertainty. This paper proposes a novel Solution Construction Procedure (SCP) that generates solutions to UCARP within a collaborative, multivehicle framework. It consists of two types of collaborative activities: one when a vehicle unexpectedly expends capacity (route failure), and the other during the refill process. Then, we propose a Genetic Programming Hyper-Heuristic (GPHH) algorithm to evolve the routing policy used within the collaborative framework. The experimental studies show that the new heuristic with vehicle collaboration and GP-evolved routing policy significantly outperforms the compared state-of-the-art algorithms on commonly studied test problems. This is shown to be especially true on instances with larger numbers of tasks and vehicles. This clearly shows the advantage of vehicle collaboration in handling the uncertain environment, and the effectiveness of the newly proposed algorithm.

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Recent Developments in Modeling and Solving the Split Delivery Vehicle Routing Problem

Cited by 9 publications

References 27 publications

Heuristics for multi-attribute vehicle routing problems: A survey and synthesis

Heuristics for multi-attribute vehicle routing problems: A survey and synthesis

Cement Transportation Limited-Fleet Modeling and Assigning to Rated Demands

Genetic Programming Hyper-Heuristics with Vehicle Collaboration for Uncertain Capacitated Arc Routing Problems

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