Exact algorithms for the double vehicle routing problem with multiple stacks

Iori, Manuel; Riera-Ledesma, Jorge

doi:10.1016/j.cor.2015.04.016

Cited by 35 publications

(37 citation statements)

References 31 publications

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“…As introduced in Iori and Riera‐Ledesma (), the DVRPMS can be formally described as follows. Let

I = {1, 2, \dots, n}

be the set of customer requests carried by the vehicles in the pickup and delivery regions.…”

Section: Problem Definitionmentioning

confidence: 99%

“…Iori and Riera‐Ledesma () proposed the DVRPMS, a generalization of the DTSPMS. The DVRPMS has the same characteristics and constraints as the DTSPMS, except that now there is a fleet of vehicles available to meet the demand of the customers.…”

Section: Introductionmentioning

confidence: 99%

“…Besides proposing the DVRPMS, Iori and Riera‐Ledesma () presented three exact algorithms: branch‐and‐cut, branch‐and‐price, and branch‐and‐cut‐and‐price. As stated by the authors, the three exact algorithms had different behavior and efficiency with respect to different instances, created to evaluate the quality of their algorithms.…”

Section: Introductionmentioning

confidence: 99%

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A variable neighborhood search heuristic algorithm for the double vehicle routing problem with multiple stacks

Chagas

Silveira

Santos

et al. 2019

Int Trans Operational Res

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This paper addresses the double vehicle routing problem with multiple stacks (DVRPMS) in which a fleet of vehicles must collect items in a pickup region and then travel to a delivery region where all items are delivered. The load compartment of all vehicles is divided into rows (horizontal stacks) of fixed profundity (horizontal heights), and on each row, the unloading process must respect the last‐in‐first‐out policy. The objective of the DVRPMS is to find optimal routes visiting all pickup and delivery points while ensuring the feasibility of the vehicle loading plans. We propose a new integer linear programming formulation, which was useful to find inconsistencies in the results of exact algorithms proposed in the literature, and a variable neighborhood search based algorithm that was able to find solutions with same or higher quality in shorter computational time for most instances when compared to the methods already present in the literature.

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“…As introduced in Iori and Riera‐Ledesma (), the DVRPMS can be formally described as follows. Let

I = {1, 2, \dots, n}

be the set of customer requests carried by the vehicles in the pickup and delivery regions.…”

Section: Problem Definitionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A variable neighborhood search heuristic algorithm for the double vehicle routing problem with multiple stacks

Chagas

Silveira

Santos

et al. 2019

Int Trans Operational Res

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“…Karimanzira et al(2014) presented a behaviour based controller coupled with waypoint tracking scheme for an AUV guidance in large scale underwater environment. Iori and Ledesma (2015) modelled AUVs routing problem with a Double Traveling Salesman Problem with Multiple Stacks (DTSPMS) for a single-vehicle pickup-and-delivery problem by minimizing the total routing cost. Other methods also studied on efficient task assignment for single/multiple vehicle moving toward the destination such as graph matching (Kwok et al 2002), Tabu search (Higgins 2005), partitioning (Liu and Shell 2012), simulated annealing (Chiang and Russell 1996), branch and cut (Lysgaard et al 2004), and evolutionary algorithms (Gehring and Homberger 2001).…”

Section: Vehicle Task Assignment-routingmentioning

confidence: 99%

“…Moreover, the task and route planning problem is a generalization of both the knapsack and TSP problems and meta-heuristics are the fastest approach introduced for solving NP-hard complexity of these problems and have been shown to produce solutions close to the optimum with high probability (Iori and Ledesma, 2015;Besada-Portas, et al, 2010). On the other hand, precise and concurrent synchronization of the higher and lower level modules is the primary requirement for preserving the consistency, stability and cohesion of this real-time system in meeting the specified objectives.…”

Section: Research Contributionmentioning

confidence: 99%

A novel versatile architecture for autonomous underwater vehicle’s motion planning and task assignment

Zadeh¹,

Powers²,

Sammut³

et al. 2016

Soft Comput

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Expansion of today's underwater scenarios and missions necessitates the requestion for robust decision making of the Autonomous Underwater Vehicle (AUV); hence, design an efficient decision making framework is essential for maximizing the mission productivity in a restricted time. This paper focuses on developing a deliberative conflict-free-task assignment architecture encompassing a Global Route Planner (GRP) and a Local Path Planner (LPP) to provide consistent motion planning encountering both environmental dynamic changes and a priori knowledge of the terrain, so that the AUV is reactively guided to the target of interest in the context of an uncertain underwater environment. The architecture involves three main modules: The GRP module at the top level deals with the task priority assignment, mission time management, and determination of a feasible route between start and destination point in a large scale environment. The LPP module at the lower level deals with safety considerations and generates collision-free optimal trajectory between each specific pair of waypoints listed in obtained global route. Re-planning module tends to promote robustness and reactive ability of the AUV with respect to the environmental changes. The experimental results for different simulated missions, demonstrate the inherent robustness and drastic efficiency of the proposed scheme in enhancement of the vehicles autonomy in terms of mission productivity, mission time management, and vehicle safety.

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A Late Acceptance Hill-Climbing Heuristic Algorithm for the Double Vehicle Routing Problem with Multiple Stacks and Heterogeneous Demand

Souza

Chagas

Penna

et al. 2019

Advances in Intelligent Systems and Computing

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Exact algorithms for the double vehicle routing problem with multiple stacks

Cited by 35 publications

References 31 publications

A variable neighborhood search heuristic algorithm for the double vehicle routing problem with multiple stacks

A variable neighborhood search heuristic algorithm for the double vehicle routing problem with multiple stacks

A novel versatile architecture for autonomous underwater vehicle’s motion planning and task assignment

A Late Acceptance Hill-Climbing Heuristic Algorithm for the Double Vehicle Routing Problem with Multiple Stacks and Heterogeneous Demand

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