Variable Neighborhood Descent

Duarte, Abraham; Sánchez‐Oro, Jesús; Mladenović, Nenad; Todosijević, Raca

doi:10.1007/978-3-319-07124-4_9

Cited by 52 publications

(29 citation statements)

References 35 publications

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“…Two algorithms from the Variable Neighborhood Search (VNS) family were applied to the following cases: Variable Neighborhood Descent (VND) and basic VNS proposed by Hansen and Mladenovic in 2003 [23] and 2007 [24], respectively. The main idea of these methods is to change the neighborhoods and apply the local search procedure.…”

Section: Variable Neighborhood Search Algorithmsmentioning

confidence: 99%

Optimization of Water Quality Monitoring Networks Using Metaheuristic Approaches: Moscow Region Use Case

Yudina

Petrovskaia

Shadrin

et al. 2021

Water

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Currently many countries are struggling to rationalize water quality monitoring stations which is caused by economic demand. Though this process is essential indeed, the exact elements of the system to be optimized without a subsequent quality and accuracy loss still remain obscure. Therefore, accurate historical data on groundwater pollution is required to detect and monitor considerable environmental impacts. To collect such data appropriate sampling and assessment methodologies with an optimum spatial distribution augmented should be exploited. Thus, the configuration of water monitoring sampling points and the number of the points required are now considered as a fundamental optimization challenge. The paper offers and tests metaheuristic approaches for optimization of monitoring procedure and multi-factors assessment of water quality in “New Moscow” area. It is shown that the considered algorithms allow us to reduce the size of the training sample set, so that the number of points for monitoring water quality in the area can be halved. Moreover, reducing the dataset size improved the quality of prediction by 20%. The obtained results convincingly demonstrate that the proposed algorithms dramatically decrease the total cost of analysis without dampening the quality of monitoring and could be recommended for optimization purposes.

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Section: Variable Neighborhood Search Algorithmsmentioning

confidence: 99%

Optimization of Water Quality Monitoring Networks Using Metaheuristic Approaches: Moscow Region Use Case

Yudina

Petrovskaia

Shadrin

et al. 2021

Water

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“…The penalty term (2) captures idle times between the requests' deliveries and installations. The total distances of truck and technician tours are captured in terms (3) and (4). Terms (5) and (6) correspond to the number of truck tours and technician tours, respectively.…”

Section: Objective Functionmentioning

confidence: 99%

“…Local search methods perform especially well when multiple neighborhoods are combined. In a recent study Duarte et al [3] explore variable neighborhood descent (VND) methods in depth and survey various successful applications of these methods in the literature. On the other hand, methods applying larger neighborhoods exhibit good performance as well.…”

Section: Introductionmentioning

confidence: 99%

Adaptive large variable neighborhood search for a multiperiod vehicle and technician routing problem

Graf

2020

Networks

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The VeRoLog Solver Challenge 2018–2019 of the EURO working group vehicle routing and logistics (VeRoLog) considers a multiperiod vehicle and technician routing and scheduling problem. This paper proposes a combination of large neighborhood and local search heuristics and a decomposition approach to efficiently generate competitive solutions under restricted computational resources. The interplay of the heuristics, the decomposition, and the way the search space is explored are orchestrated by an adaptive layer that explicitly considers the instance to be solved, a time limit and the performance of the computing environment. In a computational study it is shown that the method is efficient and effective, especially under tight time restrictions.

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“…Regarding optimization, different neighborhoods of S will not, in general, share the same local minimum. Thus, local optima trap problems may be overcome by deterministically changing the neighborhoods [4,5]. • The candidate list size.…”

Section: Greedy Randomized Adaptive Search Procedures (Grasp)mentioning

confidence: 99%

A Survivable and Reliable Network Topological Design Model

Robledo¹,

Romero²,

Sartor³

et al. 2020

Reliability and Maintenance - An Overview of Cases

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This work is focused on the resolution of a mixed model for the design of largesized networks. An algorithm is introduced, whose initial outcomes are promising in terms of topological robustness regarding connectivity and reliability. The algorithm combines the network survivability and the network reliability approaches. The problem of the topological design has been modeled based on the generalized Steiner problem with node-connectivity constraints (GSPNC), which is NP-hard. The aim of this study is to heuristically solve the GSP-NC model by designing lowcost highly connected topologies and to measure the reliability of such solutions with respect to a certain prefixed lower threshold. This research introduces a greedy randomized algorithm for the construction of feasible solutions for the GSP-NC and a local search algorithm based on the variable neighborhood search (VNS) method, customized for the GSP-NC. In order to compute the built network reliabilities, this work adapts the recursive variance reduction (RVR) technique, as a simulation method since the exact evaluation of this measurement is also NP-hard. The experimental tests were performed over a wide set of testing cases, which contained heterogeneous topologies, including instances of more than 200 nodes. The computational results showed highly competitive execution times, achieving minimal local optimal solutions of good quality fulfilling the imposed survivability and reliability conditions.

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Variable Neighborhood Descent

Cited by 52 publications

References 35 publications

Optimization of Water Quality Monitoring Networks Using Metaheuristic Approaches: Moscow Region Use Case

Optimization of Water Quality Monitoring Networks Using Metaheuristic Approaches: Moscow Region Use Case

Adaptive large variable neighborhood search for a multiperiod vehicle and technician routing problem

A Survivable and Reliable Network Topological Design Model

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