Solving Dynamic Vehicle Routing Problem with Pickup and Delivery by CLARITY Method

Yavary, Arefeh; Sajedi, Hedieh

doi:10.1109/ines.2018.8523908

Cited by 3 publications

(1 citation statement)

References 19 publications

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“…In addition to some of the studies mentioned above, RDF subgraph queries are also a class of graph search that can be applied to many scenarios through different forms of optimization. For example, solving dynamic vehicle path problems [6] and also rumor detection in different social network analyses [7]. Moreover, when the method can be applied to network searches, it can help to find the nodes that cause Doppler shifts [8].…”

Section: Related Workmentioning

confidence: 99%

RDF Subgraph Query Based on Common Subgraph in Distributed Environment

Huang

Lai

et al. 2023

Wireless Communications and Mobile Computing

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With the gradual development of the network, RDF graphs have become more and more complex as the scale of data increases; how to perform more effective query for massive RDF graphs is a hot topic of continuous research. The traditional methods of graph query and graph traversal produce great redundancy of intermediate results, and processing subgraph collection queries in stand-alone mode cannot perform efficient matching when the amount of data is extremely large. Moreover, when processing subgraph collection queries, it is necessary to iterate the query graph multiple times in the query of the common subgraph, and the execution efficiency is not high. In response to the above problems, a distributed query strategy of RDF subgraph set based on composite relation tree is proposed. Firstly, a corresponding composite relationship is established for RDF subgraph set, then the composite relation graph is clipped, and the redundant nodes and edges of the composite relation graph are deleted to obtain the composite relation tree. Finally, using the composite relation tree, a MapReduce-based RDF subgraph set query method is proposed, which can use parallel in the computing environment, the distributed query batch processing is performed on the RDF subgraph set, and the query result of the RDF subgraph set is obtained by traversing the composite relation tree. The experimental results show that the algorithm proposed in this paper can improve the query efficiency of RDF subgraph set.

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Section: Related Workmentioning

confidence: 99%

RDF Subgraph Query Based on Common Subgraph in Distributed Environment

Huang

Lai

et al. 2023

Wireless Communications and Mobile Computing

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An improved hybrid ICA-SA metaheuristic for order acceptance and scheduling with time windows and sequence-dependent setup times

Mahmoudinazlou,

Alizadeh,

Noble

et al. 2023

Neural Comput & Applic

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A Monte Carlo simulation approach to the gap-time relationship in solving scheduling problem

Toragay

Pouya

2023

Journal of Turkish Operations Management

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This article presents a study on the job shop problem, a combinatorial optimization problem that models scheduling and resource allocation in industrial settings. The article aims to investigate the relationship between optimality gap and required computational resources, considering various optimality gap levels that are applicable in real-life situations. The study uses a Monte Carlo simulation to analyze the behavior of solvers in solving different sizes of random-generated scheduling problems. The findings of the study offer insights into the worthiness of reaching an optimal solution versus implementing a near-optimal solution and starting the work. The codes used in the study are accessible on the author's GitHub account.

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Solving Dynamic Vehicle Routing Problem with Pickup and Delivery by CLARITY Method

Cited by 3 publications

References 19 publications

RDF Subgraph Query Based on Common Subgraph in Distributed Environment

RDF Subgraph Query Based on Common Subgraph in Distributed Environment

An improved hybrid ICA-SA metaheuristic for order acceptance and scheduling with time windows and sequence-dependent setup times

A Monte Carlo simulation approach to the gap-time relationship in solving scheduling problem

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