Titlebook: Variable Neighborhood Search; 8th International Co Nenad Mladenovic,Andrei Sleptchenko,Mohammed Omar Conference proceedings 2021 Springer N

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Simplicial Vertex Heuristic in Solving the Railway Arrival and Departure Paths Assignment Problem,nown heuristic that gives good quality solutions on sparse graphs. So, for solving the maximum independent set on sparse graphs, we propose an efficient heuristic based on the extended simplicial vertex test.

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0302-9743 n of Controlled Circular Data” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com..978-3-030-69624-5978-3-030-69625-2Series ISSN 0302-9743 Series E-ISSN 1611-3349

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Finding Critical Nodes in Networks Using Variable Neighborhood Search,stability, protein interaction, or social influence analysis, among others. These problems can be modeled with the Critical Node Detection Problem (CNDP). Given a network, the CNDP consists of identifying a set of . nodes whose removal minimizes the pairwise connectivity of the network. In this work

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A Variable Neighborhood Heuristic for Facility Locations in Fog Computing, and predictable latency in the response time has motivated the shift from a cloud to a fog computing approach. A fog computing architecture is likely to represent a preferable solution to reduce the application latency and the risk of network congestion by decreasing the volume of data transferred

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Scheduling in Parallel Machines with Two Servers: The Restrictive Case, loaded on a common loading server. After a machine completes processing one job, an unloading server is needed to remove the job from the machine. During the loading, respectively the unloading, operation, both the machine and the loading, respectively the unloading, server are occupied. The object

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Reduced Variable Neighbourhood Search for the Generation of Controlled Circular Data, does not apply or needs to be readjusted into the circle. This is typical, for example, in computational linguistics and natural language processing, where language models based on Bag-of-Words, Vector Space, or Word Embedding, are largely used for tasks like document classification, information re