<?xml version="1.0" encoding="utf-8" standalone="yes"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/">
  <channel>
    <title>Variable Neighborhood Search on Nikolaos Antoniadis</title>
    <link>https://nikosantoniadis.eu/tags/variable-neighborhood-search/</link>
    <description>Recent content in Variable Neighborhood Search on Nikolaos Antoniadis</description>
    <generator>Hugo -- 0.160.1</generator>
    <language>en</language>
    <lastBuildDate>Mon, 27 Sep 2021 00:00:00 +0000</lastBuildDate>
    <atom:link href="https://nikosantoniadis.eu/tags/variable-neighborhood-search/index.xml" rel="self" type="application/rss+xml" />
    <item>
      <title>A variable neighborhood search simheuristic algorithm for reliability optimization of smart grids under uncertainty</title>
      <link>https://nikosantoniadis.eu/papers/paper3/</link>
      <pubDate>Mon, 27 Sep 2021 00:00:00 +0000</pubDate>
      <guid>https://nikosantoniadis.eu/papers/paper3/</guid>
      <description>This paper presents a simheuristic algorithm that combines Variable Neighborhood Search with Monte Carlo simulation to optimize smart grid topology reconfiguration, ensuring network reliability and stability for 24 hours following an overloading incident. Published in the International Transactions in Operational Research, 2022.</description>
    </item>
    <item>
      <title>Enhancing Smart Grid Resilience and Reliability by Using and Combining Simulation and Optimization Methods</title>
      <link>https://nikosantoniadis.eu/papers/thesis2/</link>
      <pubDate>Thu, 27 May 2021 00:00:00 +0000</pubDate>
      <guid>https://nikosantoniadis.eu/papers/thesis2/</guid>
      <description>This dissertation presents a comprehensive study on optimizing the reliability and resilience of smart grids by developing mathematical and simulation-based methods that provide optimal countermeasures to prevent overloading disturbances.</description>
    </item>
    <item>
      <title>A hybrid CPU-GPU parallelization scheme of variable neighborhood search for inventory optimization problems</title>
      <link>https://nikosantoniadis.eu/papers/paper1/</link>
      <pubDate>Mon, 17 Apr 2017 00:00:00 +0000</pubDate>
      <guid>https://nikosantoniadis.eu/papers/paper1/</guid>
      <description>This paper introduces and evaluates a hybrid CPU-GPU parallelization scheme using OpenMP and OpenACC to accelerate the Variable Neighborhood Search (VNS) metaheuristic for solving complex inventory optimization problems in reverse logistics. Published in the Electronic Notes in Discrete Mathematics, 2017.</description>
    </item>
  </channel>
</rss>
