Randomized heuristics for handover minimization in mobility networks

Morán-Mirabal, L. F.; González‐Velarde, José Luis; Resende, Maurício G. C.; Silva, R. M.

doi:10.1007/s10732-013-9223-0

Cited by 28 publications

(19 citation statements)

References 20 publications

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“… PrevGRASP2: Morán-Mirabal et al (2013) also applied GRASP with path-relinking and included the variant known as evolutionary path-relinking.  PrevGRASP3: Martínez-Gavara et al (2015) proposed a simplified GRASP that provides highquality solutions in short computing times.…”

Section: Previous Grasp Methodsmentioning

confidence: 99%

“…Once the randomized greedy construction method produces an assignment vector, a local search algorithm attempts to improve the assignment by making changes on it. Specifically, Morán-Mirabal et al (2013) proposed three local search algorithms, move-1, move-max, and swap-2. The three algorithms scan the base stations in increasing order of their total traffic (capacity of the nodes).…”

Section: Previous Grasp Methodsmentioning

confidence: 99%

“…In particular, in the design of the zones to help rationalize the bulk movement of mail, see Deng and Bard (2011). Morán-Mirabal et al (2013) tackled a very interesting real-world problem, which as shown in Martínez-Gavara et al (2015) turns out to be an application of the CCP. Hence, we use this real-world application in the context of mobility networks for the investigation presented here.…”

Section: The Capacitated Clustering Problemmentioning

confidence: 99%

“…Note that the PrevGRASP2 method (Morán-Mirabal et al 2013) was designed for the handover minimization in mobility networks, and therefore it can only be applied to the MM instances since it does not target general CCP instances. We therefore split Table 4 into two sections.…”

Section: Computational Experimentsmentioning

confidence: 99%

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Randomized heuristics for the Capacitated Clustering Problem

Martı́nez-Gavara

Landa-Silva

Campos

et al. 2017

Information Sciences

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In this paper, we investigate the adaptation of the Greedy Randomized Adaptive Search Procedure (GRASP) and Iterated Greedy methodologies to the Capacitated Clustering Problem (CCP). In particular, we focus on the effect of the balance between randomization and greediness on the performance of these multi-start heuristic search methods when solving this NP-hard problem. The former is a memory-less approach that constructs independent solutions, while the latter is a memorybased method that constructs linked solutions, obtained by partially rebuilding previous ones. Both are based on the combination of greediness and randomization in the constructive process, and coupled with a subsequent local search phase. We propose these two multi-start methods and their hybridization and compare their performance on the CCP. Additionally, we propose a heuristic based on the mathematical programming formulation of this problem, which constitutes a so-called matheuristic. We also implement a classical randomized method based on simulated annealing to complete the picture of randomized heuristics. Our extensive experimentation reveals that Iterated Greedy performs better than GRASP in this problem, and improved outcomes are obtained when both methods are hybridized and coupled with the matheuristic. In fact, the hybridization is able to outperform the best approaches previously published for the CCP. This study shows that memorybased construction is an effective mechanism within multi-start heuristic search techniques.

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Section: Previous Grasp Methodsmentioning

confidence: 99%

Section: Previous Grasp Methodsmentioning

confidence: 99%

Section: The Capacitated Clustering Problemmentioning

confidence: 99%

Section: Computational Experimentsmentioning

confidence: 99%

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Randomized heuristics for the Capacitated Clustering Problem

Martı́nez-Gavara

Landa-Silva

Campos

et al. 2017

Information Sciences

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“…Decidimos definir um cromossoma formado por n genes, em que cada gene define a prioridade do vértice para ser seleccionado para ser visitado. Esta estrutura foi adaptada do modelo de Chaves Aleatórias (Random Keys) apresentado por Morán-Mirabal et al (2014). …”

Section: O Cromossomaunclassified

Sistema de Apoio à Decisão para o Transporte Não Urgente de Doentes em Veículo Partilhado

Oliveira

Ferreira

Figueiredo

et al. 2014

RISTI

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Resumo: O transporte não urgente de doentes em Portugal foi alvo de reformulação legislativa de modo a reduzir os custos que acarretava. Neste artigo apresentam-se métodos heurísticos para a formação de agrupamentos de doentes a serem transportados na mesma viatura. São apresentados resultados computacionais que validam os algoritmos desenvolvidos. Os algoritmos podem ser facilmente integrados num sistema de apoio à decisão.Palavras-chave: Algoritmo Genético; Problema de Roteamento de Veículos; Transporte a Pedido; Problemas da Orientação de Equipas; Transporte Não Urgente de Doentes. Decision Support System for Not Urgent Transportation of Patients in Shared VehicleAbstract: The non-emergency patient transport service in Portugal was targeted by legislative reforms aiming to reduce costs. This paper presents heuristic methods for grouping patients to be transported in the same vehicle. The computational results are presented and validate the developed algorithms. These algorithms can be easily integrated into a decision support system.

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Path-relinking

Resende

Ribeiro

2016

Optimization by GRASP

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Randomized heuristics for handover minimization in mobility networks

Cited by 28 publications

References 20 publications

Randomized heuristics for the Capacitated Clustering Problem

Randomized heuristics for the Capacitated Clustering Problem

Sistema de Apoio à Decisão para o Transporte Não Urgente de Doentes em Veículo Partilhado

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