2012
DOI: 10.1016/j.swevo.2011.10.002
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The urban bus routing problem in the Tunisian case by the hybrid artificial ant colony algorithm

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Cited by 54 publications
(24 citation statements)
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“…La investigación considerada en Thangiah et al, (2008) es una flota mixta, con múltiples paraderos, y entregas parciales. Euchi and Mraihi (2012) resuelven el SBRP en áreas urbanas, como un caso de estudio en la ciudad de Tunez. Los autores utilizan un algoritmo basado en colonia de hormigas para hacer frente a este problema.…”
Section: Revisión De La Literaturaunclassified
See 1 more Smart Citation
“…La investigación considerada en Thangiah et al, (2008) es una flota mixta, con múltiples paraderos, y entregas parciales. Euchi and Mraihi (2012) resuelven el SBRP en áreas urbanas, como un caso de estudio en la ciudad de Tunez. Los autores utilizan un algoritmo basado en colonia de hormigas para hacer frente a este problema.…”
Section: Revisión De La Literaturaunclassified
“…Contrario a la investigación actual donde diversas técnicas tales como búsqueda tabu (Pacheco et al, 2013), búsqueda adaptativa ávida aleatorizada (Schittekat et al, 2013), algoritmo de ramificación y acotamiento (Riera-Ledesma and SalazarGonzález, 2012), algoritmo genético (Díaz-Parra et al, 2013) y algoritmo basado en colonia de hormigas (Euchi and Mraihi, 2012) han sido propuestos para resolver el problema examinado, este articulo contribuye al estado del arte en lo siguiente: a) introducir la GMD, detallada en la investigación de Fligner and Verducci (1986), al SBRPBSS como una manera de estimar una distribución de probabilidad explicita sobre el dominio de las permutaciones. b) aplicar la GMD copulado con un EDA, llamado GMDEDA, para resolver el SBRPBSS.…”
Section: Introductionunclassified
“…SBTA and RS are implemented when buses transport students from more than one school. Minimisation of school bus routing problems is performed based on the nature of the underlying problem characteristics as follows; the number of schools: single (vehicle serves only one school) [35] or multiple (vehicle serves more than one school) [37]; fleet type: homogeneous (vehicles seating capacity remains the same) [23] or heterogeneous (vehicles seating capacity varies) [37]; service type: rural [31] or urban [30]; [17]. Table I also represents a comparison of methods applied by various researchers since 2010 for reducing school bus routing problems.…”
Section: Route Scheduling (Rs)mentioning
confidence: 99%
“…Thus, determining the set of visited bus stops is a part of the problem. The following methods of resolving the SBRPBSS are proposed: a genetic algorithm (Díaz-Parra et al, 2012;Kang et al, 2015), a column-generation-based algorithm (Kinable et al, 2014;Riera-Ledesma and Salazar-González, 2013), a GRASP + VND (variable neighborhood descent) matheuristic (Schittekat et al, 2013), an artificial ant colony with a variable neighborhood local search algorithm (Euchi and Mraihi, 2012), continuous approximation (Ellegood et al, 2015). In the work of Chalkia et al (2014) the SBRPBSS is modified and the safety of the bus stop (the size and location of the waiting area, the quality of the ground in the waiting area, and the visibility of the stop for approaching drivers, pedestrian crossing, etc.)…”
Section: Introductionmentioning
confidence: 99%