- -

A hybrid genetic algorithm for route optimization in the bale collecting problem

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

A hybrid genetic algorithm for route optimization in the bale collecting problem

Mostrar el registro completo del ítem

Gracia Calandin, CP.; Diezma Iglesias, B.; Barreiro Elorza, P. (2013). A hybrid genetic algorithm for route optimization in the bale collecting problem. Spanish Journal of Agricultural Research. 11(3):603-614. https://doi.org/10.5424/sjar/2013113-3635

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/45759

Ficheros en el ítem

Thumbnail
Nombre: Gracia;PILAR BARREIRO ...
Tamaño: 1.119Mb
Formato: PDF
Descripción: Versión editorial
Abrir/Preview

Metadatos del ítem

Título: A hybrid genetic algorithm for route optimization in the bale collecting problem
Autor: Gracia Calandin, Carlos Pablo Diezma Iglesias, Belén Barreiro Elorza, Pilar
Entidad UPV: Universitat Politècnica de València. Departamento de Organización de Empresas - Departament d'Organització d'Empreses
Fecha difusión:
Resumen:
The bale collecting problem (BCP) appears after harvest operations in grain and other crops. Its solution defines the sequence of collecting bales which lie scattered over the field. Current technology on navigation-aid ...[+]
Palabras clave: Precision agriculture , Logistics , Wheat harvest
Derechos de uso: Reserva de todos los derechos
Fuente:
Spanish Journal of Agricultural Research. (issn: 1695-971X ) (eissn: 2171-9292 )
DOI: 10.5424/sjar/2013113-3635
Editorial:
Instituto Nacional de Investigacón y Tecnología Agraria y Alimentaria
Versión del editor: http://dx.doi.org/10.5424/sjar/2013113-3635
Código del Proyecto:
info:eu-repo/grantAgreement/MICINN//AGL2010-15334/ES/CUBICACION DE LA BIOMASA DE ARBOLES FRUTALES EN BASE A DENDROMETRIA ADAPTADA Y TECNOLOGIA LIDAR EN VISTAS A LA GESTION DE LAS PLANTACIONES Y APROVECHAMIENTO DE SUS RESIDUOS/
Agradecimientos:
This work was supported in part by the Spanish Government (research project AGL2010-15334).
Tipo: Artículo

References

Amiama, C., Bueno, J., Álvarez, C. J., & Pereira, J. M. (2008). Design and field test of an automatic data acquisition system in a self-propelled forage harvester. Computers and Electronics in Agriculture, 61(2), 192-200. doi:10.1016/j.compag.2007.11.006

Baker, B. M., & Ayechew, M. A. (2003). A genetic algorithm for the vehicle routing problem. Computers & Operations Research, 30(5), 787-800. doi:10.1016/s0305-0548(02)00051-5

Baykasolu, A., Oumlzbakr, L., & Tapk, P. (2007). Artificial Bee Colony Algorithm and Its Application to Generalized Assignment Problem. Swarm Intelligence, Focus on Ant and Particle Swarm Optimization. doi:10.5772/5101 [+]
Amiama, C., Bueno, J., Álvarez, C. J., & Pereira, J. M. (2008). Design and field test of an automatic data acquisition system in a self-propelled forage harvester. Computers and Electronics in Agriculture, 61(2), 192-200. doi:10.1016/j.compag.2007.11.006

Baker, B. M., & Ayechew, M. A. (2003). A genetic algorithm for the vehicle routing problem. Computers & Operations Research, 30(5), 787-800. doi:10.1016/s0305-0548(02)00051-5

Baykasolu, A., Oumlzbakr, L., & Tapk, P. (2007). Artificial Bee Colony Algorithm and Its Application to Generalized Assignment Problem. Swarm Intelligence, Focus on Ant and Particle Swarm Optimization. doi:10.5772/5101

Bentley, J. J. (1992). Fast Algorithms for Geometric Traveling Salesman Problems. ORSA Journal on Computing, 4(4), 387-411. doi:10.1287/ijoc.4.4.387

Bochtis, D. D., & Sørensen, C. G. (2009). The vehicle routing problem in field logistics part I. Biosystems Engineering, 104(4), 447-457. doi:10.1016/j.biosystemseng.2009.09.003

Bochtis, D. D., & Sørensen, C. G. (2010). The vehicle routing problem in field logistics: Part II. Biosystems Engineering, 105(2), 180-188. doi:10.1016/j.biosystemseng.2009.10.006

Bochtis, D. D., Dogoulis, P., Busato, P., Sørensen, C. G., Berruto, R., & Gemtos, T. (2013). A flow-shop problem formulation of biomass handling operations scheduling. Computers and Electronics in Agriculture, 91, 49-56. doi:10.1016/j.compag.2012.11.015

Brady, R. M. (1985). Optimization strategies gleaned from biological evolution. Nature, 317(6040), 804-806. doi:10.1038/317804a0

Chen, J.-S., Pan, J. C.-H., & Lin, C.-M. (2008). A hybrid genetic algorithm for the re-entrant flow-shop scheduling problem. Expert Systems with Applications, 34(1), 570-577. doi:10.1016/j.eswa.2006.09.021

Cook, S. E., & Bramley, R. G. V. (1998). Precision agriculture — opportunities, benefits and pitfalls of site-specific crop management in Australia. Australian Journal of Experimental Agriculture, 38(7), 753. doi:10.1071/ea97156

Cordeau, J.-F., Gendreau, M., Laporte, G., Potvin, J.-Y., & Semet, F. (2002). A guide to vehicle routing heuristics. Journal of the Operational Research Society, 53(5), 512-522. doi:10.1057/palgrave.jors.2601319

Dantzig, G., Fulkerson, R., & Johnson, S. (1954). Solution of a Large-Scale Traveling-Salesman Problem. Journal of the Operations Research Society of America, 2(4), 393-410. doi:10.1287/opre.2.4.393

Dasgupta, D. (Ed.). (1999). Artificial Immune Systems and Their Applications. doi:10.1007/978-3-642-59901-9

Davis L, 1985. Job shop scheduling with genetic algorithms. Proc of the First Int Conf on Genetic Algorithms and their Applications, Pittsburg, PA (USA). July 24-26. pp: 136-140.

De Castro LN, Timmis J, 2002. Artificial immune systems: a new computational approach. Springer-Verlag Inc, London, UK.

Dorigo, M., Birattari, M., Blum, C., Gambardella, L. M., Mondada, F., & Stützle, T. (Eds.). (2004). Ant Colony Optimization and Swarm Intelligence. Lecture Notes in Computer Science. doi:10.1007/b99492

Eksioglu, B., Vural, A. V., & Reisman, A. (2009). The vehicle routing problem: A taxonomic review. Computers & Industrial Engineering, 57(4), 1472-1483. doi:10.1016/j.cie.2009.05.009

Garey MR, Johnson DS, 1979. Computers and intractability: a guide to the theory of NP-completeness. WH Freeman & Company, NY.

Gillett, B. E., & Miller, L. R. (1974). A Heuristic Algorithm for the Vehicle-Dispatch Problem. Operations Research, 22(2), 340-349. doi:10.1287/opre.22.2.340

Goldberg DE, 1989. Genetic algorithms in search, optimization and machine learning. Kluwer Acad Publ, Boston, MA, USA.

Gracia, C., Andrés, C., & Gracia, L. (2011). A hybrid approach based on genetic algorithms to solve the problem of cutting structural beams in a metalwork company. Journal of Heuristics, 19(2), 253-273. doi:10.1007/s10732-011-9187-x

Grisso RD, Cundiff JS, Vaughan DH, 2007. Investigating machinery management parameters with computers tools, ASABE Conf, Paper 071030.

Hameed, I. A., Bochtis, D. D., Sørensen, C. G., & Vougioukas, S. (2012). An object-oriented model for simulating agricultural in-field machinery activities. Computers and Electronics in Agriculture, 81, 24-32. doi:10.1016/j.compag.2011.11.003

Holland JH, 1975. Adaptation in natural and artificial systems (Holland JH, ed.). Ann Arbor MI Univ of Michigan Press, MI, USA.

Jünger M, Reinelt G, Rinaldi G, 1995. The traveling salesman problem. In: Network models. Handbooks on Operations Research and Management Science 7 (Ball MO, Magnanti TL, Monma CL, Nemhauser GL, eds.). Elsevier, Amsterdam, pp: 225-330.

Kennedy JF, Kennedy J, Eberhart R, Shi Y, 2001. Swarm intelligence. Academic Press Inc, London.

Laporte, G., Gendreau, M., Potvin, J.-Y., & Semet, F. (2000). Classical and modern heuristics for the vehicle routing problem. International Transactions in Operational Research, 7(4-5), 285-300. doi:10.1111/j.1475-3995.2000.tb00200.x

Martin O, Otto SW, Felten EW, 1991. Large-step markov chains for the travelling salesman problem. Complex Syst 5(3): 299-326.

Nikkilä, R., Seilonen, I., & Koskinen, K. (2010). Software architecture for farm management information systems in precision agriculture. Computers and Electronics in Agriculture, 70(2), 328-336. doi:10.1016/j.compag.2009.08.013

Sørensen, C. G., Pesonen, L., Bochtis, D. D., Vougioukas, S. G., & Suomi, P. (2011). Functional requirements for a future farm management information system. Computers and Electronics in Agriculture, 76(2), 266-276. doi:10.1016/j.compag.2011.02.005

Toth, P., & Vigo, D. (2002). 2. Branch-And-Bound Algorithms for the Capacitated VRP. The Vehicle Routing Problem, 29-51. doi:10.1137/1.9780898718515.ch2

Wang, C.-H., & Lu, J.-Z. (2008). An effective evolutionary algorithm for the practical capacitated vehicle routing problems. Journal of Intelligent Manufacturing, 21(4), 363-375. doi:10.1007/s10845-008-0185-2

Zhang, N., Wang, M., & Wang, N. (2002). Precision agriculture—a worldwide overview. Computers and Electronics in Agriculture, 36(2-3), 113-132. doi:10.1016/s0168-1699(02)00096-0

[-]

recommendations

 

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro completo del ítem