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A hybrid approach based on genetic algorithms to solve the problem of cutting structural beams in a metalwork company

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A hybrid approach based on genetic algorithms to solve the problem of cutting structural beams in a metalwork company

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dc.contributor.author Gracia Calandin, Carlos Pablo es_ES
dc.contributor.author Andrés Romano, Carlos es_ES
dc.contributor.author Gracia Calandin, Luis Ignacio es_ES
dc.date.accessioned 2016-03-03T12:50:59Z
dc.date.available 2016-03-03T12:50:59Z
dc.date.issued 2013-04
dc.identifier.issn 1381-1231
dc.identifier.uri http://hdl.handle.net/10251/61406
dc.description.abstract This work presents a hybrid approach based on the use of genetic algorithms to solve efficiently the problem of cutting structural beams arising in a local metalwork company. The problem belongs to the class of one-dimensional multiple stock sizes cutting stock problem, namely 1-dimensional multiple stock sizes cutting stock problem. The proposed approach handles overproduction and underproduction of beams and embodies the reusability of remnants in the optimization process. Along with genetic algorithms, the approach incorporates other novel refinement algorithms that are based on different search and clustering strategies.Moreover, a new encoding with a variable number of genes is developed for cutting patterns in order to make possible the application of genetic operators. The approach is experimentally tested on a set of instances similar to those of the local metalwork company. In particular, comparative results show that the proposed approach substantially improves the performance of previous heuristics. es_ES
dc.language Inglés es_ES
dc.publisher Springer Verlag (Germany) es_ES
dc.relation.ispartof Journal of Heuristics es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Cutting stock problem es_ES
dc.subject Pattern generation es_ES
dc.subject Hybrid metaheuristics es_ES
dc.subject GA es_ES
dc.subject.classification ORGANIZACION DE EMPRESAS es_ES
dc.subject.classification INGENIERIA DE SISTEMAS Y AUTOMATICA es_ES
dc.title A hybrid approach based on genetic algorithms to solve the problem of cutting structural beams in a metalwork company es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s10732-011-9187-x
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Organización de Empresas - Departament d'Organització d'Empreses es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería de Sistemas y Automática - Departament d'Enginyeria de Sistemes i Automàtica es_ES
dc.description.bibliographicCitation Gracia Calandin, CP.; Andrés Romano, C.; Gracia Calandin, LI. (2013). 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 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.1007/s10732-011-9187-x es_ES
dc.description.upvformatpinicio 253 es_ES
dc.description.upvformatpfin 273 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 19 es_ES
dc.description.issue 2 es_ES
dc.relation.senia 237036 es_ES
dc.description.references Aktin, T., Özdemir, R.G.: An integrated approach to the one dimensional cutting stock problem in coronary stent manufacturing. Eur. J. Oper. Res. 196, 737–743 (2009) es_ES
dc.description.references Alves, C., Valério de Carvalho, J.M.: A stabilized branch-and-price-and-cut algorithm for the multiple length cutting stock problem. Comput. Oper. Res. 35, 1315–1328 (2008) es_ES
dc.description.references Anand, S., McCord, C., Sharma, R., et al.: An integrated machine vision based system for solving the nonconvex cutting stock problem using genetic algorithms. J. Manuf. Syst. 18, 396–415 (1999) es_ES
dc.description.references Belov, G., Scheithauer, G.: A cutting plane algorithm for the one-dimensional cutting stock problem with multiple stock lengths. Eur. J. Oper. Res. 141, 274–294 (2002) es_ES
dc.description.references Christofides, N., Hadjiconstantinou, E.: An exact algorithm for orthogonal 2-D cutting problems using guillotine cuts. Eur. J. Oper. Res. 83, 21–38 (1995) es_ES
dc.description.references Elizondo, R., Parada, V., Pradenas, L., Artigues, C.: An evolutionary and constructive approach to a crew scheduling problem in underground passenger transport. J. Heuristics 16, 575–591 (2010) es_ES
dc.description.references Fan, L., Mumford, C.L.: A metaheuristic approach to the urban transit routing problem. J. Heuristics 16, 353–372 (2010) es_ES
dc.description.references Gau, T., Wäscher, G.: CUTGEN1: a problem generator for the standard one-dimensional cutting stock problem. Eur. J. Oper. Res. 84, 572–579 (1995) es_ES
dc.description.references Gilmore, P.C., Gomory, R.E.: A linear programming approach to the cutting stock problem. Oper. Res. 9, 849–859 (1961) es_ES
dc.description.references Gilmore, P.C., Gomory, R.E.: A linear programming approach to the cutting stock problem. Part II. Oper. Res. 11, 863–888 (1963) es_ES
dc.description.references Ghiani, G., Laganà, G., Laporte, G., Mari, F.: Ant colony optimization for the arc routing problem with intermediate facilities under capacity and length restrictions. J. Heuristics 16, 211–233 (2010) es_ES
dc.description.references Gonçalves, J.F., Resende, G.C.: Biased random-key genetic algorithms for combinatorial optimization. J. Heuristics (2011). doi: 10.1007/s10732-010-9143-1 es_ES
dc.description.references Gradisar, M., Kljajic, M., Resinovic, G., et al.: A sequential heuristic procedure for one-dimensional cutting. Eur. J. Oper. Res. 114, 557–568 (1999) es_ES
dc.description.references Haessler, R.W.: One-dimensional cutting stock problems and solution procedures. Math. Comput. Model. 16, 1–8 (1992) es_ES
dc.description.references Haessler, R.W., Sweeney, P.E.: Cutting stock problems and solution procedures. Eur. J. Oper. Res. 54(2), 141–150 (1991) es_ES
dc.description.references Haessler, R.W.: Solving the two-stage cutting stock problem. Omega 7, 145–151 (1979) es_ES
dc.description.references Hinterding, R., Khan, L.: Genetic algorithms for cutting stock problems: with and without contiguity. In: Yao, X. (ed.) Progress in Evolutionary Computation. LNAI, vol. 956, pp. 166–186. Springer, Berlin (1995) es_ES
dc.description.references Holthaus, O.: Decomposition approaches for solving the integer one-dimensional cutting stock problem with different types of standard lengths. Eur. J. Oper. Res. 141, 295–312 (2002) es_ES
dc.description.references Kantorovich, L.V.: Mathematical methods of organizing and planning production. Manag. Sci. 6, 366–422 (1939) (Translation to English 1960) es_ES
dc.description.references Liang, K., Yao, X., Newton, C., et al.: A new evolutionary approach to cutting stock problems with and without contiguity. Comput. Oper. Res. 29, 1641–1659 (2002) es_ES
dc.description.references Poldi, K., Arenales, M.: Heuristics for the one-dimensional cutting stock problem with limited multiple stock lengths. Comput. Oper. Res. 36, 2074–2081 (2009) es_ES
dc.description.references Suliman, S.M.A.: Pattern generating procedure for the cutting stock problem. Int. J. Prod. Econ. 74, 293–301 (2001) es_ES
dc.description.references Talbi, E.-G.: A taxonomy of hybrid metaheuristics. J. Heuristics 8, 541–564 (2002) es_ES
dc.description.references Vahrenkamp, R.: Random search in the one-dimensional cutting stock problem. Eur. J. Oper. Res. 95, 191–200 (1996) es_ES
dc.description.references Vanderbeck, F.: Exact algorithm for minimizing the number of set ups in the one dimensional cutting stock problems. Oper. Res. 48, 915–926 (2000) es_ES
dc.description.references Wagner, B.J.: A genetic algorithm solution for one-dimensional bundled stock cutting. Eur. J. Oper. Res. 117, 368–381 (1999) es_ES
dc.description.references Wäscher, G., Haußner, H., Schumann, H.: An improved typology of cutting and packing problems. Eur. J. Oper. Res. 183, 1109–1130 (2007) es_ES


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