Automated generation of stacking plans for prefabricated panels transported by A-frame trailers

Prefabrication is a sustainable construction method that improves productivity and reduces environmental footprints. Prefabricated panel is one typical type of components widely used in practice. When designing panel stacking plans for transportation, practitioners should consider numerous practical...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Wang, Huiwen [verfasserIn] Yi, Wen [verfasserIn] Zhen, Lu [verfasserIn] Wang, Haoqing [verfasserIn] P. C. Chan, Albert [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Prefabrication Prefabricated panel Vertical stacking Construction technology

Übergeordnetes Werk:	Enthalten in: Advanced engineering informatics - Amsterdam [u.a.] : Elsevier Science, 2002, 57
Übergeordnetes Werk:	volume:57

DOI / URN:	10.1016/j.aei.2023.102077

Katalog-ID:	ELV063412640

Internformat


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520			\|a Prefabrication is a sustainable construction method that improves productivity and reduces environmental footprints. Prefabricated panel is one typical type of components widely used in practice. When designing panel stacking plans for transportation, practitioners should consider numerous practical factors, e.g., panel stability and reshufflings. However, in current practice, stacking plans are made on the basis of planners’ intuition and experience. A scientific method that can yield satisfactory panel stacking plans is thus required. Motivated by this real need, this paper aims to address a practical problem for practitioners: how to stack prefabricated panels transported by A-frame trailers with high stability and little reshuffling. This paper extends the literature by innovatively formulating a bi-objective mixed-integer programming model that incorporates all the aforementioned factors and objectives. A non-dominated sorting genetic algorithm is designed to approximate the Pareto optimal solutions. We conduct extensive numerical experiments to validate the effectiveness, efficiency, and applicability of our proposed model and algorithm. The developed model and algorithm are capable of automatically performing calculations and effectively generating vertical stacking plans of high quality for planners in real-world settings within seconds. Future research may be devoted to the optimization of stacking plans for other types of prefabricated components or the horizontal stacking plans for components transported by flat-bed trailers.
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publishDate	2023
allfields	10.1016/j.aei.2023.102077 doi (DE-627)ELV063412640 (ELSEVIER)S1474-0346(23)00205-7 DE-627 ger DE-627 rda eng 004 620 670 VZ 54.72 bkl 50.03 bkl Wang, Huiwen verfasserin (orcid)0000-0002-1038-4349 aut Automated generation of stacking plans for prefabricated panels transported by A-frame trailers 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Prefabrication is a sustainable construction method that improves productivity and reduces environmental footprints. Prefabricated panel is one typical type of components widely used in practice. When designing panel stacking plans for transportation, practitioners should consider numerous practical factors, e.g., panel stability and reshufflings. However, in current practice, stacking plans are made on the basis of planners’ intuition and experience. A scientific method that can yield satisfactory panel stacking plans is thus required. Motivated by this real need, this paper aims to address a practical problem for practitioners: how to stack prefabricated panels transported by A-frame trailers with high stability and little reshuffling. This paper extends the literature by innovatively formulating a bi-objective mixed-integer programming model that incorporates all the aforementioned factors and objectives. A non-dominated sorting genetic algorithm is designed to approximate the Pareto optimal solutions. We conduct extensive numerical experiments to validate the effectiveness, efficiency, and applicability of our proposed model and algorithm. The developed model and algorithm are capable of automatically performing calculations and effectively generating vertical stacking plans of high quality for planners in real-world settings within seconds. Future research may be devoted to the optimization of stacking plans for other types of prefabricated components or the horizontal stacking plans for components transported by flat-bed trailers. Prefabrication Prefabricated panel Vertical stacking Construction technology Yi, Wen verfasserin aut Zhen, Lu verfasserin aut Wang, Haoqing verfasserin aut P. C. Chan, Albert verfasserin aut Enthalten in Advanced engineering informatics Amsterdam [u.a.] : Elsevier Science, 2002 57 Online-Ressource (DE-627)320423565 (DE-600)2002862-3 (DE-576)094478821 1474-0346 nnns volume:57 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.72 Künstliche Intelligenz VZ 50.03 Methoden und Techniken der Ingenieurwissenschaften VZ AR 57
spelling	10.1016/j.aei.2023.102077 doi (DE-627)ELV063412640 (ELSEVIER)S1474-0346(23)00205-7 DE-627 ger DE-627 rda eng 004 620 670 VZ 54.72 bkl 50.03 bkl Wang, Huiwen verfasserin (orcid)0000-0002-1038-4349 aut Automated generation of stacking plans for prefabricated panels transported by A-frame trailers 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Prefabrication is a sustainable construction method that improves productivity and reduces environmental footprints. Prefabricated panel is one typical type of components widely used in practice. When designing panel stacking plans for transportation, practitioners should consider numerous practical factors, e.g., panel stability and reshufflings. However, in current practice, stacking plans are made on the basis of planners’ intuition and experience. A scientific method that can yield satisfactory panel stacking plans is thus required. Motivated by this real need, this paper aims to address a practical problem for practitioners: how to stack prefabricated panels transported by A-frame trailers with high stability and little reshuffling. This paper extends the literature by innovatively formulating a bi-objective mixed-integer programming model that incorporates all the aforementioned factors and objectives. A non-dominated sorting genetic algorithm is designed to approximate the Pareto optimal solutions. We conduct extensive numerical experiments to validate the effectiveness, efficiency, and applicability of our proposed model and algorithm. The developed model and algorithm are capable of automatically performing calculations and effectively generating vertical stacking plans of high quality for planners in real-world settings within seconds. Future research may be devoted to the optimization of stacking plans for other types of prefabricated components or the horizontal stacking plans for components transported by flat-bed trailers. Prefabrication Prefabricated panel Vertical stacking Construction technology Yi, Wen verfasserin aut Zhen, Lu verfasserin aut Wang, Haoqing verfasserin aut P. C. Chan, Albert verfasserin aut Enthalten in Advanced engineering informatics Amsterdam [u.a.] : Elsevier Science, 2002 57 Online-Ressource (DE-627)320423565 (DE-600)2002862-3 (DE-576)094478821 1474-0346 nnns volume:57 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.72 Künstliche Intelligenz VZ 50.03 Methoden und Techniken der Ingenieurwissenschaften VZ AR 57
allfields_unstemmed	10.1016/j.aei.2023.102077 doi (DE-627)ELV063412640 (ELSEVIER)S1474-0346(23)00205-7 DE-627 ger DE-627 rda eng 004 620 670 VZ 54.72 bkl 50.03 bkl Wang, Huiwen verfasserin (orcid)0000-0002-1038-4349 aut Automated generation of stacking plans for prefabricated panels transported by A-frame trailers 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Prefabrication is a sustainable construction method that improves productivity and reduces environmental footprints. Prefabricated panel is one typical type of components widely used in practice. When designing panel stacking plans for transportation, practitioners should consider numerous practical factors, e.g., panel stability and reshufflings. However, in current practice, stacking plans are made on the basis of planners’ intuition and experience. A scientific method that can yield satisfactory panel stacking plans is thus required. Motivated by this real need, this paper aims to address a practical problem for practitioners: how to stack prefabricated panels transported by A-frame trailers with high stability and little reshuffling. This paper extends the literature by innovatively formulating a bi-objective mixed-integer programming model that incorporates all the aforementioned factors and objectives. A non-dominated sorting genetic algorithm is designed to approximate the Pareto optimal solutions. We conduct extensive numerical experiments to validate the effectiveness, efficiency, and applicability of our proposed model and algorithm. The developed model and algorithm are capable of automatically performing calculations and effectively generating vertical stacking plans of high quality for planners in real-world settings within seconds. Future research may be devoted to the optimization of stacking plans for other types of prefabricated components or the horizontal stacking plans for components transported by flat-bed trailers. Prefabrication Prefabricated panel Vertical stacking Construction technology Yi, Wen verfasserin aut Zhen, Lu verfasserin aut Wang, Haoqing verfasserin aut P. C. Chan, Albert verfasserin aut Enthalten in Advanced engineering informatics Amsterdam [u.a.] : Elsevier Science, 2002 57 Online-Ressource (DE-627)320423565 (DE-600)2002862-3 (DE-576)094478821 1474-0346 nnns volume:57 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.72 Künstliche Intelligenz VZ 50.03 Methoden und Techniken der Ingenieurwissenschaften VZ AR 57
allfieldsGer	10.1016/j.aei.2023.102077 doi (DE-627)ELV063412640 (ELSEVIER)S1474-0346(23)00205-7 DE-627 ger DE-627 rda eng 004 620 670 VZ 54.72 bkl 50.03 bkl Wang, Huiwen verfasserin (orcid)0000-0002-1038-4349 aut Automated generation of stacking plans for prefabricated panels transported by A-frame trailers 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Prefabrication is a sustainable construction method that improves productivity and reduces environmental footprints. Prefabricated panel is one typical type of components widely used in practice. When designing panel stacking plans for transportation, practitioners should consider numerous practical factors, e.g., panel stability and reshufflings. However, in current practice, stacking plans are made on the basis of planners’ intuition and experience. A scientific method that can yield satisfactory panel stacking plans is thus required. Motivated by this real need, this paper aims to address a practical problem for practitioners: how to stack prefabricated panels transported by A-frame trailers with high stability and little reshuffling. This paper extends the literature by innovatively formulating a bi-objective mixed-integer programming model that incorporates all the aforementioned factors and objectives. A non-dominated sorting genetic algorithm is designed to approximate the Pareto optimal solutions. We conduct extensive numerical experiments to validate the effectiveness, efficiency, and applicability of our proposed model and algorithm. The developed model and algorithm are capable of automatically performing calculations and effectively generating vertical stacking plans of high quality for planners in real-world settings within seconds. Future research may be devoted to the optimization of stacking plans for other types of prefabricated components or the horizontal stacking plans for components transported by flat-bed trailers. Prefabrication Prefabricated panel Vertical stacking Construction technology Yi, Wen verfasserin aut Zhen, Lu verfasserin aut Wang, Haoqing verfasserin aut P. C. Chan, Albert verfasserin aut Enthalten in Advanced engineering informatics Amsterdam [u.a.] : Elsevier Science, 2002 57 Online-Ressource (DE-627)320423565 (DE-600)2002862-3 (DE-576)094478821 1474-0346 nnns volume:57 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.72 Künstliche Intelligenz VZ 50.03 Methoden und Techniken der Ingenieurwissenschaften VZ AR 57
allfieldsSound	10.1016/j.aei.2023.102077 doi (DE-627)ELV063412640 (ELSEVIER)S1474-0346(23)00205-7 DE-627 ger DE-627 rda eng 004 620 670 VZ 54.72 bkl 50.03 bkl Wang, Huiwen verfasserin (orcid)0000-0002-1038-4349 aut Automated generation of stacking plans for prefabricated panels transported by A-frame trailers 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Prefabrication is a sustainable construction method that improves productivity and reduces environmental footprints. Prefabricated panel is one typical type of components widely used in practice. When designing panel stacking plans for transportation, practitioners should consider numerous practical factors, e.g., panel stability and reshufflings. However, in current practice, stacking plans are made on the basis of planners’ intuition and experience. A scientific method that can yield satisfactory panel stacking plans is thus required. Motivated by this real need, this paper aims to address a practical problem for practitioners: how to stack prefabricated panels transported by A-frame trailers with high stability and little reshuffling. This paper extends the literature by innovatively formulating a bi-objective mixed-integer programming model that incorporates all the aforementioned factors and objectives. A non-dominated sorting genetic algorithm is designed to approximate the Pareto optimal solutions. We conduct extensive numerical experiments to validate the effectiveness, efficiency, and applicability of our proposed model and algorithm. The developed model and algorithm are capable of automatically performing calculations and effectively generating vertical stacking plans of high quality for planners in real-world settings within seconds. Future research may be devoted to the optimization of stacking plans for other types of prefabricated components or the horizontal stacking plans for components transported by flat-bed trailers. Prefabrication Prefabricated panel Vertical stacking Construction technology Yi, Wen verfasserin aut Zhen, Lu verfasserin aut Wang, Haoqing verfasserin aut P. C. Chan, Albert verfasserin aut Enthalten in Advanced engineering informatics Amsterdam [u.a.] : Elsevier Science, 2002 57 Online-Ressource (DE-627)320423565 (DE-600)2002862-3 (DE-576)094478821 1474-0346 nnns volume:57 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.72 Künstliche Intelligenz VZ 50.03 Methoden und Techniken der Ingenieurwissenschaften VZ AR 57
language	English
source	Enthalten in Advanced engineering informatics 57 volume:57
sourceStr	Enthalten in Advanced engineering informatics 57 volume:57
format_phy_str_mv	Article
bklname	Künstliche Intelligenz Methoden und Techniken der Ingenieurwissenschaften
institution	findex.gbv.de
topic_facet	Prefabrication Prefabricated panel Vertical stacking Construction technology
dewey-raw	004
isfreeaccess_bool	false
container_title	Advanced engineering informatics
authorswithroles_txt_mv	Wang, Huiwen @@aut@@ Yi, Wen @@aut@@ Zhen, Lu @@aut@@ Wang, Haoqing @@aut@@ P. C. Chan, Albert @@aut@@
publishDateDaySort_date	2023-01-01T00:00:00Z
hierarchy_top_id	320423565
dewey-sort	14
id	ELV063412640
language_de	englisch
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author	Wang, Huiwen
spellingShingle	Wang, Huiwen ddc 004 bkl 54.72 bkl 50.03 misc Prefabrication misc Prefabricated panel misc Vertical stacking misc Construction technology Automated generation of stacking plans for prefabricated panels transported by A-frame trailers
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topic_title	004 620 670 VZ 54.72 bkl 50.03 bkl Automated generation of stacking plans for prefabricated panels transported by A-frame trailers Prefabrication Prefabricated panel Vertical stacking Construction technology
topic	ddc 004 bkl 54.72 bkl 50.03 misc Prefabrication misc Prefabricated panel misc Vertical stacking misc Construction technology
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title	Automated generation of stacking plans for prefabricated panels transported by A-frame trailers
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title_full	Automated generation of stacking plans for prefabricated panels transported by A-frame trailers
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title_sort	automated generation of stacking plans for prefabricated panels transported by a-frame trailers
title_auth	Automated generation of stacking plans for prefabricated panels transported by A-frame trailers
abstract	Prefabrication is a sustainable construction method that improves productivity and reduces environmental footprints. Prefabricated panel is one typical type of components widely used in practice. When designing panel stacking plans for transportation, practitioners should consider numerous practical factors, e.g., panel stability and reshufflings. However, in current practice, stacking plans are made on the basis of planners’ intuition and experience. A scientific method that can yield satisfactory panel stacking plans is thus required. Motivated by this real need, this paper aims to address a practical problem for practitioners: how to stack prefabricated panels transported by A-frame trailers with high stability and little reshuffling. This paper extends the literature by innovatively formulating a bi-objective mixed-integer programming model that incorporates all the aforementioned factors and objectives. A non-dominated sorting genetic algorithm is designed to approximate the Pareto optimal solutions. We conduct extensive numerical experiments to validate the effectiveness, efficiency, and applicability of our proposed model and algorithm. The developed model and algorithm are capable of automatically performing calculations and effectively generating vertical stacking plans of high quality for planners in real-world settings within seconds. Future research may be devoted to the optimization of stacking plans for other types of prefabricated components or the horizontal stacking plans for components transported by flat-bed trailers.
abstractGer	Prefabrication is a sustainable construction method that improves productivity and reduces environmental footprints. Prefabricated panel is one typical type of components widely used in practice. When designing panel stacking plans for transportation, practitioners should consider numerous practical factors, e.g., panel stability and reshufflings. However, in current practice, stacking plans are made on the basis of planners’ intuition and experience. A scientific method that can yield satisfactory panel stacking plans is thus required. Motivated by this real need, this paper aims to address a practical problem for practitioners: how to stack prefabricated panels transported by A-frame trailers with high stability and little reshuffling. This paper extends the literature by innovatively formulating a bi-objective mixed-integer programming model that incorporates all the aforementioned factors and objectives. A non-dominated sorting genetic algorithm is designed to approximate the Pareto optimal solutions. We conduct extensive numerical experiments to validate the effectiveness, efficiency, and applicability of our proposed model and algorithm. The developed model and algorithm are capable of automatically performing calculations and effectively generating vertical stacking plans of high quality for planners in real-world settings within seconds. Future research may be devoted to the optimization of stacking plans for other types of prefabricated components or the horizontal stacking plans for components transported by flat-bed trailers.
abstract_unstemmed	Prefabrication is a sustainable construction method that improves productivity and reduces environmental footprints. Prefabricated panel is one typical type of components widely used in practice. When designing panel stacking plans for transportation, practitioners should consider numerous practical factors, e.g., panel stability and reshufflings. However, in current practice, stacking plans are made on the basis of planners’ intuition and experience. A scientific method that can yield satisfactory panel stacking plans is thus required. Motivated by this real need, this paper aims to address a practical problem for practitioners: how to stack prefabricated panels transported by A-frame trailers with high stability and little reshuffling. This paper extends the literature by innovatively formulating a bi-objective mixed-integer programming model that incorporates all the aforementioned factors and objectives. A non-dominated sorting genetic algorithm is designed to approximate the Pareto optimal solutions. We conduct extensive numerical experiments to validate the effectiveness, efficiency, and applicability of our proposed model and algorithm. The developed model and algorithm are capable of automatically performing calculations and effectively generating vertical stacking plans of high quality for planners in real-world settings within seconds. Future research may be devoted to the optimization of stacking plans for other types of prefabricated components or the horizontal stacking plans for components transported by flat-bed trailers.
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title_short	Automated generation of stacking plans for prefabricated panels transported by A-frame trailers
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author2	Yi, Wen Zhen, Lu Wang, Haoqing P. C. Chan, Albert
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up_date	2024-07-06T19:38:36.958Z
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score	7.400075

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Automated generation of stacking plans for prefabricated panels transported by A-frame trailers

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