{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T13:00:58Z","timestamp":1772715658050,"version":"3.50.1"},"reference-count":66,"publisher":"Springer Science and Business Media LLC","issue":"34","license":[{"start":{"date-parts":[[2024,9,14]],"date-time":"2024-09-14T00:00:00Z","timestamp":1726272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,9,14]],"date-time":"2024-09-14T00:00:00Z","timestamp":1726272000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/100022100","name":"Tactical Technology Office","doi-asserted-by":"publisher","award":["D22AP00147\u201300"],"award-info":[{"award-number":["D22AP00147\u201300"]}],"id":[{"id":"10.13039\/100022100","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2024,12]]},"DOI":"10.1007\/s00521-024-10332-w","type":"journal-article","created":{"date-parts":[[2024,9,14]],"date-time":"2024-09-14T08:02:47Z","timestamp":1726300967000},"page":"21703-21721","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Optimizing island sequencing in laser powder bed fusion using Genetic Algorithms"],"prefix":"10.1007","volume":"36","author":[{"given":"Amit Kumar","family":"Ball","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Riddhiman","family":"Raut","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6053-0092","authenticated-orcid":false,"given":"Amrita","family":"Basak","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,9,14]]},"reference":[{"key":"10332_CR1","doi-asserted-by":"publisher","first-page":"7936","DOI":"10.3390\/su12197936","volume":"12","author":"A Alfaify","year":"2020","unstructured":"Alfaify A, Saleh M, Abdullah FM, Al-Ahmari AM (2020) Design for additive manufacturing: a systematic review. Sustainability 12:7936. https:\/\/doi.org\/10.3390\/su12197936","journal-title":"Sustainability"},{"key":"10332_CR2","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1016\/j.mattod.2017.07.001","volume":"21","author":"SAM Tofail","year":"2018","unstructured":"Tofail SAM, Koumoulos EP, Bandyopadhyay A, Bose S, O\u2019Donoghue L, Charitidis C (2018) Additive manufacturing: scientific and technological challenges, market uptake and opportunities. Mater Today 21:22\u201337. https:\/\/doi.org\/10.1016\/j.mattod.2017.07.001","journal-title":"Mater Today"},{"key":"10332_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2019\/9656938","volume":"2019","author":"M Jim\u00e9nez","year":"2019","unstructured":"Jim\u00e9nez M, Romero L, Dom\u00ednguez IA, del Espinosa MM, Dominguez M (2019) Additive manufacturing technologies: an overview about 3D printing methods and future prospects. Complexity 2019:1\u201330. https:\/\/doi.org\/10.1155\/2019\/9656938","journal-title":"Complexity"},{"key":"10332_CR4","doi-asserted-by":"crossref","unstructured":"Najmon JC, Raeisi S, Tovar A (2019) Review of additive manufacturing technologies and applications in the aerospace industry. In: Addit. Manuf. Aerosp. Ind. Elsevier, pp 7\u201331","DOI":"10.1016\/B978-0-12-814062-8.00002-9"},{"key":"10332_CR5","doi-asserted-by":"publisher","DOI":"10.4103\/am.am_20_20","author":"A Ariz","year":"2021","unstructured":"Ariz A, Tasneem I, Bharti D, Vaish A, Haleem A, Javaid M (2021) Is additive manufacturing of patient-specific implant is beneficial for orthopedics. Apollo Med. https:\/\/doi.org\/10.4103\/am.am_20_20","journal-title":"Apollo Med"},{"key":"10332_CR6","doi-asserted-by":"publisher","DOI":"10.1002\/adma.201901994","author":"EA Guzzi","year":"2020","unstructured":"Guzzi EA, Tibbitt MW (2020) Additive manufacturing of precision biomaterials. Adv Mater. https:\/\/doi.org\/10.1002\/adma.201901994","journal-title":"Adv Mater"},{"key":"10332_CR7","doi-asserted-by":"publisher","first-page":"282","DOI":"10.1016\/j.copbio.2021.09.004","volume":"73","author":"NC Paxton","year":"2022","unstructured":"Paxton NC, Nightingale RC, Woodruff MA (2022) Capturing patient anatomy for designing and manufacturing personalized prostheses. Curr Opin Biotechnol 73:282\u2013289. https:\/\/doi.org\/10.1016\/j.copbio.2021.09.004","journal-title":"Curr Opin Biotechnol"},{"key":"10332_CR8","doi-asserted-by":"publisher","DOI":"10.1016\/j.jobe.2021.103603","volume":"45","author":"A Pajonk","year":"2022","unstructured":"Pajonk A, Prieto A, Blum U, Knaack U (2022) Multi-material additive manufacturing in architecture and construction: a review. J Build Eng 45:103603. https:\/\/doi.org\/10.1016\/j.jobe.2021.103603","journal-title":"J Build Eng"},{"key":"10332_CR9","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1884\/2154-8587\/CGP\/v09i01\/57-81","volume":"9","author":"R van Woensel","year":"2018","unstructured":"van Woensel R, van Oirschot T, Burgmans MJH, Mohammadi PhDM, Hermans K (2018) Printing architecture: an overview of existing and promising additive manufacturing methods and their application in the building industry. Int J Constr Environ 9:57\u201381. https:\/\/doi.org\/10.1884\/2154-8587\/CGP\/v09i01\/57-81","journal-title":"Int J Constr Environ"},{"key":"10332_CR10","doi-asserted-by":"publisher","first-page":"1150","DOI":"10.1016\/j.proeng.2017.04.275","volume":"180","author":"I Paoletti","year":"2017","unstructured":"Paoletti I (2017) Mass customization with additive manufacturing: new perspectives for multi performative building components in architecture. Procedia Eng 180:1150\u20131159. https:\/\/doi.org\/10.1016\/j.proeng.2017.04.275","journal-title":"Procedia Eng"},{"key":"10332_CR11","doi-asserted-by":"publisher","first-page":"332","DOI":"10.1016\/j.jmapro.2017.08.008","volume":"29","author":"MA Habib","year":"2017","unstructured":"Habib MA, Khoda B (2017) Support grain architecture design for additive manufacturing. J Manuf Process 29:332\u2013342. https:\/\/doi.org\/10.1016\/j.jmapro.2017.08.008","journal-title":"J Manuf Process"},{"key":"10332_CR12","doi-asserted-by":"publisher","first-page":"378","DOI":"10.1016\/j.promfg.2015.09.045","volume":"1","author":"A Habib","year":"2015","unstructured":"Habib A, Ahsan N, Khoda B (2015) Optimizing material deposition direction for functional internal architecture in additive manufacturing processes. Procedia Manuf 1:378\u2013392. https:\/\/doi.org\/10.1016\/j.promfg.2015.09.045","journal-title":"Procedia Manuf"},{"key":"10332_CR13","doi-asserted-by":"publisher","first-page":"225","DOI":"10.1016\/j.techfore.2015.07.024","volume":"102","author":"M Bogers","year":"2016","unstructured":"Bogers M, Hadar R, Bilberg A (2016) Additive manufacturing for consumer-centric business models: Implications for supply chains in consumer goods manufacturing. Technol Forecast Soc Change 102:225\u2013239. https:\/\/doi.org\/10.1016\/j.techfore.2015.07.024","journal-title":"Technol Forecast Soc Change"},{"key":"10332_CR14","doi-asserted-by":"publisher","first-page":"189","DOI":"10.4236\/jssm.2017.103017","volume":"10","author":"M Attaran","year":"2017","unstructured":"Attaran M (2017) Additive manufacturing: the most promising technology to alter the supply chain and logistics. J Serv Sci Manag 10:189\u2013206. https:\/\/doi.org\/10.4236\/jssm.2017.103017","journal-title":"J Serv Sci Manag"},{"key":"10332_CR15","doi-asserted-by":"crossref","unstructured":"Vasco JC (2021) Additive manufacturing for the automotive industry. In: Addit. Manuf. Elsevier, pp 505\u2013530","DOI":"10.1016\/B978-0-12-818411-0.00010-0"},{"key":"10332_CR16","doi-asserted-by":"publisher","first-page":"1671","DOI":"10.1007\/s00170-017-0239-8","volume":"92","author":"R Leal","year":"2017","unstructured":"Leal R, Barreiros FM, Alves L, Romeiro F, Vasco JC, Santos M, Marto C (2017) Additive manufacturing tooling for the automotive industry. Int J Adv Manuf Technol 92:1671\u20131676. https:\/\/doi.org\/10.1007\/s00170-017-0239-8","journal-title":"Int J Adv Manuf Technol"},{"key":"10332_CR17","doi-asserted-by":"publisher","first-page":"1677","DOI":"10.1007\/s11837-018-3024-8","volume":"70","author":"P-A Pires","year":"2018","unstructured":"Pires P-A, Desmaison O, Megahed M (2018) ICME manufacturability assessment in powder bed fusion additive manufacturing. JOM 70:1677\u20131685. https:\/\/doi.org\/10.1007\/s11837-018-3024-8","journal-title":"JOM"},{"key":"10332_CR18","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmatprotec.2020.117018","volume":"291","author":"AP Nagalingam","year":"2021","unstructured":"Nagalingam AP, Lee J-Y, Yeo SH (2021) Multi-jet hydrodynamic surface finishing and X-ray computed tomography (X-CT) inspection of laser powder bed fused Inconel 625 fuel injection\/spray nozzles. J Mater Process Technol 291:117018. https:\/\/doi.org\/10.1016\/j.jmatprotec.2020.117018","journal-title":"J Mater Process Technol"},{"key":"10332_CR19","doi-asserted-by":"publisher","first-page":"350","DOI":"10.1016\/j.matpr.2020.08.415","volume":"46","author":"D Dev Singh","year":"2021","unstructured":"Dev Singh D, Mahender T, Raji Reddy A (2021) Powder bed fusion process: a brief review. Mater Today Proc 46:350\u2013355. https:\/\/doi.org\/10.1016\/j.matpr.2020.08.415","journal-title":"Mater Today Proc"},{"key":"10332_CR20","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1108\/RPJ-01-2022-0014","volume":"28","author":"M Mehrpouya","year":"2022","unstructured":"Mehrpouya M, Tuma D, Vaneker T, Afrasiabi M, Bambach M, Gibson I (2022) Multimaterial powder bed fusion techniques. Rapid Prototyp J 28:1\u201319. https:\/\/doi.org\/10.1108\/RPJ-01-2022-0014","journal-title":"Rapid Prototyp J"},{"key":"10332_CR21","doi-asserted-by":"publisher","first-page":"347","DOI":"10.1080\/17452759.2021.1928520","volume":"16","author":"C Wei","year":"2021","unstructured":"Wei C, Li L (2021) Recent progress and scientific challenges in multi-material additive manufacturing via laser-based powder bed fusion. Virtual Phys Prototyp 16:347\u2013371. https:\/\/doi.org\/10.1080\/17452759.2021.1928520","journal-title":"Virtual Phys Prototyp"},{"key":"10332_CR22","doi-asserted-by":"publisher","first-page":"424","DOI":"10.3390\/met13020424","volume":"13","author":"ND Dejene","year":"2023","unstructured":"Dejene ND, Lemu HG (2023) Current status and challenges of powder bed fusion-based metal additive manufacturing: literature review. Metals (Basel) 13:424. https:\/\/doi.org\/10.3390\/met13020424","journal-title":"Metals (Basel)"},{"key":"10332_CR23","doi-asserted-by":"publisher","first-page":"1084","DOI":"10.3390\/ma16031084","volume":"16","author":"A Martucci","year":"2023","unstructured":"Martucci A, Aversa A, Lombardi M (2023) Ongoing challenges of laser-based powder bed fusion processing of Al Alloys and potential solutions from the literature\u2014a review. Materials 16:1084. https:\/\/doi.org\/10.3390\/ma16031084","journal-title":"Materials"},{"key":"10332_CR24","doi-asserted-by":"crossref","unstructured":"Rastogi P, Gharde S, Kandasubramanian B (2020) Thermal Effects in 3D Printed Parts. pp 43\u201368","DOI":"10.1007\/978-981-15-5424-7_3"},{"key":"10332_CR25","doi-asserted-by":"publisher","first-page":"252","DOI":"10.3221\/IGF-ESIS.53.21","volume":"14","author":"P Ferro","year":"2020","unstructured":"Ferro P, Berto F, Romanin L (2020) Understanding powder bed fusion additive manufacturing phenomena via numerical simulation. Frat ed Integrit\u00e0 Strutt 14:252\u2013284. https:\/\/doi.org\/10.3221\/IGF-ESIS.53.21","journal-title":"Frat ed Integrit\u00e0 Strutt"},{"key":"10332_CR26","doi-asserted-by":"publisher","DOI":"10.1016\/j.cjmeam.2022.100039","volume":"1","author":"D Xie","year":"2022","unstructured":"Xie D, Lv F, Yang Y, Shen L, Tian Z, Shuai C, Chen B, Zhao J (2022) A review on distortion and residual stress in additive manufacturing. Chin J Mech Eng Addit Manuf Front 1:100039. https:\/\/doi.org\/10.1016\/j.cjmeam.2022.100039","journal-title":"Chin J Mech Eng Addit Manuf Front"},{"key":"10332_CR27","doi-asserted-by":"publisher","first-page":"773","DOI":"10.1016\/j.jmatprotec.2018.01.029","volume":"255","author":"F Calignano","year":"2018","unstructured":"Calignano F, Cattano G, Manfredi D (2018) Manufacturing of thin wall structures in AlSi10Mg alloy by laser powder bed fusion through process parameters. J Mater Process Technol 255:773\u2013783. https:\/\/doi.org\/10.1016\/j.jmatprotec.2018.01.029","journal-title":"J Mater Process Technol"},{"key":"10332_CR28","doi-asserted-by":"publisher","first-page":"122","DOI":"10.1016\/j.matdes.2017.09.018","volume":"135","author":"K An","year":"2017","unstructured":"An K, Yuan L, Dial L, Spinelli I, Stoica AD, Gao Y (2017) Neutron residual stress measurement and numerical modeling in a curved thin-walled structure by laser powder bed fusion additive manufacturing. Mater Des 135:122\u2013132. https:\/\/doi.org\/10.1016\/j.matdes.2017.09.018","journal-title":"Mater Des"},{"key":"10332_CR29","doi-asserted-by":"publisher","DOI":"10.1016\/j.addma.2020.101169","volume":"34","author":"CL Druzgalski","year":"2020","unstructured":"Druzgalski CL, Ashby A, Guss G, King WE, Roehling TT, Matthews MJ (2020) Process optimization of complex geometries using feed forward control for laser powder bed fusion additive manufacturing. Addit Manuf 34:101169. https:\/\/doi.org\/10.1016\/j.addma.2020.101169","journal-title":"Addit Manuf"},{"key":"10332_CR30","doi-asserted-by":"publisher","first-page":"869","DOI":"10.1016\/j.addma.2018.05.001","volume":"22","author":"H Peng","year":"2018","unstructured":"Peng H, Ghasri-Khouzani M, Gong S et al (2018) Fast prediction of thermal distortion in metal powder bed fusion additive manufacturing: Part 2, a quasi-static thermo-mechanical model. Addit Manuf 22:869\u2013882. https:\/\/doi.org\/10.1016\/j.addma.2018.05.001","journal-title":"Addit Manuf"},{"key":"10332_CR31","doi-asserted-by":"publisher","DOI":"10.1016\/j.addma.2021.102116","author":"Q Chen","year":"2021","unstructured":"Chen Q, Taylor H, Takezawa A, Liang X, Jimenez X, Wicker R, To AC (2021) Island scanning pattern optimization for residual deformation mitigation in laser powder bed fusion via sequential inherent strain method and sensitivity analysis. Addit Manuf. https:\/\/doi.org\/10.1016\/j.addma.2021.102116","journal-title":"Addit Manuf"},{"key":"10332_CR32","doi-asserted-by":"publisher","first-page":"489","DOI":"10.1016\/j.addma.2019.03.034","volume":"27","author":"RK Ganeriwala","year":"2019","unstructured":"Ganeriwala RK, Strantza M, King WE, Clausen B, Phan TQ, Levine LE, Brown DW, Hodge NE (2019) Evaluation of a thermomechanical model for prediction of residual stress during laser powder bed fusion of Ti-6Al-4V. Addit Manuf 27:489\u2013502. https:\/\/doi.org\/10.1016\/j.addma.2019.03.034","journal-title":"Addit Manuf"},{"key":"10332_CR33","doi-asserted-by":"publisher","DOI":"10.1016\/j.cma.2021.114095","volume":"386","author":"G Misiun","year":"2021","unstructured":"Misiun G, van de Ven E, Langelaar M, Geijselaers H, van Keulen F, van den Boogaard T, Ayas C (2021) Topology optimization for additive manufacturing with distortion constraints. Comput Methods Appl Mech Eng 386:114095. https:\/\/doi.org\/10.1016\/j.cma.2021.114095","journal-title":"Comput Methods Appl Mech Eng"},{"key":"10332_CR34","doi-asserted-by":"publisher","DOI":"10.1115\/IMECE2020-24581","author":"E Malekipour","year":"2020","unstructured":"Malekipour E, Valladares H, Shin Y, El-Mounayri H (2020) Optimization of chessboard scanning strategy using genetic algorithm in multi-laser additive manufacturing process. Adv Manuf. https:\/\/doi.org\/10.1115\/IMECE2020-24581","journal-title":"Adv Manuf"},{"key":"10332_CR35","doi-asserted-by":"publisher","first-page":"258","DOI":"10.1016\/j.addma.2019.02.006","volume":"26","author":"C Li","year":"2019","unstructured":"Li C, Gouge MF, Denlinger ER, Irwin JE, Michaleris P (2019) Estimation of part-to-powder heat losses as surface convection in laser powder bed fusion. Addit Manuf 26:258\u2013269. https:\/\/doi.org\/10.1016\/j.addma.2019.02.006","journal-title":"Addit Manuf"},{"key":"10332_CR36","doi-asserted-by":"crossref","unstructured":"Irwin J, Gouge M (2018) Validation of the American makes builds. In: Thermo-mechanical model. Addit. Manuf. Elsevier, pp 251\u2013263","DOI":"10.1016\/B978-0-12-811820-7.00018-5"},{"key":"10332_CR37","doi-asserted-by":"crossref","unstructured":"Gouge M, Michaleris P, Denlinger E, Irwin J (2018) The finite element method for the thermo-mechanical modeling of additive manufacturing processes. In: Thermo-Mechanical Model. Addit. Manuf. Elsevier, pp 19\u201338","DOI":"10.1016\/B978-0-12-811820-7.00003-3"},{"key":"10332_CR38","doi-asserted-by":"publisher","DOI":"10.1016\/j.addma.2020.101531","volume":"36","author":"N Peter","year":"2020","unstructured":"Peter N, Pitts Z, Thompson S, Saharan A (2020) Benchmarking build simulation software for laser powder bed fusion of metals. Addit Manuf 36:101531. https:\/\/doi.org\/10.1016\/j.addma.2020.101531","journal-title":"Addit Manuf"},{"key":"10332_CR39","doi-asserted-by":"publisher","DOI":"10.1016\/j.addma.2019.06.022","volume":"29","author":"M Gouge","year":"2019","unstructured":"Gouge M, Denlinger E, Irwin J, Li C, Michaleris P (2019) Experimental validation of thermo-mechanical part-scale modeling for laser powder bed fusion processes. Addit Manuf 29:100771. https:\/\/doi.org\/10.1016\/j.addma.2019.06.022","journal-title":"Addit Manuf"},{"key":"10332_CR40","doi-asserted-by":"publisher","first-page":"299","DOI":"10.1007\/BF02667333","volume":"15","author":"J Goldak","year":"1984","unstructured":"Goldak J, Chakravarti A, Bibby M (1984) A new finite element model for welding heat sources. Metall Trans B 15:299\u2013305. https:\/\/doi.org\/10.1007\/BF02667333","journal-title":"Metall Trans B"},{"key":"10332_CR41","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1016\/j.matdes.2016.10.003","volume":"113","author":"Z Wang","year":"2017","unstructured":"Wang Z, Denlinger E, Michaleris P, Stoica AD, Ma D, Beese AM (2017) Residual stress mapping in Inconel 625 fabricated through additive manufacturing: Method for neutron diffraction measurements to validate thermomechanical model predictions. Mater Des 113:169\u2013177. https:\/\/doi.org\/10.1016\/j.matdes.2016.10.003","journal-title":"Mater Des"},{"key":"10332_CR42","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1016\/j.addma.2016.04.007","volume":"12","author":"AJ Dunbar","year":"2016","unstructured":"Dunbar AJ, Denlinger ER, Heigel J, Michaleris P, Guerrier P, Martukanitz R, Simpson TW (2016) Development of experimental method for in situ distortion and temperature measurements during the laser powder bed fusion additive manufacturing process. Addit Manuf 12:25\u201330. https:\/\/doi.org\/10.1016\/j.addma.2016.04.007","journal-title":"Addit Manuf"},{"key":"10332_CR43","unstructured":"https:\/\/www.paraview.org\/."},{"key":"10332_CR44","doi-asserted-by":"publisher","first-page":"237","DOI":"10.1080\/10407790050192753","volume":"38","author":"HAD JasakGosman","year":"2000","unstructured":"JasakGosman HAD (2000) Automatic resolution control for the finite-volume method, part 1: a-posteriori error estimates. Numer Heat Transf Part B Fundam 38:237\u2013256. https:\/\/doi.org\/10.1080\/10407790050192753","journal-title":"Numer Heat Transf Part B Fundam"},{"key":"10332_CR45","doi-asserted-by":"publisher","first-page":"484","DOI":"10.1016\/0021-9991(84)90073-1","volume":"53","author":"MJ Berger","year":"1984","unstructured":"Berger MJ, Oliger J (1984) Adaptive mesh refinement for hyperbolic partial differential equations. J Comput Phys 53:484\u2013512. https:\/\/doi.org\/10.1016\/0021-9991(84)90073-1","journal-title":"J Comput Phys"},{"key":"10332_CR46","unstructured":"https:\/\/www.solidworks.com\/."},{"key":"10332_CR47","doi-asserted-by":"publisher","first-page":"2995","DOI":"10.1007\/s00170-023-11974-1","volume":"128","author":"AK Ball","year":"2023","unstructured":"Ball AK, Basak A (2023) AI modeling for high-fidelity heat transfer and thermal distortion forecast in metal additive manufacturing. Int J Adv Manuf Technol 128:2995\u20133010. https:\/\/doi.org\/10.1007\/s00170-023-11974-1","journal-title":"Int J Adv Manuf Technol"},{"key":"10332_CR48","doi-asserted-by":"publisher","DOI":"10.1016\/j.jer.2023.09.026","author":"R Raut","year":"2023","unstructured":"Raut R, Ball AK, Basak A (2023) Impact of track length, track shape, and track location on thermal distortion in laser powder bed fusion of IN625: single laser vs. three lasers. J Eng Res. https:\/\/doi.org\/10.1016\/j.jer.2023.09.026","journal-title":"J Eng Res"},{"key":"10332_CR49","doi-asserted-by":"publisher","DOI":"10.1016\/j.cjmeam.2023.100103","volume":"2","author":"AK Ball","year":"2023","unstructured":"Ball AK, Basak A (2023) Numerical investigation of the thermal distortion in multi-laser powder bed fusion (ML-PBF) additive manufacturing of inconel 625. Chin J Mech Eng Addit Manuf Front 2:100103. https:\/\/doi.org\/10.1016\/j.cjmeam.2023.100103","journal-title":"Chin J Mech Eng Addit Manuf Front"},{"key":"10332_CR50","unstructured":"Goldberg DE (2006) Genetic algorithms in search, optimization and machine learning, 1st ed. Pearson Education India"},{"key":"10332_CR51","unstructured":"Sivanandam SN, Deepa SN (2011) Principles of Soft Computing, 2nd ed. Wiley"},{"key":"10332_CR52","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/1090.001.0001","volume-title":"Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence","author":"JH Holland","year":"1992","unstructured":"Holland JH (1992) Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence. MIT Press, Cambridge, Massachusetts, London, England"},{"key":"10332_CR53","doi-asserted-by":"publisher","DOI":"10.1002\/9780470549124","author":"SS Rao","year":"2009","unstructured":"Rao SS (2009) Engineering optimization. Eng Optim Theory Pract Fourth Ed. https:\/\/doi.org\/10.1002\/9780470549124","journal-title":"Eng Optim Theory Pract Fourth Ed"},{"key":"10332_CR54","doi-asserted-by":"publisher","first-page":"26766","DOI":"10.1109\/ACCESS.2021.3056407","volume":"9","author":"P Agrawal","year":"2021","unstructured":"Agrawal P, Abutarboush HF, Ganesh T, Mohamed AW (2021) Metaheuristic algorithms on feature selection: a survey of one decade of research (2009\u20132019). IEEE Access 9:26766\u201326791. https:\/\/doi.org\/10.1109\/ACCESS.2021.3056407","journal-title":"IEEE Access"},{"key":"10332_CR55","unstructured":"Pratihar DK (2013) Soft Computing: Fundamentals and Applications, 1st ed. Alpha Science International Ltd"},{"key":"10332_CR56","doi-asserted-by":"publisher","first-page":"679","DOI":"10.1016\/j.future.2020.08.028","volume":"114","author":"Z Xiao","year":"2021","unstructured":"Xiao Z, Liu X, Xu J, Sun Q, Gan L (2021) Highly scalable parallel genetic algorithm on Sunway many-core processors. Futur Gener Comput Syst 114:679\u2013691. https:\/\/doi.org\/10.1016\/j.future.2020.08.028","journal-title":"Futur Gener Comput Syst"},{"key":"10332_CR57","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1007\/s10710-009-9096-z","volume":"11","author":"JLJ Laredo","year":"2010","unstructured":"Laredo JLJ, Eiben AE, van Steen M, Merelo JJ (2010) EvAg: a scalable peer-to-peer evolutionary algorithm. Genet Program Evolv Mach 11:227\u2013246. https:\/\/doi.org\/10.1007\/s10710-009-9096-z","journal-title":"Genet Program Evolv Mach"},{"key":"10332_CR58","doi-asserted-by":"crossref","unstructured":"Scott SD, Samal A, Seth S (1995) HGA. In: Proc. 1995 ACM third Int. Symp. Field-programmable gate arrays. ACM, New York, NY, USA, pp 53\u201359","DOI":"10.1145\/201310.201319"},{"key":"10332_CR59","doi-asserted-by":"publisher","first-page":"5923","DOI":"10.1007\/s00500-017-2810-5","volume":"22","author":"X-S Yang","year":"2018","unstructured":"Yang X-S, Deb S, Zhao Y-X, Fong S, He X (2018) Swarm intelligence: past, present and future. Soft Comput 22:5923\u20135933. https:\/\/doi.org\/10.1007\/s00500-017-2810-5","journal-title":"Soft Comput"},{"key":"10332_CR60","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2020.106438","volume":"94","author":"AK Ball","year":"2020","unstructured":"Ball AK, Roy SS, Kisku DR, Murmu NC, dos Coelho LS (2020) Optimization of drop ejection frequency in EHD inkjet printing system using an improved firefly algorithm. Appl Soft Comput 94:106438. https:\/\/doi.org\/10.1016\/j.asoc.2020.106438","journal-title":"Appl Soft Comput"},{"key":"10332_CR61","doi-asserted-by":"publisher","first-page":"571","DOI":"10.1007\/s00500-019-04202-0","volume":"24","author":"AK Ball","year":"2020","unstructured":"Ball AK, Das R, Roy SS, Kisku DR, Murmu NC (2020) Modeling of EHD inkjet printing performance using soft computing-based approaches. Soft Comput 24:571\u2013589. https:\/\/doi.org\/10.1007\/s00500-019-04202-0","journal-title":"Soft Comput"},{"key":"10332_CR62","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1109\/TEVC.2016.2634625","volume":"22","author":"D Gong","year":"2018","unstructured":"Gong D, Sun J, Miao Z (2018) A set-based genetic algorithm for interval many-objective optimization problems. IEEE Trans Evol Comput 22:47\u201360. https:\/\/doi.org\/10.1109\/TEVC.2016.2634625","journal-title":"IEEE Trans Evol Comput"},{"key":"10332_CR63","doi-asserted-by":"publisher","first-page":"360","DOI":"10.1016\/j.commatsci.2016.10.003","volume":"126","author":"T Mukherjee","year":"2017","unstructured":"Mukherjee T, Zhang W, DebRoy T (2017) An improved prediction of residual stresses and distortion in additive manufacturing. Comput Mater Sci 126:360\u2013372. https:\/\/doi.org\/10.1016\/j.commatsci.2016.10.003","journal-title":"Comput Mater Sci"},{"key":"10332_CR64","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0162259","volume":"11","author":"YP Raykov","year":"2016","unstructured":"Raykov YP, Boukouvalas A, Baig F, Little MA (2016) What to do when K-means clustering fails: a simple yet principled alternative algorithm. PLoS ONE 11:e0162259. https:\/\/doi.org\/10.1371\/journal.pone.0162259","journal-title":"PLoS ONE"},{"key":"10332_CR65","doi-asserted-by":"publisher","DOI":"10.1016\/j.addma.2022.102708","volume":"54","author":"C Bayraktar","year":"2022","unstructured":"Bayraktar C, Demir E (2022) A thermomechanical finite element model and its comparison to inherent strain method for powder-bed fusion process. Addit Manuf 54:102708. https:\/\/doi.org\/10.1016\/j.addma.2022.102708","journal-title":"Addit Manuf"},{"key":"10332_CR66","doi-asserted-by":"publisher","DOI":"10.1016\/j.addma.2020.101585","volume":"36","author":"S Feng","year":"2020","unstructured":"Feng S, Chen S, Kamat AM, Zhang R, Huang M, Hu L (2020) Investigation on shape deviation of horizontal interior circular channels fabricated by laser powder bed fusion. Addit Manuf 36:101585. https:\/\/doi.org\/10.1016\/j.addma.2020.101585","journal-title":"Addit Manuf"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-024-10332-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-024-10332-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-024-10332-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,23]],"date-time":"2024-11-23T09:09:17Z","timestamp":1732352957000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-024-10332-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,14]]},"references-count":66,"journal-issue":{"issue":"34","published-print":{"date-parts":[[2024,12]]}},"alternative-id":["10332"],"URL":"https:\/\/doi.org\/10.1007\/s00521-024-10332-w","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,9,14]]},"assertion":[{"value":"15 March 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 July 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 September 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}