{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,27]],"date-time":"2025-08-27T16:02:53Z","timestamp":1756310573896,"version":"3.40.3"},"publisher-location":"Cham","reference-count":14,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030916077"},{"type":"electronic","value":"9783030916084"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-91608-4_37","type":"book-chapter","created":{"date-parts":[[2021,11,23]],"date-time":"2021-11-23T20:05:55Z","timestamp":1637697955000},"page":"378-386","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["An Intelligent Decision Support System for Production Planning in Garments Industry"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8078-4148","authenticated-orcid":false,"given":"Rui","family":"Ribeiro","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4380-3220","authenticated-orcid":false,"given":"Andr\u00e9","family":"Pilastri","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3631-1487","authenticated-orcid":false,"given":"Hugo","family":"Carvalho","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4902-9483","authenticated-orcid":false,"given":"Arthur","family":"Matta","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6169-8778","authenticated-orcid":false,"given":"Pedro Jos\u00e9","family":"Pereira","sequence":"additional","affiliation":[]},{"given":"Pedro","family":"Rocha","sequence":"additional","affiliation":[]},{"given":"Marcelo","family":"Alves","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7991-2090","authenticated-orcid":false,"given":"Paulo","family":"Cortez","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,11,23]]},"reference":[{"key":"37_CR1","doi-asserted-by":"publisher","unstructured":"\u00c1ngeles Solari, M.D.L., Ocampo, E.: Application of genetic algorithms to a manufacturing industry scheduling multi-agent system. In: Sobh, T., Elleithy, K., Mahmood, A., Karim, M. (eds.) Innovative Algorithms and Techniques in Automation, Industrial Electronics and Telecommunications, pp. 263\u2013268. Springer, Dordrecht (2007). https:\/\/doi.org\/10.1007\/978-1-4020-6266-7_48","DOI":"10.1007\/978-1-4020-6266-7_48"},{"issue":"4","key":"37_CR2","doi-asserted-by":"publisher","first-page":"269","DOI":"10.1057\/jit.2014.16","volume":"29","author":"D Arnott","year":"2014","unstructured":"Arnott, D., Pervan, G.: A critical analysis of decision support systems research revisited: the rise of design science. J. Inf. Technol. 29(4), 269\u2013293 (2014). https:\/\/doi.org\/10.1057\/jit.2014.16","journal-title":"J. Inf. Technol."},{"key":"37_CR3","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1016\/j.ijpe.2019.05.003","volume":"218","author":"O Ben-Ammar","year":"2019","unstructured":"Ben-Ammar, O., Bettayeb, B., Dolgui, A.: Optimization of multi-period supply planning under stochastic lead times and a dynamic demand. Int. J. Prod. Econ. 218, 106\u2013117 (2019). https:\/\/doi.org\/10.1016\/j.ijpe.2019.05.003","journal-title":"Int. J. Prod. Econ."},{"key":"37_CR4","doi-asserted-by":"publisher","first-page":"89497","DOI":"10.1109\/ACCESS.2020.2990567","volume":"8","author":"J Blank","year":"2020","unstructured":"Blank, J., Deb, K.: Pymoo: multi-objective optimization in python. IEEE Access 8, 89497\u201389509 (2020). https:\/\/doi.org\/10.1109\/ACCESS.2020.2990567","journal-title":"IEEE Access"},{"issue":"12","key":"37_CR5","doi-asserted-by":"publisher","first-page":"1272","DOI":"10.1016\/j.ifacol.2016.07.690","volume":"49","author":"G Campos Ciro","year":"2016","unstructured":"Campos Ciro, G., Dugardin, F., Yalaoui, F., Kelly, R.: A nsga-ii and nsga-iii comparison for solving an open shop scheduling problem with resource constraints. IFAC-PapersOnLine 49(12), 1272\u20131277 (2016). https:\/\/doi.org\/10.1016\/j.ifacol.2016.07.690","journal-title":"IFAC-PapersOnLine"},{"issue":"5","key":"37_CR6","doi-asserted-by":"publisher","first-page":"912","DOI":"10.1016\/j.camwa.2011.11.057","volume":"63","author":"G Chiandussi","year":"2012","unstructured":"Chiandussi, G., Codegone, M., Ferrero, S., Varesio, F.: Comparison of multi-objective optimization methodologies for engineering applications. Comput. Math. Appl 63(5), 912\u2013942 (2012). https:\/\/doi.org\/10.1016\/j.camwa.2011.11.057","journal-title":"Comput. Math. Appl"},{"key":"37_CR7","series-title":"Use R!","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-72819-9","volume-title":"Modern Optimization with R","author":"P Cortez","year":"2021","unstructured":"Cortez, P.: Modern Optimization with R. UR, Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-72819-9"},{"issue":"2","key":"37_CR8","doi-asserted-by":"publisher","first-page":"182","DOI":"10.1109\/4235.996017","volume":"6","author":"K Deb","year":"2002","unstructured":"Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multiobjective genetic algorithm: Nsga-ii. IEEE Trans. Evol. Comput. 6(2), 182\u2013197 (2002). https:\/\/doi.org\/10.1109\/4235.996017","journal-title":"IEEE Trans. Evol. Comput."},{"key":"37_CR9","doi-asserted-by":"crossref","unstructured":"Ferreira, L., Pilastri, A., Martins, C.M., Pires, P.M., Cortez, P.: A comparison of AutoML tools for machine learning, deep learning and XGBoost. In: International Joint Conference on Neural Networks, IJCNN 2021. IEEE (2021)","DOI":"10.1109\/IJCNN52387.2021.9534091"},{"issue":"4","key":"37_CR10","doi-asserted-by":"publisher","first-page":"972","DOI":"10.1016\/j.cie.2013.01.006","volume":"64","author":"Z Guo","year":"2013","unstructured":"Guo, Z., Wong, W., Li, Z., Ren, P.: Modeling and pareto optimization of multi-objective order scheduling problems in production planning. Comput. Ind. Eng. 64(4), 972\u2013986 (2013). https:\/\/doi.org\/10.1016\/j.cie.2013.01.006","journal-title":"Comput. Ind. Eng."},{"key":"37_CR11","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-32929-9","volume-title":"Adaptive Business Intelligence","author":"Z Michalewicz","year":"2006","unstructured":"Michalewicz, Z., Schmidt, M., Michalewicz, M., Chiriac, C.: Adaptive Business Intelligence. Springer, Heidelberg (2006). https:\/\/doi.org\/10.1007\/978-3-540-32929-9"},{"issue":"1","key":"37_CR12","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1007\/s10845-011-0548-y","volume":"24","author":"PY Mok","year":"2013","unstructured":"Mok, P.Y., Cheung, T.Y., Wong, W.K., Leung, S.Y., Fan, J.T.: Intelligent production planning for complex garment manufacturing. J. Intell. Manuf. 24(1), 133\u2013145 (2013). https:\/\/doi.org\/10.1007\/s10845-011-0548-y","journal-title":"J. Intell. Manuf."},{"key":"37_CR13","doi-asserted-by":"publisher","first-page":"339","DOI":"10.1016\/j.compchemeng.2017.05.004","volume":"104","author":"H Mokhtari","year":"2017","unstructured":"Mokhtari, H., Hasani, A.: An energy-efficient multi-objective optimization for flexible job-shop scheduling problem. Comput. Chem. Eng. 104, 339\u2013352 (2017). https:\/\/doi.org\/10.1016\/j.compchemeng.2017.05.004","journal-title":"Comput. Chem. Eng."},{"issue":"8","key":"37_CR14","doi-asserted-by":"publisher","first-page":"2072","DOI":"10.3390\/en11082072","volume":"11","author":"WH Tsai","year":"2018","unstructured":"Tsai, W.H.: Green production planning and control for the textile industry by using mathematical programming and industry 4.0 techniques. Energies 11(8), 2072 (2018). https:\/\/doi.org\/10.3390\/en11082072","journal-title":"Energies"}],"container-title":["Lecture Notes in Computer Science","Intelligent Data Engineering and Automated Learning \u2013 IDEAL 2021"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-91608-4_37","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T15:53:24Z","timestamp":1710258804000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-91608-4_37"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030916077","9783030916084"],"references-count":14,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-91608-4_37","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"23 November 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IDEAL","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Data Engineering and Automated Learning","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Manchester","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 November 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 November 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ideal2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ideal-conf.com\/ideal2021","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"85","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"61","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"72% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2.8","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2.3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"The conference took place virtually due to the COVID-19 pandemic","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}