{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T17:03:30Z","timestamp":1776877410935,"version":"3.51.2"},"publisher-location":"Cham","reference-count":12,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030038397","type":"print"},{"value":"9783030038403","type":"electronic"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-030-03840-3_35","type":"book-chapter","created":{"date-parts":[[2018,11,8]],"date-time":"2018-11-08T06:28:57Z","timestamp":1541658537000},"page":"474-486","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Energy-Aware Multiple State Machine Scheduling for Multiobjective Optimization"],"prefix":"10.1007","author":[{"given":"Angelo","family":"Oddi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Riccardo","family":"Rasconi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Miguel A.","family":"Gonz\u00e1lez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,11,9]]},"reference":[{"key":"35_CR1","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511615320","volume-title":"Principles of Constraint Programming","author":"K Apt","year":"2003","unstructured":"Apt, K.: Principles of Constraint Programming. Cambridge University Press, New York (2003)"},{"key":"35_CR2","volume-title":"Introduction to Sequencing and Scheduling","author":"K Baker","year":"1974","unstructured":"Baker, K.: Introduction to Sequencing and Scheduling. Wiley, London (1974)"},{"key":"35_CR3","first-page":"225","volume-title":"Industrial Scheduling","author":"H Fisher","year":"1963","unstructured":"Fisher, H., Thomson, G.L.: Probabilistic learning combinations of local job-shop scheduling rules. In: Muth, J.F., Thomson, G.L. (eds.) Industrial Scheduling, pp. 225\u2013251. Prentice Hall, Englewood Cliffs (1963)"},{"key":"35_CR4","doi-asserted-by":"crossref","unstructured":"Gonz\u00e1lez, M.A., Oddi, A., Rasconi, R.: Multi-objective optimization in a job shop with energy costs through hybrid evolutionary techniques. In: Proceedings of the Twenty-Seventh International Conference on Automated Planning and Scheduling (ICAPS-2017), pp. 140\u2013148. AAAI Press, Pittsburgh (2017)","DOI":"10.1609\/icaps.v27i1.13809"},{"issue":"2","key":"35_CR5","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1016\/S0004-3702(02)00362-4","volume":"143","author":"P Laborie","year":"2003","unstructured":"Laborie, P.: Algorithms for propagating resource constraints in AI planning and scheduling: existing approaches and new results. Artif. Intell. 143(2), 151\u2013188 (2003)","journal-title":"Artif. Intell."},{"key":"35_CR6","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4615-1479-4","volume-title":"Constraint-Based Scheduling: Applying Constraint Programming to Scheduling Problems","author":"C Pape Le","year":"2001","unstructured":"Le Pape, C., Baptiste, P., Nuijten, W.: Constraint-Based Scheduling: Applying Constraint Programming to Scheduling Problems. Springer, New York (2001). https:\/\/doi.org\/10.1007\/978-1-4615-1479-4"},{"key":"35_CR7","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1016\/j.jclepro.2013.07.060","volume":"65","author":"Y Liu","year":"2014","unstructured":"Liu, Y., Dong, H., Lohse, N., Petrovic, S., Gindy, N.: An investigation into minimising total energy consumption and total weighted tardiness in job shops. J. Clean. Prod. 65, 87\u201396 (2014)","journal-title":"J. Clean. Prod."},{"issue":"23","key":"35_CR8","doi-asserted-by":"publisher","first-page":"7071","DOI":"10.1080\/00207543.2015.1005248","volume":"53","author":"G May","year":"2015","unstructured":"May, G., Stahl, B., Taisch, M., Prabhu, V.: Multi-objective genetic algorithm for energy-efficient job shop scheduling. Int. J. Prod. Res. 53(23), 7071\u20137089 (2015)","journal-title":"Int. J. Prod. Res."},{"key":"35_CR9","series-title":"International Series in Operations Research & Management Science","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4615-5563-6","volume-title":"Nonlinear Multiobjective Optimization","author":"K Miettinen","year":"2012","unstructured":"Miettinen, K.: Nonlinear Multiobjective Optimization. International Series in Operations Research & Management Science. Springer, New York (2012). https:\/\/doi.org\/10.1007\/978-1-4615-5563-6 . https:\/\/books.google.it\/books?id=bnzjBwAAQBAJ"},{"key":"35_CR10","unstructured":"Oddi, A., Rasconi, R., Gonz\u00e1lez, M.: A constraint programming approach for the energy-efficient job shop scheduling problem. In: Gunawan, A., Kendall, G., Soon, L., McCollum, B., Seow, H.V. (eds.) Proceedings of the 8th Multidisciplinary International Conference on Scheduling : Theory and Applications (MISTA 2017), 05\u201308 December 2017, Kuala Lumpur, Malaysia, pp. 158\u2013172 (2017)"},{"key":"35_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1007\/978-3-540-30201-8_8","volume-title":"Principles and Practice of Constraint Programming \u2013 CP 2004","author":"P Vil\u00edm","year":"2004","unstructured":"Vil\u00edm, P., Bart\u00e1k, R., \u010cepek, O.: Unary resource constraint with optional activities. In: Wallace, M. (ed.) CP 2004. LNCS, vol. 3258, pp. 62\u201376. Springer, Heidelberg (2004). https:\/\/doi.org\/10.1007\/978-3-540-30201-8_8"},{"key":"35_CR12","doi-asserted-by":"publisher","first-page":"3361","DOI":"10.1016\/j.jclepro.2015.09.097","volume":"112","author":"R Zhang","year":"2016","unstructured":"Zhang, R., Chiong, R.: Solving the energy-efficient job shop scheduling problem: a multi-objective genetic algorithm with enhanced local search for minimizing the total weighted tardiness and total energy consumption. J. Clean. Prod. 112, 3361\u20133375 (2016)","journal-title":"J. Clean. Prod."}],"container-title":["Lecture Notes in Computer Science","AI*IA 2018 \u2013 Advances in Artificial Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-03840-3_35","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,6]],"date-time":"2023-09-06T21:54:54Z","timestamp":1694037294000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-03840-3_35"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030038397","9783030038403"],"references-count":12,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-03840-3_35","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"AI*IA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference of the Italian Association for Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Trento","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 November 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 November 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aiia2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/aixia2018.fbk.eu\/index.php\/home\/","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"}},{"value":"Easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"210","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"41","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"20% - 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"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"2,5","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}}]}}