{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T23:17:02Z","timestamp":1743031022957,"version":"3.40.3"},"publisher-location":"Cham","reference-count":23,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030539559"},{"type":"electronic","value":"9783030539566"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","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":[[2020]]},"DOI":"10.1007\/978-3-030-53956-6_28","type":"book-chapter","created":{"date-parts":[[2020,7,12]],"date-time":"2020-07-12T11:02:42Z","timestamp":1594551762000},"page":"312-324","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["An Improved Bacterial Foraging Optimization with Differential and Poisson Distribution Strategy and its Application to Nurse Scheduling Problem"],"prefix":"10.1007","author":[{"given":"Jingzhou","family":"Jiang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaojun","family":"Xiong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yikun","family":"Ou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hong","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,7,13]]},"reference":[{"issue":"3","key":"28_CR1","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1109\/MCS.2002.1004010","volume":"22","author":"KM Passino","year":"2002","unstructured":"Passino, K.M.: Biomimicry of bacterial foraging for distributed optimization and control. IEEE Control Syst. Mag. 22(3), 52\u201367 (2002)","journal-title":"IEEE Control Syst. Mag."},{"issue":"3","key":"28_CR2","doi-asserted-by":"publisher","first-page":"1311","DOI":"10.1109\/TPWRS.2011.2175455","volume":"27","author":"N Amjady","year":"2012","unstructured":"Amjady, N., Fatemi, H., Zareipour, H.: Solution of optimal power flow subject to security constraints by a new improved bacterial foraging method. IEEE Trans. Power Syst. 27(3), 1311\u20131323 (2012)","journal-title":"IEEE Trans. Power Syst."},{"issue":"4","key":"28_CR3","doi-asserted-by":"publisher","first-page":"210","DOI":"10.1016\/j.sbspro.2012.04.093","volume":"43","author":"Q Liu","year":"2012","unstructured":"Liu, Q., Xu, J.: Traffic signal timing optimization for isolated intersections based on differential evolution bacteria foraging algorithm. Procedia-Soc. Behav. Sci. 43(4), 210\u2013215 (2012)","journal-title":"Procedia-Soc. Behav. Sci."},{"issue":"1","key":"28_CR4","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1109\/TEVC.2004.840144","volume":"9","author":"S Mishra","year":"2005","unstructured":"Mishra, S.: A hybrid least square-fuzzy bacterial foraging strategy for harmonic estimation. IEEE Trans. Evol. Comput. 9(1), 61\u201373 (2005)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"28_CR5","doi-asserted-by":"crossref","unstructured":"Niu, B., Wang, H., Tan, L., Li, L.: Improved BFO with adaptive chemotaxis step for global optimization. In: 2011 Seventh International Conference on Computational Intelligence and Security, pp. 76\u201380. IEEE (2011)","DOI":"10.1109\/CIS.2011.25"},{"issue":"6","key":"28_CR6","doi-asserted-by":"publisher","first-page":"10097","DOI":"10.1016\/j.eswa.2009.01.012","volume":"36","author":"R Majhi","year":"2009","unstructured":"Majhi, R., Panda, G., Majhi, B., Sahoo, G.: Efficient prediction of stock market indices using adaptive bacterial foraging optimization (ABFO) and BFO based techniques. Expert Syst. Appl. 36(6), 10097\u201310104 (2009)","journal-title":"Expert Syst. Appl."},{"issue":"1","key":"28_CR7","doi-asserted-by":"publisher","first-page":"214","DOI":"10.1007\/s10489-016-0832-9","volume":"46","author":"K Tang","year":"2016","unstructured":"Tang, K., Xiao, X., Wu, J., Yang, J., Luo, L.: An improved multilevel thresholding approach based modified bacterial foraging optimization. Appl. Intell. 46(1), 214\u2013226 (2016). https:\/\/doi.org\/10.1007\/s10489-016-0832-9","journal-title":"Appl. Intell."},{"issue":"7","key":"28_CR8","doi-asserted-by":"publisher","first-page":"2743","DOI":"10.1007\/s10845-018-1420-0","volume":"30","author":"M Raju","year":"2019","unstructured":"Raju, M., Gupta, M.K., Bhanot, N., Sharma, V.S.: A hybrid PSO-BFO evolutionary algorithm for optimization of fused deposition modelling process parameters. J. Intell. Manuf. 30(7), 2743\u20132758 (2019)","journal-title":"J. Intell. Manuf."},{"issue":"5","key":"28_CR9","first-page":"624","volume":"4","author":"DH Kim","year":"2006","unstructured":"Kim, D.H., Cho, J.H.: A biologically inspired intelligent PID controller tuning for AVR systems. Int. J. Control Autom. Syst. 4(5), 624\u2013636 (2006)","journal-title":"Int. J. Control Autom. Syst."},{"issue":"2","key":"28_CR10","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1057\/palgrave.jors.2602534","volume":"60","author":"G Zobolas","year":"2009","unstructured":"Zobolas, G., Tarantilis, C.D., Ioannou, G.: A hybrid evolutionary algorithm for the job shop scheduling problem. J. Oper. Res. Soc. 60(2), 221\u2013235 (2009)","journal-title":"J. Oper. Res. Soc."},{"key":"28_CR11","series-title":"Advances in Soft Computing","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1007\/978-3-540-74972-1_34","volume-title":"Innovations in Hybrid Intelligent Systems","author":"A Biswas","year":"2007","unstructured":"Biswas, A., Dasgupta, S., Das, S., Abraham, A.: Synergy of PSO and bacterial foraging optimization\u2014a comparative study on numerical benchmarks. In: Corchado, E., Corchado, J.M., Abraham, A. (eds.) Innovations in Hybrid Intelligent Systems. AINSC, vol. 44, pp. 255\u2013263. Springer, Heidelberg (2007). https:\/\/doi.org\/10.1007\/978-3-540-74972-1_34"},{"issue":"1","key":"28_CR12","first-page":"88","volume":"16","author":"A Goli","year":"2018","unstructured":"Goli, A., Aazami, A., Jabbarzadeh, A.: Accelerated cuckoo optimization algorithm for capacitated vehicle routing problem in competitive conditions. Int. J. Artif. Intell. 16(1), 88\u2013112 (2018)","journal-title":"Int. J. Artif. Intell."},{"issue":"5","key":"28_CR13","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1016\/j.ifacol.2016.07.089","volume":"49","author":"RE Precup","year":"2016","unstructured":"Precup, R.E., David, R.C., Petriu, E.M., Szedlak-Stinean, A.I., Bojan-Dragos, C.A.: Grey wolf optimizer-based approach to the tuning of pi-fuzzy controllers with a reduced process parametric sensitivity. IFAC-PapersOnline 49(5), 55\u201360 (2016)","journal-title":"IFAC-PapersOnline"},{"issue":"5","key":"28_CR14","doi-asserted-by":"publisher","first-page":"761","DOI":"10.1016\/S0305-0548(03)00034-0","volume":"31","author":"U Aickelin","year":"2004","unstructured":"Aickelin, U., Dowsland, K.A.: An indirect genetic algorithm for a nurse-scheduling problem. Comput. Oper. Res. 31(5), 761\u2013778 (2004)","journal-title":"Comput. Oper. Res."},{"key":"28_CR15","unstructured":"Tong, Y.L.: Bacteria foraging optimization algorithm based on self-adaptative method. Value Eng. (2015)"},{"issue":"12","key":"28_CR16","first-page":"15332","volume":"38","author":"SP Chatzis","year":"2011","unstructured":"Chatzis, S.P., Koukas, S.: Numerical optimization using synergetic swarms of foraging bacterial populations. Expert Syst. Appl. 38(12), 15332\u201315343 (2011)","journal-title":"Expert Syst. Appl."},{"key":"28_CR17","unstructured":"Dasgupta, S.: Analysis of a greedy active learning strategy. In: Advances in Neural Information Processing Systems, pp. 337\u2013344 (2005)"},{"issue":"4","key":"28_CR18","doi-asserted-by":"publisher","first-page":"3341","DOI":"10.1016\/j.aej.2017.12.010","volume":"57","author":"MA Sahib","year":"2018","unstructured":"Sahib, M.A., Abdulnabi, A.R., Mohammed, M.A.: Improving bacterial foraging algorithm using non-uniform elimination-dispersal probability distribution. Alexandria Eng. J. 57(4), 3341\u20133349 (2018)","journal-title":"Alexandria Eng. J."},{"issue":"2","key":"28_CR19","first-page":"338","volume":"33","author":"W Chao","year":"2013","unstructured":"Chao, W., Dong, X.: Variable neighborhood search algorithm for nurse rostering problem. J. Comput. Appl. 33(2), 338\u2013341 (2013)","journal-title":"J. Comput. Appl."},{"issue":"1\u20133","key":"28_CR20","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1016\/0004-3702(89)90050-7","volume":"40","author":"LB Booker","year":"1989","unstructured":"Booker, L.B., Goldberg, D.E., Holland, J.H.: Classifier systems and genetic algorithms. Artif. Intell. 40(1\u20133), 235\u2013282 (1989)","journal-title":"Artif. Intell."},{"key":"28_CR21","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1007\/978-3-319-93815-8_33","volume-title":"Advances in Swarm Intelligence","author":"X Yan","year":"2018","unstructured":"Yan, X., Niu, B.: Hydrologic cycle optimization part i: background and theory. In: Tan, Y., Shi, Y., Tang, Q. (eds.) ICSI 2018. LNCS, vol. 10941, pp. 341\u2013349. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-93815-8_33"},{"key":"28_CR22","doi-asserted-by":"crossref","unstructured":"Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proceedings of ICNN 1995-International Conference on Neural Networks, vol. 4, pp. 1942\u20131948. IEEE (1995)","DOI":"10.1109\/ICNN.1995.488968"},{"key":"28_CR23","unstructured":"Surjanovic, S., Bingham, D.: Virtual library of simulation experiments: test functions and datasets. http:\/\/www.sfu.ca\/~ssurjano. Accessed 20 Feb 2020"}],"container-title":["Lecture Notes in Computer Science","Advances in Swarm Intelligence"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-53956-6_28","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,9]],"date-time":"2024-08-09T23:03:57Z","timestamp":1723244637000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-53956-6_28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030539559","9783030539566"],"references-count":23,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-53956-6_28","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"13 July 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICSI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Swarm Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Belgrade","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Serbia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 July 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 July 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"swarm2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-si.org\/committees\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Confy","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"127","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":"63","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":"50% - 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","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":"2.4","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":"No","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 was held 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)"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}