{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,1,4]],"date-time":"2025-01-04T03:40:26Z","timestamp":1735962026528,"version":"3.32.0"},"reference-count":17,"publisher":"Institute of Electronics, Information and Communications Engineers (IEICE)","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEICE Trans. Inf. & Syst."],"published-print":{"date-parts":[[2025,1,1]]},"DOI":"10.1587\/transinf.2024pap0007","type":"journal-article","created":{"date-parts":[[2024,7,10]],"date-time":"2024-07-10T22:12:23Z","timestamp":1720649543000},"page":"12-22","source":"Crossref","is-referenced-by-count":0,"title":["A Flip-Count-Based Dynamic Temperature Control Method for Constrained Combinatorial Optimization by Parallel Annealing Algorithms"],"prefix":"10.1587","volume":"E108.D","author":[{"given":"Genta","family":"INOUE","sequence":"first","affiliation":[{"name":"Tokyo Institute of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daiki","family":"OKONOGI","sequence":"additional","affiliation":[{"name":"Tokyo Institute of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Satoru","family":"JIMBO","sequence":"additional","affiliation":[{"name":"Tokyo Institute of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thiem Van","family":"CHU","sequence":"additional","affiliation":[{"name":"Tokyo Institute of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Masato","family":"MOTOMURA","sequence":"additional","affiliation":[{"name":"Tokyo Institute of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kazushi","family":"KAWAMURA","sequence":"additional","affiliation":[{"name":"Tokyo Institute of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"532","reference":[{"key":"1","doi-asserted-by":"publisher","unstructured":"[1] N. Mohseni, P.L. McMahon, and T. Byrnes, \u201cIsing machines as hardware solvers of combinatorial optimization problems,\u201d Nature Reviews Physics, vol.4, no.6, pp.363-379, June 2022. 10.1038\/s42254-022-00440-8","DOI":"10.1038\/s42254-022-00440-8"},{"key":"2","doi-asserted-by":"publisher","unstructured":"[2] L. Wei, Z. Zhang, D. Zhang, and S.C.H. Leung, \u201cA simulated annealing algorithm for the capacitated vehicle routing problem with two-dimensional loading constraints,\u201d European Journal of Operational Research, vol.265, no.3, pp.843-859, 2018. 10.1016\/j.ejor.2017.08.035","DOI":"10.1016\/j.ejor.2017.08.035"},{"key":"3","doi-asserted-by":"publisher","unstructured":"[3] A.M. Fathollahi-Fard, K. Govindan, M. Hajiaghaei-Keshteli, and A. Ahmadi, \u201cA green home health care supply chain: New modified simulated annealing algorithms,\u201d Journal of Cleaner Production, vol.240, 118200, 2019. 10.1016\/j.jclepro.2019.118200","DOI":"10.1016\/j.jclepro.2019.118200"},{"key":"4","doi-asserted-by":"publisher","unstructured":"[4] W. Zhang, A. Maleki, M.A. Rosen, and J. Liu, \u201cOptimization with a simulated annealing algorithm of a hybrid system for renewable energy including battery and hydrogen storage,\u201d Energy, vol.163, pp.191-207, 2018. 10.1016\/j.energy.2018.08.112","DOI":"10.1016\/j.energy.2018.08.112"},{"key":"5","doi-asserted-by":"publisher","unstructured":"[5] M.C. Aguitoni, L.V. Pav\u00e3o, and M. Antonio da Silva S\u00e1 Ravagnani, \u201cHeat exchanger network synthesis combining simulated annealing and differential evolution,\u201d Energy, vol.181, pp.654-664, 2019. 10.1016\/j.energy.2019.05.211","DOI":"10.1016\/j.energy.2019.05.211"},{"key":"6","doi-asserted-by":"publisher","unstructured":"[6] R.K. Nath, H. Thapliyal, and T.S. Humble, \u201cA review of machine learning classification using quantum annealing for real-world applications,\u201d SN Computer Science, vol.2, no.5, 365, July 2021. 10.1007\/s42979-021-00751-0","DOI":"10.1007\/s42979-021-00751-0"},{"key":"7","doi-asserted-by":"publisher","unstructured":"[7] H. Asaoka and K. Kudo, \u201cNonnegative\/binary matrix factorization for image classification using quantum annealing,\u201d Scientific Reports, vol.13, no.1, 16527, Oct. 2023. 10.1038\/s41598-023-43729-z","DOI":"10.1038\/s41598-023-43729-z"},{"key":"8","doi-asserted-by":"publisher","unstructured":"[8] A. Lucas, \u201cIsing formulations of many NP problems,\u201d Frontiers in Physics, vol.2, 5, 2014. 10.3389\/fphy.2014.00005","DOI":"10.3389\/fphy.2014.00005"},{"key":"9","doi-asserted-by":"publisher","unstructured":"[9] H. Goto, K. Endo, M. Suzuki, Y. Sakai, T. Kanao, Y. Hamakawa, R. Hidaka, M. Yamasaki, and K. Tatsumura, \u201cHigh-performance combinatorial optimization based on classical mechanics,\u201d Science Advances, vol.7, no.6, eabe7953, 2021. 10.1126\/sciadv.abe7953","DOI":"10.1126\/sciadv.abe7953"},{"key":"10","doi-asserted-by":"crossref","unstructured":"[10] K. Yamamoto, K. Ando, N. Mertig, T. Takemoto, M. Yamaoka, H. Teramoto, A. Sakai, S. Takamaeda-Yamazaki, and M. Motomura, \u201cSTATICA: A 512-spin 0.25M-weight full-digital annealing processor with a near-memory all-spin-updates-at-once architecture for combinatorial optimization with complete spin-spin interactions,\u201d 2020 IEEE International Solid-State Circuits Conference (ISSCC), pp.138-140, 2020. 10.1109\/isscc19947.2020.9062965","DOI":"10.1109\/ISSCC19947.2020.9062965"},{"key":"11","doi-asserted-by":"publisher","unstructured":"[11] T. Okuyama, T. Sonobe, K.-I. Kawarabayashi, and M. Yamaoka, \u201cBinary optimization by momentum annealing,\u201d Phys. Rev. E, vol.100, 012111, July 2019. 10.1103\/physreve.100.012111","DOI":"10.1103\/PhysRevE.100.012111"},{"key":"12","doi-asserted-by":"crossref","unstructured":"[12] K. Kawamura, J. Yu, D. Okonogi, S. Jimbo, G. Inoue, A. Hyodo, \u00c1.L\u00f3. Garc\u00eda-Arias, K. Ando, B.H. Fukushima-Kimura, R. Yasudo, T. Van Chu, and M. Motomura, \u201cAmorphica: 4-replica 512 fully connected spin 336MHz metamorphic annealer with programmable optimization strategy and compressed-spin-transfer multi-chip extension,\u201d 2023 IEEE International Solid-State Circuits Conference (ISSCC), pp.42-44, 2023. 10.1109\/isscc42615.2023.10067504","DOI":"10.1109\/ISSCC42615.2023.10067504"},{"key":"13","doi-asserted-by":"crossref","unstructured":"[13] S. Patel, L. Chen, P. Canoza, and S. Salahuddin, \u201cIsing model optimization problems on a FPGA accelerated restricted Boltzmann machine,\u201d 2020. 10.21203\/rs.3.rs-122016\/v1","DOI":"10.21203\/rs.3.rs-122016\/v1"},{"key":"14","doi-asserted-by":"crossref","unstructured":"[14] Q. Tao and J. Han, \u201cSolving traveling salesman problems via a parallel fully connected Ising machine,\u201d Proc. 59th ACM\/IEEE Design Automation Conference, DAC\u2006\u201922, pp.1123-1128, 2022. 10.1145\/3489517.3530595","DOI":"10.1145\/3489517.3530595"},{"key":"15","doi-asserted-by":"crossref","unstructured":"[15] M. Ayodele, R. Allmendinger, M. L\u00f3pez-Ib\u00e1\u00f1ez, and M. Parizy, \u201cMulti-objective QUBO solver: Bi-objective quadratic assignment problem,\u201d Proc. Genetic and Evolutionary Computation Conference, GECCO\u2006\u201922, pp.467-475, 2022. 10.1145\/3512290.3528698","DOI":"10.1145\/3512290.3528698"},{"key":"16","unstructured":"[16] G. Reinelt, \u201cTSPLIB - Discrete and combinatorial optimization,\u201d http:\/\/comopt.ifi.uni-heidelberg.de\/software\/TSPLIB95, accessed Jan. 9. 2024."},{"key":"17","unstructured":"[17] R. Burkard, E. \u00c7ela, S. Karisch, and F. Rendl, \u201cQAPLIB - A quadratic assignment problem library,\u201d https:\/\/qaplib.mgi.polymtl.ca\/, accessed Jan. 9. 2024."}],"container-title":["IEICE Transactions on Information and Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E108.D\/1\/E108.D_2024PAP0007\/_pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,4]],"date-time":"2025-01-04T03:19:47Z","timestamp":1735960787000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E108.D\/1\/E108.D_2024PAP0007\/_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,1]]},"references-count":17,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2025]]}},"URL":"https:\/\/doi.org\/10.1587\/transinf.2024pap0007","relation":{},"ISSN":["0916-8532","1745-1361"],"issn-type":[{"type":"print","value":"0916-8532"},{"type":"electronic","value":"1745-1361"}],"subject":[],"published":{"date-parts":[[2025,1,1]]},"article-number":"2024PAP0007"}}