{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T02:12:52Z","timestamp":1768011172312,"version":"3.49.0"},"publisher-location":"New York, NY, USA","reference-count":26,"publisher":"ACM","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,11,16]]},"DOI":"10.1145\/3731599.3767585","type":"proceedings-article","created":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T16:13:44Z","timestamp":1762532024000},"page":"2190-2200","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Bridging Speed and Optimality in Job Scheduling: A Hybrid Ant Colony Optimization Approach for Distributed Systems"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2851-595X","authenticated-orcid":false,"given":"Hongwei","family":"Jin","sequence":"first","affiliation":[{"name":"Argonne National Laboratory (ANL), Lemont, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9811-0309","authenticated-orcid":false,"given":"Pawel","family":"Zuk","sequence":"additional","affiliation":[{"name":"University of Southern California (USC), Los Angeles, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9409-2011","authenticated-orcid":false,"given":"Krishnan","family":"Raghavan","sequence":"additional","affiliation":[{"name":"Argonne National Laboratory (ANL), Lemont, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-1436-0292","authenticated-orcid":false,"given":"Prachi","family":"Jadhav","sequence":"additional","affiliation":[{"name":"University of Tennessee, Knoxville, Knoxville, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-6088-2129","authenticated-orcid":false,"given":"Aiden","family":"Hamade","sequence":"additional","affiliation":[{"name":"University of Kentucky, Lexington, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5106-503X","authenticated-orcid":false,"given":"Ewa","family":"Deelman","sequence":"additional","affiliation":[{"name":"University of Southern California (USC), Los Angeles, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0292-5715","authenticated-orcid":false,"given":"Prasanna","family":"Balaprakash","sequence":"additional","affiliation":[{"name":"Oak Ridge National Laboratory (ORNL), Oak Ridge, USA"}]}],"member":"320","published-online":{"date-parts":[[2025,11,15]]},"reference":[{"key":"e_1_3_3_1_2_2","doi-asserted-by":"crossref","unstructured":"Christian Blum and Michael Sampels. 2004. An ant colony optimization algorithm for shop scheduling problems. Journal of Mathematical Modelling and Algorithms 3 (2004) 285\u2013308.","DOI":"10.1023\/B:JMMA.0000038614.39977.6f"},{"key":"e_1_3_3_1_3_2","doi-asserted-by":"crossref","unstructured":"Eric Bonabeau. 1999. Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press google schola 2 (1999) 25\u201334.","DOI":"10.1093\/oso\/9780195131581.001.0001"},{"key":"e_1_3_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.5555\/983298"},{"key":"e_1_3_3_1_5_2","doi-asserted-by":"crossref","unstructured":"Peter Brucker Bernd Jurisch and Bernd Sievers. 1994. A branch and bound algorithm for the job-shop scheduling problem. Discrete applied mathematics 49 1-3 (1994) 107\u2013127.","DOI":"10.1016\/0166-218X(94)90204-6"},{"key":"e_1_3_3_1_6_2","doi-asserted-by":"crossref","unstructured":"Jingru Chang Dong Yu Yi Hu Wuwei He and Haoyu Yu. 2022. Deep reinforcement learning for dynamic flexible job shop scheduling with random job arrival. Processes 10 4 (2022) 760.","DOI":"10.3390\/pr10040760"},{"key":"e_1_3_3_1_7_2","doi-asserted-by":"publisher","DOI":"10.1145\/2541940.2541941"},{"key":"e_1_3_3_1_8_2","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/1290.001.0001"},{"key":"e_1_3_3_1_9_2","unstructured":"Yuping Fan. 2021. Job scheduling in high performance computing. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2109.09269 (2021)."},{"key":"e_1_3_3_1_10_2","doi-asserted-by":"crossref","unstructured":"Michael\u00a0R Garey David\u00a0S Johnson and Ravi Sethi. 1976. The complexity of flowshop and jobshop scheduling. Mathematics of operations research 1 2 (1976) 117\u2013129.","DOI":"10.1287\/moor.1.2.117"},{"key":"e_1_3_3_1_11_2","unstructured":"Z Haipeng G Mitsuo F Shigeru and KK Woo. 2004. Hybrid ant colony optimization for job-shop scheduling problem. Faji Shisutemu Shinpojiumu Koen Ronbunshu 20 (2004) 304\u201305."},{"key":"e_1_3_3_1_12_2","doi-asserted-by":"crossref","unstructured":"Ali\u00a0S Kiran Sema Alptekin and A Celal\u00a0Kaplan. 1991. Tardiness heuristic for scheduling flexible manufacturing systems. Production Planning & Control 2 3 (1991) 228\u2013241.","DOI":"10.1080\/09537289108919351"},{"key":"e_1_3_3_1_13_2","unstructured":"M Mastrolilli and LM Gambardella. 1998. Effective neighborhood functions for the flexible job shop problem: Appendix."},{"key":"e_1_3_3_1_14_2","volume-title":"Evolutionary search and the job shop: investigations on genetic algorithms for production scheduling","author":"Mattfeld Dirk\u00a0C","year":"2013","unstructured":"Dirk\u00a0C Mattfeld. 2013. Evolutionary search and the job shop: investigations on genetic algorithms for production scheduling. Springer Science & Business Media."},{"key":"e_1_3_3_1_15_2","doi-asserted-by":"crossref","unstructured":"Toshiyuki Miyamoto Toyohiro Umeda and Shigemasa Takai. 2020. Distributed Job Shop Scheduling using Consensus Alternating Direction Method of Multipliers. IFAC-PapersOnLine 53 2 (2020) 10785\u201310790.","DOI":"10.1016\/j.ifacol.2020.12.2862"},{"key":"e_1_3_3_1_16_2","doi-asserted-by":"crossref","unstructured":"Eugeniusz Nowicki and Czeslaw Smutnicki. 1996. A fast taboo search algorithm for the job shop problem. Management science 42 6 (1996) 797\u2013813.","DOI":"10.1287\/mnsc.42.6.797"},{"key":"e_1_3_3_1_17_2","doi-asserted-by":"publisher","DOI":"10.1145\/2517349.2522716"},{"key":"e_1_3_3_1_18_2","unstructured":"Laurent Perron and Vincent Furnon. 2024. OR-Tools. https:\/\/developers.google.com\/optimization\/"},{"key":"e_1_3_3_1_19_2","doi-asserted-by":"crossref","unstructured":"Ferdinando Pezzella Gianluca Morganti and Giampiero Ciaschetti. 2008. A genetic algorithm for the flexible job-shop scheduling problem. Computers & operations research 35 10 (2008) 3202\u20133212.","DOI":"10.1016\/j.cor.2007.02.014"},{"key":"e_1_3_3_1_20_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-05921-6"},{"key":"e_1_3_3_1_21_2","unstructured":"Igor\u00a0G Smit Jianan Zhou Robbert Reijnen Yaoxin Wu Jian Chen Cong Zhang Zaharah Bukhsh Wim Nuijten and Yingqian Zhang. 2024. Graph Neural Networks for Job Shop Scheduling Problems: A Survey. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2406.14096 (2024)."},{"key":"e_1_3_3_1_22_2","unstructured":"Richard\u00a0S Sutton. 2018. Reinforcement learning: An introduction. A Bradford Book (2018)."},{"key":"e_1_3_3_1_23_2","doi-asserted-by":"crossref","unstructured":"Eric Taillard. 1993. Benchmarks for basic scheduling problems. arXiv 64 2 (1993) 278\u2013285.","DOI":"10.1016\/0377-2217(93)90182-M"},{"key":"e_1_3_3_1_24_2","doi-asserted-by":"crossref","unstructured":"Jianchao Tang Guoji Zhang Binbin Lin and Bixi Zhang. 2011. A hybrid algorithm for flexible job-shop scheduling problem. Procedia Engineering 15 (2011) 3678\u20133683.","DOI":"10.1016\/j.proeng.2011.08.689"},{"key":"e_1_3_3_1_25_2","unstructured":"Pierre Tassel Martin Gebser and Konstantin Schekotihin. 2021. A Reinforcement Learning Environment For Job-Shop Scheduling. arxiv:https:\/\/arXiv.org\/abs\/2104.03760\u00a0[cs.LG]"},{"key":"e_1_3_3_1_26_2","doi-asserted-by":"crossref","unstructured":"Mehmet\u00a0Fatih Uslu S\u00fcleyman Uslu and Faruk Bulut. 2022. An adaptive hybrid approach: Combining genetic algorithm and ant colony optimization for integrated process planning and scheduling. Applied Computing and Informatics 18 1\/2 (2022) 101\u2013112.","DOI":"10.1016\/j.aci.2018.12.002"},{"key":"e_1_3_3_1_27_2","doi-asserted-by":"crossref","unstructured":"Peter\u00a0JM Van\u00a0Laarhoven Emile\u00a0HL Aarts and Jan\u00a0Karel Lenstra. 1992. Job shop scheduling by simulated annealing. Operations research 40 1 (1992) 113\u2013125.","DOI":"10.1287\/opre.40.1.113"}],"event":{"name":"SC Workshops '25: Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis","location":"St Louis MO USA","acronym":"SC Workshops '25","sponsor":["SIGHPC ACM Special Interest Group on High Performance Computing, Special Interest Group on High Performance Computing"]},"container-title":["Proceedings of the SC '25 Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3731599.3767585","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T19:28:32Z","timestamp":1767986912000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3731599.3767585"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,15]]},"references-count":26,"alternative-id":["10.1145\/3731599.3767585","10.1145\/3731599"],"URL":"https:\/\/doi.org\/10.1145\/3731599.3767585","relation":{},"subject":[],"published":{"date-parts":[[2025,11,15]]},"assertion":[{"value":"2025-11-15","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}