{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T06:23:47Z","timestamp":1740119027985,"version":"3.37.3"},"reference-count":70,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2021,10,1]],"date-time":"2021-10-01T00:00:00Z","timestamp":1633046400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2021,10,1]],"date-time":"2021-10-01T00:00:00Z","timestamp":1633046400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2021,10,1]],"date-time":"2021-10-01T00:00:00Z","timestamp":1633046400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2021,10,1]],"date-time":"2021-10-01T00:00:00Z","timestamp":1633046400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2021,10,1]],"date-time":"2021-10-01T00:00:00Z","timestamp":1633046400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,10,1]],"date-time":"2021-10-01T00:00:00Z","timestamp":1633046400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61573278","62103062"],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002837","name":"Chang'an University","doi-asserted-by":"publisher","award":["300102320302"],"id":[{"id":"10.13039\/501100002837","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100013804","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100013804","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100017596","name":"Natural Science Basic Research Program of Shaanxi Province","doi-asserted-by":"publisher","award":["2021JQ-288"],"id":[{"id":"10.13039\/501100017596","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Engineering Applications of Artificial Intelligence"],"published-print":{"date-parts":[[2021,10]]},"DOI":"10.1016\/j.engappai.2021.104411","type":"journal-article","created":{"date-parts":[[2021,8,28]],"date-time":"2021-08-28T19:25:44Z","timestamp":1630178744000},"page":"104411","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":11,"special_numbering":"C","title":["Hybrid particle swarm optimization algorithm for scheduling flexible assembly systems with blocking and deadlock constraints"],"prefix":"10.1016","volume":"105","author":[{"given":"Xiaoling","family":"Li","sequence":"first","affiliation":[]},{"given":"Keyi","family":"Xing","sequence":"additional","affiliation":[]},{"given":"Qingchang","family":"Lu","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.engappai.2021.104411_b1","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2021.104196","article-title":"Two efficient nature inspired meta-heuristics solving blocking hybrid flow shop manufacturing problem","volume":"100","author":"Aqil","year":"2021","journal-title":"Eng. Appl. Artif. Intell."},{"issue":"5","key":"10.1016\/j.engappai.2021.104411_b2","doi-asserted-by":"crossref","first-page":"831","DOI":"10.1109\/TSMC.2014.2376471","article-title":"Deadlock-free scheduling method for flexible manufacturing systems based on timed colored Petri nets and anytime heuristic search","volume":"45","author":"Baruwa","year":"2015","journal-title":"IEEE Trans. Syst. Man Cybern.: Syst."},{"issue":"5","key":"10.1016\/j.engappai.2021.104411_b3","doi-asserted-by":"crossref","first-page":"961","DOI":"10.1007\/s10845-013-0837-8","article-title":"A research survey: Review of AI solution strategies of job shop scheduling problem","volume":"26","author":"Calis","year":"2015","journal-title":"J. Intell. Manuf."},{"issue":"1","key":"10.1016\/j.engappai.2021.104411_b4","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1109\/TASE.2019.2945717","article-title":"A knowledge-based cuckoo search algorithm to schedule a flexible job shop with sequencing flexibility","volume":"18","author":"Cao","year":"2021","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"issue":"12","key":"10.1016\/j.engappai.2021.104411_b5","doi-asserted-by":"crossref","first-page":"3561","DOI":"10.1080\/00207543.2015.1084063","article-title":"A competitive memetic algorithm for the distributed two-stage assembly flow-shop scheduling problem","volume":"54","author":"Deng","year":"2015","journal-title":"Int. J. Prod. Res."},{"key":"10.1016\/j.engappai.2021.104411_b6","doi-asserted-by":"crossref","DOI":"10.1016\/j.cor.2020.104951","article-title":"Improved particle swarm optimization algorithm based novel encoding and decoding schemes for flexible job shop scheduling problem","volume":"121","author":"Ding","year":"2020","journal-title":"Comput. Oper. Res."},{"key":"10.1016\/j.engappai.2021.104411_b7","doi-asserted-by":"crossref","DOI":"10.1016\/j.cor.2020.105088","article-title":"Energy aware scheduling in flexible flow shops with hybrid particle swarm optimization","volume":"125","author":"Ding","year":"2021","journal-title":"Comput. Oper. Res."},{"issue":"2","key":"10.1016\/j.engappai.2021.104411_b8","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1023\/A:1014482419706","article-title":"Design of supervisors to avoid deadlock in flexible assembly systems","volume":"14","author":"Fanti","year":"2002","journal-title":"Int. J. Flexible Manuf. Syst."},{"key":"10.1016\/j.engappai.2021.104411_b9","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1016\/j.engappai.2018.04.009","article-title":"The social engineering optimizer (SEO)","volume":"72","author":"Fathollahi-Fard","year":"2018","journal-title":"Eng. Appl. Artif. Intell."},{"key":"10.1016\/j.engappai.2021.104411_b10","doi-asserted-by":"crossref","DOI":"10.1007\/s00500-020-04812-z","article-title":"Red deer algorithm (RDA): A new nature-inspired meta-heuristic","author":"Fathollahi-Fard","year":"2020","journal-title":"Soft Comput."},{"key":"10.1016\/j.engappai.2021.104411_b11","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2020.106734","article-title":"Cooperation search algorithm: A novel metaheuristic evolutionary intelligence algorithm for numerical optimization and engineering optimization problems","volume":"98","author":"Feng","year":"2021","journal-title":"Appl. Soft Comput. J."},{"issue":"12","key":"10.1016\/j.engappai.2021.104411_b12","doi-asserted-by":"crossref","first-page":"2438","DOI":"10.1109\/TSMC.2018.2847448","article-title":"Target disassembly sequencing and scheme evaluation for CNC machine tools using improved multiobjective ant colony algorithm and fuzzy integral","volume":"49","author":"Feng","year":"2019","journal-title":"IEEE Trans. Syst. Man Cybern.: Syst."},{"issue":"3","key":"10.1016\/j.engappai.2021.104411_b13","doi-asserted-by":"crossref","first-page":"707","DOI":"10.1016\/j.ejor.2016.09.055","article-title":"A new vision of approximate methods for the permutation flowshop to minimize makespan: State-of-the-art and computational evaluation","volume":"257","author":"Fernandez-Viagas","year":"2017","journal-title":"European J. Oper. Res."},{"key":"10.1016\/j.engappai.2021.104411_b14","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1016\/j.ejor.2018.04.033","article-title":"Deterministic assembly scheduling problems: A review and classification of concurrent-type scheduling models and solution procedures","volume":"273","author":"Framinan","year":"2019","journal-title":"European J. Oper. Res."},{"key":"10.1016\/j.engappai.2021.104411_b15","doi-asserted-by":"crossref","DOI":"10.1016\/j.swevo.2019.100572","article-title":"A three-level particle swarm optimization with variable neighborhood search algorithm for the production scheduling problem with mould maintenance","volume":"50","author":"Fu","year":"2019","journal-title":"Swarm Evol. Comput."},{"key":"10.1016\/j.engappai.2021.104411_b16","doi-asserted-by":"crossref","first-page":"515","DOI":"10.1016\/j.jclepro.2019.04.046","article-title":"Stochastic multi-objective modelling and optimization of an energy-conscious distributed permutation flow shop scheduling problem with the total tardiness constraint","volume":"226","author":"Fu","year":"2019","journal-title":"J. Clean. Prod."},{"key":"10.1016\/j.engappai.2021.104411_b17","doi-asserted-by":"crossref","first-page":"2257","DOI":"10.1007\/s10845-017-1385-4","article-title":"Two-agent stochastic flow shop deteriorating scheduling via a hybrid multi-objective evolutionary algorithm","volume":"30","author":"Fu","year":"2019","journal-title":"J. Intell. Manuf."},{"key":"10.1016\/j.engappai.2021.104411_b18","unstructured":"Hajiaghaei-Keshteli, M., Aminnayeri, M., 2013. Keshtel Algorithm (KA): A new optimization algorithm inspired by Keshtels\u2019 feeding. In: Proceeding in IEEE Conference on Industrial Engineering and Management Systems. pp. 2249-2253."},{"key":"10.1016\/j.engappai.2021.104411_b19","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1016\/j.asoc.2014.09.034","article-title":"Solving the integrated scheduling of production and rail transportation problem by keshtel algorithm","volume":"25","author":"Hajiaghaei-Keshteli","year":"2014","journal-title":"Appl. Soft Comput."},{"key":"10.1016\/j.engappai.2021.104411_b20","doi-asserted-by":"crossref","first-page":"849","DOI":"10.1016\/j.future.2019.02.028","article-title":"Harris hawks optimization: Algorithm and applications","volume":"97","author":"Heidari","year":"2019","journal-title":"Future Gener. Comput. Syst."},{"issue":"10","key":"10.1016\/j.engappai.2021.104411_b21","doi-asserted-by":"crossref","first-page":"2538","DOI":"10.1016\/j.automatica.2008.03.008","article-title":"Robustness analysis of holonic assembly\/disassembly processes with Petri nets","volume":"44","author":"Hsieh","year":"2008","journal-title":"Automatica"},{"issue":"2","key":"10.1016\/j.engappai.2021.104411_b22","doi-asserted-by":"crossref","first-page":"513","DOI":"10.1109\/TCST.2014.2342664","article-title":"A Petri net-based discrete-event control of automated manufacturing systems with assembly operations","volume":"23","author":"Hu","year":"2015","journal-title":"IEEE Trans. Control Syst. Technol."},{"issue":"1","key":"10.1016\/j.engappai.2021.104411_b23","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1109\/TII.2012.2198661","article-title":"Deadlock-free control of automated manufacturing systems with flexible routes and assembly operations using Petri nets","volume":"9","author":"Hu","year":"2013","journal-title":"IEEE Trans. Ind. Inf."},{"key":"10.1016\/j.engappai.2021.104411_b24","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2020.104016","article-title":"Effective constructive heuristics and discrete bee colony optimization for distributed flowshop with setup times","volume":"97","author":"Huang","year":"2021","journal-title":"Eng. Appl. Artif. Intell."},{"key":"10.1016\/j.engappai.2021.104411_b25","series-title":"Proceedings of the IEEE International Conference on Neural Networks","first-page":"1942","article-title":"Particle swarm optimization","author":"Kennedy","year":"1995"},{"issue":"10","key":"10.1016\/j.engappai.2021.104411_b26","doi-asserted-by":"crossref","first-page":"2926","DOI":"10.1080\/00207543.2018.1550269","article-title":"Flow shop scheduling problems with assembly operations: A review and new trends","volume":"57","author":"Komaki","year":"2019","journal-title":"Int. J. Prod. Res."},{"key":"10.1016\/j.engappai.2021.104411_b27","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1016\/j.cie.2017.01.006","article-title":"Improved discrete cuckoo optimization algorithm for the three-stage assembly flowshop scheduling problem","volume":"105","author":"Komaki","year":"2017","journal-title":"Comput. Ind. Eng."},{"key":"10.1016\/j.engappai.2021.104411_b28","doi-asserted-by":"crossref","first-page":"680","DOI":"10.1016\/j.ins.2014.02.155","article-title":"A particle swarm optimization based hyper-heuristic algorithm for the classic resource constrained project scheduling problem","volume":"277","author":"Koulinas","year":"2014","journal-title":"Inform. Sci."},{"key":"10.1016\/j.engappai.2021.104411_b29","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1016\/j.cie.2018.06.001","article-title":"Minimizing total completion time in the assembly scheduling problem","volume":"122","author":"Lee","year":"2018","journal-title":"Comput. Ind. Eng."},{"key":"10.1016\/j.engappai.2021.104411_b30","article-title":"Cooperated teaching-learning-based optimization for distributed two-stage assembly flow shop scheduling","author":"Lei","year":"2020","journal-title":"Int. J. Prod. Res."},{"key":"10.1016\/j.engappai.2021.104411_b31","doi-asserted-by":"crossref","first-page":"413","DOI":"10.1016\/j.asoc.2017.01.045","article-title":"Hybrid heuristic search approach for deadlock-free scheduling of flexible manufacturing systems using petri nets","volume":"55","author":"Lei","year":"2017","journal-title":"Appl. Soft Comput."},{"key":"10.1016\/j.engappai.2021.104411_b32","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1016\/j.ins.2014.10.009","article-title":"Solving the large-scale hybrid flow shop scheduling problem with limited buffers by a hybrid artificial bee colony algorithm","volume":"316","author":"Li","year":"2015","journal-title":"Inform. Sci."},{"key":"10.1016\/j.engappai.2021.104411_b33","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1016\/j.engappai.2014.09.015","article-title":"A discrete teaching-learning-based optimization algorithm for realistic flowshop rescheduling problems","volume":"37","author":"Li","year":"2015","journal-title":"Eng. Appl. Artif. Intell."},{"issue":"4","key":"10.1016\/j.engappai.2021.104411_b34","doi-asserted-by":"crossref","first-page":"437","DOI":"10.1109\/TSMCC.2011.2160626","article-title":"Deadlock control of automated manufacturing systems based on Petri nets-A literature review","volume":"42","author":"Li","year":"2012","journal-title":"IEEE Trans. Syst. Man Cybern. C, Appl. Rev."},{"key":"10.1016\/j.engappai.2021.104411_b35","doi-asserted-by":"crossref","first-page":"188","DOI":"10.1016\/j.cie.2016.12.008","article-title":"Total energy consumption optimization via genetic algorithm in flexible manufacturing systems","volume":"104","author":"Li","year":"2017","journal-title":"Comput. Ind. Eng."},{"issue":"2","key":"10.1016\/j.engappai.2021.104411_b36","doi-asserted-by":"crossref","first-page":"691","DOI":"10.1109\/TASE.2018.2852722","article-title":"Modified dynamic programming algorithm for optimization of total energy consumption in flexible manufacturing systems","volume":"16","author":"Li","year":"2019","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"issue":"9","key":"10.1016\/j.engappai.2021.104411_b37","doi-asserted-by":"crossref","first-page":"3274","DOI":"10.1080\/00207543.2017.1401240","article-title":"Job shop scheduling with a combination of four buffering constraints","volume":"56","author":"Liu","year":"2018","journal-title":"Int. J. Prod. Res."},{"issue":"6","key":"10.1016\/j.engappai.2021.104411_b38","doi-asserted-by":"crossref","first-page":"3379","DOI":"10.1109\/TII.2018.2876343","article-title":"A Petri net-based deadlock avoidance policy for flexible manufacturing systems with assembly operations and multiple resource acquisition","volume":"15","author":"Luo","year":"2019","journal-title":"IEEE Trans. Ind. Inf."},{"key":"10.1016\/j.engappai.2021.104411_b39","doi-asserted-by":"crossref","DOI":"10.1016\/j.cor.2019.104812","article-title":"An improved particle swarm optimization algorithm to solve hybrid flowshop scheduling problems with the effect of human factors-A case study","volume":"114","author":"Marichelvam","year":"2020","journal-title":"Comput. Oper. Res."},{"key":"10.1016\/j.engappai.2021.104411_b40","doi-asserted-by":"crossref","first-page":"498","DOI":"10.1016\/S0377-2217(01)00338-1","article-title":"Job-shop scheduling with blocking and no-wait constraints","volume":"143","author":"Mascis","year":"2002","journal-title":"European J. Oper. Res."},{"issue":"8","key":"10.1016\/j.engappai.2021.104411_b41","doi-asserted-by":"crossref","first-page":"2169","DOI":"10.1080\/00207541003733775","article-title":"Modelling and solving a practical flexible job-shop scheduling problem with blocking constraints","volume":"49","author":"Mati","year":"2011","journal-title":"Int. J. Prod. Res."},{"key":"10.1016\/j.engappai.2021.104411_b42","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.advengsoft.2013.12.007","article-title":"Grey wolf optimizer","volume":"69","author":"Mirjalili","year":"2014","journal-title":"Adv. Eng. Softw."},{"key":"10.1016\/j.engappai.2021.104411_b43","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1016\/j.eswa.2019.06.069","article-title":"The blocking flow shop scheduling problem: A comprehensive and conceptual review","volume":"137","author":"Miyata","year":"2019","journal-title":"Expert Syst. Appl."},{"year":"2005","series-title":"Design and Analysis of Experiments","author":"Montgomery","key":"10.1016\/j.engappai.2021.104411_b44"},{"key":"10.1016\/j.engappai.2021.104411_b45","doi-asserted-by":"crossref","first-page":"573","DOI":"10.1007\/s11269-020-02737-8","article-title":"Multiple hydropower reservoirs operation by hyperbolic grey wolf optimizer based on elitism selection and adaptive mutation","volume":"35","author":"Niu","year":"2021","journal-title":"Water Resour. Manag."},{"year":"2016","series-title":"Scheduling Theory, Algorithms, and Systems","author":"Pinedo","key":"10.1016\/j.engappai.2021.104411_b46"},{"issue":"4","key":"10.1016\/j.engappai.2021.104411_b47","doi-asserted-by":"crossref","first-page":"587","DOI":"10.1007\/s10732-014-9279-5","article-title":"An iterated greedy metaheuristic for the blocking job shop scheduling problem","volume":"22","author":"Pranzo","year":"2016","journal-title":"J. Heuristics"},{"key":"10.1016\/j.engappai.2021.104411_b48","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1016\/j.omega.2017.05.010","article-title":"The non-permutation flow-shop scheduling problem: A literature review","volume":"77","author":"Rossit","year":"2018","journal-title":"Omega"},{"issue":"1","key":"10.1016\/j.engappai.2021.104411_b49","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1109\/TSMCA.2003.820572","article-title":"Supervisory control for deadlock avoidance in compound processes","volume":"34","author":"Roszkowska","year":"2004","journal-title":"IEEE Trans. Syst. Man Cybern.: Syst."},{"key":"10.1016\/j.engappai.2021.104411_b50","doi-asserted-by":"crossref","first-page":"488","DOI":"10.1016\/j.asoc.2015.12.035","article-title":"A robust hybrid approach based on particle swarm optimization and genetic algorithm to minimize the total machine load on unrelated parallel machines","volume":"41","author":"Salehi\u00a0Mir","year":"2016","journal-title":"Appl. Soft Comput."},{"key":"10.1016\/j.engappai.2021.104411_b51","doi-asserted-by":"crossref","first-page":"4647","DOI":"10.1007\/s10489-020-01809-x","article-title":"Effective constructive heuristic and metaheuristic for the distributed assembly blocking flow-shop scheduling problem","volume":"50","author":"Shao","year":"2020","journal-title":"Appl. Intell."},{"issue":"9","key":"10.1016\/j.engappai.2021.104411_b52","doi-asserted-by":"crossref","first-page":"1159","DOI":"10.1007\/s00170-009-2337-8","article-title":"Metaheuristic approaches to sequencing mixed-model fabrication\/assembly systems with two objectives","volume":"48","author":"Shao","year":"2010","journal-title":"Int. J. Adv. Manuf. Technol."},{"issue":"9","key":"10.1016\/j.engappai.2021.104411_b53","doi-asserted-by":"crossref","first-page":"2604","DOI":"10.1080\/00207543.2019.1622052","article-title":"Hybrid algorithm based on improved extended shifting bottleneck procedure and GA for assembly job shop scheduling problem","volume":"58","author":"Shi","year":"2020","journal-title":"Int. J. Prod. Res."},{"key":"10.1016\/j.engappai.2021.104411_b54","doi-asserted-by":"crossref","DOI":"10.1016\/j.swevo.2020.100807","article-title":"A genetic programming hyper-heuristic for the distributed assembly permutation flow-shop scheduling problem with sequence dependent setup times","volume":"60","author":"Song","year":"2021","journal-title":"Swarm Evol. Comput."},{"issue":"4","key":"10.1016\/j.engappai.2021.104411_b55","doi-asserted-by":"crossref","first-page":"2456","DOI":"10.1109\/TII.2018.2884845","article-title":"Modeling and planning for dual-objective selective disassembly using and\/or graph and discrete artificial bee colony","volume":"15","author":"Tian","year":"2019","journal-title":"IEEE Trans. Ind. Inf."},{"key":"10.1016\/j.engappai.2021.104411_b56","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1016\/j.swevo.2018.01.012","article-title":"A two-stage three-machine assembly flow shop scheduling with learning consideration to minimize the flowtime by six hybrids of particle swarm optimization","volume":"41","author":"Wu","year":"2018","journal-title":"Swarm Evol. Comput."},{"issue":"3","key":"10.1016\/j.engappai.2021.104411_b57","doi-asserted-by":"crossref","first-page":"421","DOI":"10.1007\/s00291-006-0046-3","article-title":"Real-time deadlock-free scheduling for semiconductor track systems based on colored timed Petri nets","volume":"29","author":"Wu","year":"2007","journal-title":"OR Spectr."},{"issue":"1","key":"10.1016\/j.engappai.2021.104411_b58","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1109\/TSMCA.2007.909542","article-title":"Resource-oriented Petri net for deadlock avoidance in flexible assembly systems","volume":"38","author":"Wu","year":"2008","journal-title":"IEEE Trans. Syst. Man Cybern.: Syst."},{"key":"10.1016\/j.engappai.2021.104411_b59","doi-asserted-by":"crossref","first-page":"358","DOI":"10.1016\/j.automatica.2017.09.001","article-title":"Deadlock characterization and control of flexible assembly systems with petri net","volume":"87","author":"Xing","year":"2018","journal-title":"Automatica"},{"issue":"3","key":"10.1016\/j.engappai.2021.104411_b60","doi-asserted-by":"crossref","first-page":"757","DOI":"10.1109\/TASE.2013.2259816","article-title":"Solving assembly scheduling problems with tree-structure precedence constraints: A Lagrangian relaxation approach","volume":"10","author":"Xu","year":"2013","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"issue":"4","key":"10.1016\/j.engappai.2021.104411_b61","doi-asserted-by":"crossref","first-page":"663","DOI":"10.3390\/sym13040663","article-title":"Disassembly sequence planning for intelligent manufacturing using social engineering optimizer","volume":"13","author":"Zhang","year":"2021","journal-title":"Sym."},{"issue":"2","key":"10.1016\/j.engappai.2021.104411_b62","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1016\/j.ejor.2019.11.016","article-title":"Multi-objective optimisation in flexible assembly job shop scheduling using a distributed ant colony system","volume":"283","author":"Zhang","year":"2020","journal-title":"European J. Oper. Res."},{"key":"10.1016\/j.engappai.2021.104411_b63","doi-asserted-by":"crossref","DOI":"10.1016\/j.swevo.2020.100785","article-title":"A matrix-cube-based estimation of distribution algorithm for the distributed assembly permutation flow-shop scheduling problem","volume":"60","author":"Zhang","year":"2021","journal-title":"Swarm Evol. Comput."},{"key":"10.1016\/j.engappai.2021.104411_b64","doi-asserted-by":"crossref","DOI":"10.1016\/j.rcim.2020.102081","article-title":"A discrete whale swarm algorithm for hybrid flow-shop scheduling problem with limited buffers","volume":"68","author":"Zhang","year":"2021","journal-title":"Robot. Comput. Integr. Manuf."},{"key":"10.1016\/j.engappai.2021.104411_b65","doi-asserted-by":"crossref","first-page":"549","DOI":"10.1016\/j.jmsy.2021.03.020","article-title":"Maintenance costs and makespan minimization for assembly permutation flow shop scheduling by considering preventive and corrective maintenance","volume":"59","author":"Zhang","year":"2021","journal-title":"J. Manuf. Syst."},{"issue":"3","key":"10.1016\/j.engappai.2021.104411_b66","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1109\/TEM.2017.2785774","article-title":"Flexible assembly job-shop scheduling with sequence-dependent setup times and part sharing in a dynamic environment: Constraint programming model, mixed-integer programming model, and dispatching rules","volume":"65","author":"Zhang","year":"2018","journal-title":"IEEE Trans. Eng. Manage."},{"key":"10.1016\/j.engappai.2021.104411_b67","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1016\/j.engappai.2018.09.005","article-title":"Discrete differential evolution algorithm for distributed blocking flowshop scheduling with makespan criterion","volume":"76","author":"Zhang","year":"2018","journal-title":"Eng. Appl. Artif. Intell."},{"key":"10.1016\/j.engappai.2021.104411_b68","first-page":"41","article-title":"A factorial based particle swarm optimization with a population adaptation mechanism for the no-wait flow shop scheduling problem with the makespan objective","volume":"126","author":"Zhao","year":"2019","journal-title":"Eng. Appl. Artif. Intell."},{"key":"10.1016\/j.engappai.2021.104411_b69","doi-asserted-by":"crossref","DOI":"10.1016\/j.cie.2020.107082","article-title":"A cooperative water wave optimization algorithm with reinforcement learning for the distributed assembly no-idle flowshop scheduling problem","volume":"153","author":"Zhao","year":"2021","journal-title":"Comput. Ind. Eng."},{"year":"2005","series-title":"Deadlock Resolution in Computer-Integrated System","author":"Zhou","key":"10.1016\/j.engappai.2021.104411_b70"}],"container-title":["Engineering Applications of Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0952197621002591?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0952197621002591?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2023,3,11]],"date-time":"2023-03-11T19:59:55Z","timestamp":1678564795000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0952197621002591"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10]]},"references-count":70,"alternative-id":["S0952197621002591"],"URL":"https:\/\/doi.org\/10.1016\/j.engappai.2021.104411","relation":{},"ISSN":["0952-1976"],"issn-type":[{"type":"print","value":"0952-1976"}],"subject":[],"published":{"date-parts":[[2021,10]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Hybrid particle swarm optimization algorithm for scheduling flexible assembly systems with blocking and deadlock constraints","name":"articletitle","label":"Article Title"},{"value":"Engineering Applications of Artificial Intelligence","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.engappai.2021.104411","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2021 Elsevier Ltd. All rights reserved.","name":"copyright","label":"Copyright"}],"article-number":"104411"}}