{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T04:01:30Z","timestamp":1768795290831,"version":"3.49.0"},"reference-count":47,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2022,1,10]],"date-time":"2022-01-10T00:00:00Z","timestamp":1641772800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,1,10]],"date-time":"2022-01-10T00:00:00Z","timestamp":1641772800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Intell Manuf"],"published-print":{"date-parts":[[2023,4]]},"DOI":"10.1007\/s10845-021-01888-8","type":"journal-article","created":{"date-parts":[[2022,1,10]],"date-time":"2022-01-10T21:29:01Z","timestamp":1641850141000},"page":"1763-1778","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["An improved artificial algae algorithm integrated with differential evolution for job-shop scheduling problem"],"prefix":"10.1007","volume":"34","author":[{"given":"Abdelmonem M.","family":"Ibrahim","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3231-0594","authenticated-orcid":false,"given":"Mohamed A.","family":"Tawhid","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,1,10]]},"reference":[{"key":"1888_CR1","doi-asserted-by":"crossref","unstructured":"Ali, A.\u00a0F., & Tawhid, M.\u00a0A. (2015). Hybrid particle swarm optimization with a modified arithmetical crossover for solving unconstrained optimization problems. INFOR: Information Systems and Operational Research, 53(3), 125\u2013141.","DOI":"10.3138\/infor.53.3.125"},{"issue":"1","key":"1888_CR2","first-page":"151","volume":"12","author":"AF Ali","year":"2016","unstructured":"Ali, A. F., & Tawhid, M. A. (2016). Hybrid simulated annealing and pattern search method for solving minimax and integer programming problems. Pacific Journal of Optimization, 12(1), 151\u2013184.","journal-title":"Pacific Journal of Optimization"},{"key":"1888_CR3","doi-asserted-by":"publisher","first-page":"376","DOI":"10.1016\/j.cie.2015.04.006","volume":"85","author":"L Asadzadeh","year":"2015","unstructured":"Asadzadeh, L. (2015). A local search genetic algorithm for the job shop scheduling problem with intelligent agents. Computers& Industrial Engineering, 85, 376\u2013383.","journal-title":"Computers & Industrial Engineering"},{"issue":"11\u201312","key":"1888_CR4","doi-asserted-by":"publisher","first-page":"1957","DOI":"10.1016\/j.mcm.2010.04.019","volume":"52","author":"L Asadzadeh","year":"2010","unstructured":"Asadzadeh, L., & Zamanifar, K. (2010). An agent-based parallel approach for the job shop scheduling problem with genetic algorithms. Mathematical and Computer Modelling, 52(11\u201312), 1957\u20131965.","journal-title":"Mathematical and Computer Modelling"},{"key":"1888_CR5","doi-asserted-by":"crossref","unstructured":"Balande, U., & Shrimankar, D. (2020). A modified teaching learning metaheuristic algorithm with opposite-based learning for permutation flow-shop scheduling problem. Evolutionary Intelligence, 1\u201323.","DOI":"10.1007\/s12065-020-00487-5"},{"key":"1888_CR6","doi-asserted-by":"publisher","first-page":"204","DOI":"10.1016\/j.ins.2014.02.056","volume":"276","author":"A Baykaso\u011flu","year":"2014","unstructured":"Baykaso\u011flu, A., Hamzadayi, A., & K\u00f6se, S. Y. (2014). Testing the performance of teaching-learning based optimization (tlbo) algorithm on combinatorial problems: Flow shop and job shop scheduling cases. Information Sciences, 276, 204\u2013218.","journal-title":"Information Sciences"},{"key":"1888_CR7","first-page":"1196","volume":"2010","author":"S Cong","year":"2010","unstructured":"Cong, S., Li, G., & Feng, X. (2010). An improved algorithm of chaos optimization. IEEE ICCA, 2010, 1196\u20131200.","journal-title":"IEEE ICCA"},{"key":"1888_CR8","doi-asserted-by":"crossref","unstructured":"Dabah, A., Bendjoudi, A., AitZai, A., El-Baz, D., & Nouali Taboudjemat, N. (2016). Multi and many-core parallel B&B approaches for the blocking job shop scheduling problem. In 2016 IEEE international conference on high performance computing simulation (HPCS) (pp. 705\u2013712).","DOI":"10.1109\/HPCSim.2016.7568404"},{"issue":"5","key":"1888_CR9","doi-asserted-by":"publisher","first-page":"849","DOI":"10.1007\/s10845-013-0804-4","volume":"25","author":"M Gen","year":"2014","unstructured":"Gen, M., & Lin, L. (2014). Multiobjective evolutionary algorithm for manufacturing scheduling problems: State-of-the-art survey. Journal of Intelligent Manufacturing, 25(5), 849\u2013866.","journal-title":"Journal of Intelligent Manufacturing"},{"key":"1888_CR10","doi-asserted-by":"crossref","unstructured":"Gong, G., Chiong, Q, Deng, R., & Luo, Q. (2020). A memetic algorithm for multi-objective distributed production scheduling: minimizing the makespan and total energy consumption. Journal of Intelligent Manufacturing, 1\u201324.","DOI":"10.1007\/s10845-019-01521-9"},{"issue":"4","key":"1888_CR11","doi-asserted-by":"publisher","first-page":"541","DOI":"10.1007\/s12065-019-00255-0","volume":"12","author":"AM Ibrahim","year":"2019","unstructured":"Ibrahim, A. M., & Tawhid, M. A. (2019). A hybridization of cuckoo search and particle swarm optimization for solving nonlinear systems. Evolutionary Intelligence, 12(4), 541\u2013561.","journal-title":"Evolutionary Intelligence"},{"issue":"3","key":"1888_CR12","doi-asserted-by":"publisher","first-page":"354","DOI":"10.1016\/j.jcde.2018.10.006","volume":"6","author":"AM Ibrahim","year":"2019","unstructured":"Ibrahim, A. M., & Tawhid, M. A. (2019). A hybridization of differential evolution and monarch butterfly optimization for solving systems of nonlinear equations. Journal of Computational Design and Engineering, 6(3), 354\u2013367.","journal-title":"Journal of Computational Design and Engineering"},{"key":"1888_CR13","doi-asserted-by":"publisher","first-page":"74","DOI":"10.1016\/j.ijar.2020.01.012","volume":"120","author":"AM Ibrahim","year":"2020","unstructured":"Ibrahim, A. M., Tawhid, M. A., & Ward, R. K. (2020). A binary water wave optimization for feature selection. International Journal of Approximate Reasoning, 120, 74\u201391.","journal-title":"International Journal of Approximate Reasoning"},{"key":"1888_CR14","doi-asserted-by":"crossref","unstructured":"Ibrahim, A.\u00a0M., & Tawhid, M.\u00a0A. (2021). A new hybrid binary algorithm of bat algorithm and differential evolution for feature selection and classification. In Applications of bat algorithm and its variants (pp. 1\u201318). Springer.","DOI":"10.1007\/978-981-15-5097-3_1"},{"issue":"4","key":"1888_CR15","doi-asserted-by":"publisher","first-page":"258","DOI":"10.1287\/ijoc.13.4.258.9733","volume":"13","author":"V Jain","year":"2001","unstructured":"Jain, V., & Grossmann, I. E. (2001). Algorithms for hybrid milp\/cp models for a class of optimization problems. INFORMS Journal on Computing, 13(4), 258\u2013276.","journal-title":"INFORMS Journal on Computing"},{"issue":"03","key":"1888_CR16","doi-asserted-by":"publisher","first-page":"1850016","DOI":"10.1142\/S1469026818500165","volume":"17","author":"T Jiang","year":"2018","unstructured":"Jiang, T. (2018). A hybrid grey wolf optimization for job shop scheduling problem. International Journal of Computational Intelligence and Applications, 17(03), 1850016.","journal-title":"International Journal of Computational Intelligence and Applications"},{"key":"1888_CR17","doi-asserted-by":"publisher","first-page":"26231","DOI":"10.1109\/ACCESS.2018.2833552","volume":"6","author":"T Jiang","year":"2018","unstructured":"Jiang, T., & Zhang, C. (2018). Application of grey wolf optimization for solving combinatorial problems: Job shop and flexible job shop scheduling cases. IEEE Access, 6, 26231\u201326240.","journal-title":"IEEE Access"},{"key":"1888_CR18","unstructured":"Khadwilard, A., Chansombat, S., Thepphakorn, T., Thapatsuwan, P., Chainate, W., & Pongcharoen, P. (2011). Investigation of firefly algorithm parameter setting for solving job shop scheduling problems. Operation Research Network in Thailand, 89\u201397."},{"key":"1888_CR19","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1016\/j.swevo.2017.07.008","volume":"38","author":"S Khalilpourazari","year":"2018","unstructured":"Khalilpourazari, S., & Khalilpourazary, S. (2018). A robust stochastic fractal search approach for optimization of the surface grinding process. Swarm and Evolutionary Computation, 38, 173\u2013186.","journal-title":"Swarm and Evolutionary Computation"},{"key":"1888_CR20","doi-asserted-by":"crossref","unstructured":"Kommadath, R., & Kotecha, P. (2020) Scheduling of jobs on dissimilar parallel machine using computational intelligence algorithms (pp. 441\u2013464).","DOI":"10.1007\/978-3-030-26458-1_24"},{"key":"1888_CR21","doi-asserted-by":"crossref","unstructured":"Kuo, I.-H., Horng, S.-J., Lee, T.-L., Kao, C.-L., Lin, T.-W., Terano, T., & Pan, Y. (2009). An efficient flow-shop scheduling algorithm based on a hybrid particle swarm optimization model. Expert Systems with Applications,36(3), 7027\u20137032.","DOI":"10.1016\/j.eswa.2008.08.054"},{"issue":"10","key":"1888_CR22","first-page":"12","volume":"2","author":"T Lamoudan","year":"2011","unstructured":"Lamoudan, T., Khoukhi, F., Alaoui, A., & Boukachour, J. (2011). Flow shop scheduling problem with transportation times, two-robots and inputs\/outputs with limited capacity. International Journal of Intelligent Computing Research, 2(10), 12.","journal-title":"International Journal of Intelligent Computing Research"},{"key":"1888_CR23","unstructured":"Liang, J. J., Qu, B. Y., & Suganthan, P. N. (2013). Problem definitions and evaluation criteria for the cec 2014 special session and competition on single objective real-parameter numerical optimization. Technical Report: Zhengzhou University and Nanyang Technological University."},{"key":"1888_CR24","doi-asserted-by":"publisher","first-page":"14513","DOI":"10.1109\/ACCESS.2019.2892826","volume":"7","author":"Y Lu","year":"2019","unstructured":"Lu, Y., & Jiang, T. (2019). Bi-population based discrete bat algorithm for the low-carbon job shop scheduling problem. IEEE Access, 7, 14513\u201314522.","journal-title":"IEEE Access"},{"issue":"7\u20138","key":"1888_CR25","doi-asserted-by":"publisher","first-page":"1569","DOI":"10.1007\/s00521-014-1640-y","volume":"25","author":"S Mirjalili","year":"2014","unstructured":"Mirjalili, S., & Lewis, A. (2014). Adaptive gbest-guided gravitational search algorithm. Neural Computing and Applications, 25(7\u20138), 1569\u20131584.","journal-title":"Neural Computing and Applications"},{"key":"1888_CR26","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1016\/j.ins.2012.04.028","volume":"209","author":"Md Nasir","year":"2012","unstructured":"Nasir, Md., Das, Swagatam, Maity, Dipankar, Sengupta, Soumyadip, Halder, Udit, & Suganthan, P. N. (2012). A dynamic neighborhood learning based particle swarm optimizer for global numerical optimization. Information Sciences, 209, 16\u201336.","journal-title":"Information Sciences"},{"key":"1888_CR27","doi-asserted-by":"crossref","unstructured":"Pinedo, M., & Hadavi, K. (1992). Scheduling: theory, algorithms and systems development. In Operations research proceedings 1991 (pp. 35\u201342). Springer.","DOI":"10.1007\/978-3-642-46773-8_5"},{"issue":"5\u20136","key":"1888_CR28","doi-asserted-by":"publisher","first-page":"563","DOI":"10.1007\/s00170-005-0375-4","volume":"32","author":"M Saidi-Mehrabad","year":"2007","unstructured":"Saidi-Mehrabad, M., & Fattahi, P. (2007). Flexible job shop scheduling with tabu search algorithms. The international journal of Advanced Manufacturing technology, 32(5\u20136), 563\u2013570.","journal-title":"The international journal of Advanced Manufacturing technology"},{"key":"1888_CR29","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1016\/j.engappai.2017.04.018","volume":"63","author":"V Savsani","year":"2017","unstructured":"Savsani, V., & Tawhid, M. A. (2017). Non-dominated sorting moth flame optimization (ns-mfo) for multi-objective problems. Engineering Applications of Artificial Intelligence, 63, 20\u201332.","journal-title":"Engineering Applications of Artificial Intelligence"},{"issue":"3","key":"1888_CR30","doi-asserted-by":"publisher","first-page":"265","DOI":"10.3934\/mfc.2018012","volume":"1","author":"P Savsani","year":"2018","unstructured":"Savsani, P., & Tawhid, M. A. (2018). Discrete heat transfer search for solving travelling salesman problem. Mathematical Foundations of Computing, 1(3), 265.","journal-title":"Mathematical Foundations of Computing"},{"key":"1888_CR31","doi-asserted-by":"crossref","unstructured":"Taillard, E. (1993). Benchmarks for basic scheduling problems. European Journal of Operational Research, 64(2), 278 \u2013 285 (Project Management and Scheduling).","DOI":"10.1016\/0377-2217(93)90182-M"},{"issue":"3","key":"1888_CR32","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1007\/s12293-016-0180-7","volume":"8","author":"MA Tawhid","year":"2016","unstructured":"Tawhid, M. A., & Ali, A. F. (2016). A simplex social spider algorithm for solving integer programming and minimax problems. Memetic Computing, 8(3), 169\u2013188.","journal-title":"Memetic Computing"},{"key":"1888_CR33","doi-asserted-by":"crossref","unstructured":"Tawhid, M. A., & Ali, A. F. (2017a). A hybrid social spider optimization and genetic algorithm for minimizing molecular potential energy function. Soft Computing, 21(21), 6499\u20136514.","DOI":"10.1007\/s00500-016-2208-9"},{"key":"1888_CR34","doi-asserted-by":"crossref","unstructured":"Tawhid, M. A., & Ali, A. F. (2017b). Multi-directional bat algorithm for solving unconstrained optimization problems. OPSEARCH, 54(4), 684\u2013705.","DOI":"10.1007\/s12597-017-0302-0"},{"key":"1888_CR35","doi-asserted-by":"crossref","unstructured":"Tawhid, M. A., & Ali, A. F. (2017c). A simplex grey wolf optimizer for solving integer programming and minimax problems. Numerical Algebra, Control & Optimization, 7(3), 301\u2013323.","DOI":"10.3934\/naco.2017020"},{"key":"1888_CR36","doi-asserted-by":"crossref","unstructured":"Tawhid, M. A., & Ibrahim, A. M. (2020a). A hybridization of grey wolf optimizer and differential evolution for solving nonlinear systems. Evolving Systems, 11(1), 65\u201387.","DOI":"10.1007\/s12530-019-09291-8"},{"key":"1888_CR37","doi-asserted-by":"crossref","unstructured":"Tawhid, M. A., & Ibrahim, A. M. (2020b). Feature selection based on rough set approach, wrapper approach, and binary whale optimization algorithm. International Journal of Machine Learning and Cybernetics, 11(3), 573\u2013602.","DOI":"10.1007\/s13042-019-00996-5"},{"key":"1888_CR38","doi-asserted-by":"crossref","unstructured":"Tawhid, M. A., & Savsani, P. (2019a). Discrete sine-cosine algorithm (dsca) with local search for solving traveling salesman problem. Arabian Journal for Science and Engineering, 44(4), 3669\u20133679.","DOI":"10.1007\/s13369-018-3617-0"},{"key":"1888_CR39","doi-asserted-by":"crossref","unstructured":"Tawhid, M. A., & Savsani, V. (2019b). Multi-objective sine-cosine algorithm (mo-sca) for multi-objective engineering design problems. Neural Computing and Applications, 31(2), 915\u2013929.","DOI":"10.1007\/s00521-017-3049-x"},{"key":"1888_CR40","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1016\/j.asoc.2015.03.003","volume":"31","author":"SA Uymaz","year":"2015","unstructured":"Uymaz, S. A., Tezel, G., & Yel, E. (2015). Artificial algae algorithm (aaa) for nonlinear global optimization. Applied Soft Computing, 31, 153\u2013171.","journal-title":"Applied Soft Computing"},{"issue":"3","key":"1888_CR41","doi-asserted-by":"publisher","first-page":"707","DOI":"10.1007\/s10845-020-01697-5","volume":"32","author":"X Wu","year":"2021","unstructured":"Wu, X., Peng, J., Xiao, X., & Wu, S. (2021). An effective approach for the dual-resource flexible job shop scheduling problem considering loading and unloading. Journal of Intelligent Manufacturing, 32(3), 707\u2013728.","journal-title":"Journal of Intelligent Manufacturing"},{"key":"1888_CR42","doi-asserted-by":"crossref","unstructured":"Xinyi, S., Aimin, W., Yan, G., & Jieran, Y. (2020). Job shop scheduling problem with job sizes and inventories. In 2020 IEEE 11th international conference on mechanical and intelligent manufacturing technologies (ICMIMT) (pp. 202\u2013206).","DOI":"10.1109\/ICMIMT49010.2020.9041174"},{"key":"1888_CR43","doi-asserted-by":"crossref","unstructured":"Xu, H., Liu, X., & Su, J. (2017). An improved grey wolf optimizer algorithm integrated with cuckoo search. In 2017 9th IEEE international conference on intelligent data acquisition and advanced computing systems: Technology and applications (IDAACS) (Vol.\u00a01, pp. 490\u2013493).","DOI":"10.1109\/IDAACS.2017.8095129"},{"key":"1888_CR44","unstructured":"Yang, X. S. (2010). Nature-inspired metaheuristic algorithms. Luniver Press."},{"issue":"4","key":"1888_CR45","doi-asserted-by":"publisher","first-page":"1229","DOI":"10.1016\/j.cnsns.2013.08.017","volume":"19","author":"D Yang","year":"2014","unstructured":"Yang, D., Liu, Z., & Zhou, J. (2014). Chaos optimization algorithms based on chaotic maps with different probability distribution and search speed for global optimization. Communications in Nonlinear Science and Numerical Simulation, 19(4), 1229\u20131246.","journal-title":"Communications in Nonlinear Science and Numerical Simulation"},{"issue":"3\u20134","key":"1888_CR46","doi-asserted-by":"publisher","first-page":"348","DOI":"10.1007\/s00170-007-1104-y","volume":"38","author":"K-C Ying","year":"2008","unstructured":"Ying, K.-C. (2008). Solving non-permutation flowshop scheduling problems by an effective iterated greedy heuristic. The International Journal of Advanced Manufacturing Technology, 38(3\u20134), 348.","journal-title":"The International Journal of Advanced Manufacturing Technology"},{"issue":"1","key":"1888_CR47","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.cie.2009.01.016","volume":"58","author":"C Zhang","year":"2010","unstructured":"Zhang, C., Ning, J., & Ouyang, D. (2010). A hybrid alternate two phases particle swarm optimization algorithm for flow shop scheduling problem. Computers& Industrial Engineering, 58(1), 1\u201311.","journal-title":"Computers & Industrial Engineering"}],"container-title":["Journal of Intelligent Manufacturing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10845-021-01888-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10845-021-01888-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10845-021-01888-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,3,15]],"date-time":"2023-03-15T17:13:26Z","timestamp":1678900406000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10845-021-01888-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,10]]},"references-count":47,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2023,4]]}},"alternative-id":["1888"],"URL":"https:\/\/doi.org\/10.1007\/s10845-021-01888-8","relation":{},"ISSN":["0956-5515","1572-8145"],"issn-type":[{"value":"0956-5515","type":"print"},{"value":"1572-8145","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,10]]},"assertion":[{"value":"25 December 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 November 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 January 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}