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Citations Report
 
 
Cited Paper
[Jrnl 1]Efficient Generation of Near Optimal Initial Populations to Enhance Genetic Algorithms for Job-Shop Scheduling
Author(s): Kuczapski, Artur M.; Micea, Mihai Victor; Maniu, Laurentiu A.; Cretu, Vladimir Ioan
In: Information Technology and Control
Volume 39, Issue 1
Editor(s): Seinauskas, Rimantas; Rubliauskas, Dalius; Telksnys, Laimutis
Publisher: Kaunas University of Technology
Kaunas, Lithuania, 2010
Pages: 32 - 37, Online, ISSN 1392-124X
Indexed: ISI Web of Science, Thomson Reuters (WOS: 000275844300004), IF: 0.88
44
 [+] Keywords | [+] Abstract | Cover picture | Journal info
Genetic algorithms; Job-shop scheduling; Initial populations; Chromosomes
This paper presents an efficient method of enhancing genetic algorithms (GAs) for solving the Job-Shop Scheduling Problem (JSSP), by generating near optimal initial populations. Since the choice of the initial population has a high impact on the speed of the evolution and the quality of the final results, we focused on generating its individuals using genetically evolved priority dispatching rules. Our experiments show a significant increase in quality and speed of scheduling with GAs, and in some cases the evolved priority rules alone determined better solutions then the GA itself. The analyzed reference GA uses Giffler & Thompson (GT) heuristic and priority lists. To speed up the generation of priority rules, we have used a weighted sum of priority rules formula that revealed significantly better performances than Genetic Programming (GP). For evaluation of the proposed algorithm, the well known benchmark data sets from Fisher & Thompson (F&T) and Laurence Kramer (LA) have been used.
28 Citations in total (with a cummulated IF: 26.297)
 
 
Citing papers
[Jrnl 28]M. Habib Zahmani, B. Atmani, "Multiple dispatching rules allocation in real time using data mining, genetic algorithms, and simulation", J Sched., vol. 24 (2), Springer, USA, Apr. 2021, pp. (175 - 196), ISSN 1094-6136, DOI: 10.1007/s10951-020-00664-5. [Indexed: ISI Web of Science, Clarivate Analytics].
[Jrnl 27]I. Vlasic, M. Durasevic, D. Jakobovic, "Improving genetic algorithm performance by population initialisation with dispatching rules", Comput. lnd. Eng., vol. 137, Pergamon-Elsevier Science Ltd., Oxford, UK, Nov. 2019, pp. (1 - 15), ISSN 0045-7906, DOI: 10.1016/j.cie.2019.106030. [Indexed: ISI Web of Science, Thomson Reuters].
[Conf 26]S. Yu, "Differential Evolution Quantum Particle Swarm Optimization for Solving Job-shop Scheduling Problem", in Proc. Chinese Contr. Decision C, CCDC 2019, IEEE, China, 03-05 Jun., 2019, pp. (559 - 564), ISBN 978-1-7281-0105-7, DOI: 10.1109/CCDC.2019.8833361. [Indexed: Scopus, Elsevier].
[Jrnl 25]J. Zhang, G. Ding, Y. Zou, S. Qin, J. Fu, "Review of job shop scheduling research and its new perspectives under Industry 4.0", J Intell. Manuf., vol. 30 (4), Springer, The Netherlands, Apr. 2019, pp. (1809 - 1830), ISSN 0956-5515, DOI: 10.1007/s10845-017-1350-2. [Indexed: ISI Web of Science, Thomson Reuters].
[BChp 24]S. Nguyen, M. Zhang, M. Johnston, K. C. Tan, "Genetic Programming for Job Shop Scheduling", in Studies in Computational Intelligence, vol. 779, Springer, The Netherlands, 2019, pp. (143 - 167), ISSN 1860-949X, DOI: 10.1007 /978-3-319-91341-4_8. [Indexed: ISI Web of Science, Thomson Reuters].
[Jrnl 23]V. Guliashki, L. Kirilov, "Algorithm Generating Initial Population of Schedules for Population-Based Algorithms Solving Flexible Job Shop Problems", C. R. Acad. Bulg. Sci., vol. 72 (6), Publ. House Bulgarian Acad. Sci., Sofia, BG, 2019, pp. (699 - 710), ISSN 1310-1331, DOI: 10.7546/CRABS.2019.06.01. [Indexed: ISI Web of Science, Thomson Reuters].
[Jrnl 22]S. Shukor, I. Shaheed, S. Abdullah, "Population initialisation methods for fuzzy job-shop scheduling problems: Issues and future trends", Int J Adv. Sci. Eng. Inf. Technol., vol. 8 (4), Insight Society, Padang, Indonesia, Aug. 2018, pp. (1820 - 1828), ISSN 2088-5334. [Indexed: Scopus, Elsevier].
[Jrnl 21]L. A. Son, H. Aoki, T. Suzuki, "Evaluation of Driver Distraction with Changes in Gaze Direction Based on a Vestibulo-Ocular Reflex Model", J Transport. Tech., vol. 7, Scientific Research Publishing, Wuhan, China, Jul. 2017, pp. (336 - 350), ISSN 2160-0473, DOI: 10.4236/jtts.2017.73022.
[Jrnl 20]S. Nguyen, Y. Mei, M. Zhang, "Genetic programming for production scheduling: a survey with a unified framework", Complex Intell. Syst., vol. 3 (1), Springer Heidelberg, Heidelberg, GE, Mar. 2017, pp. (41 - 66), ISSN 2199-4536, DOI: 10.1007/s40747-017-0036-x. [Indexed: ISI Web of Science, Thomson Reuters].
[Jrnl 19]I. M. Shaheed, A. S. Syaimak, B. N. Erna, "An empirical analysis of the relationship between the initialization method performance and the convergence speed of a meta-heuristic for Fuzzy Job-Shop scheduling problems", J Theor. Applied Inf. Tech., vol. 93 (2), Little Lion Scientific, Islamabad, Pakistan, Nov. 2016, pp. (297 - 311), ISSN 1992-8645. [Indexed: Scopus, Elsevier].
[Jrnl 18]M. Abdolrazzagh-Nezhad, E. B. Nababan, N. S. Jaddi, H. M. Sarim, "Electromagnetic-like mechanism for job-shop scheduling by novel heuristic initialization", J Theor. Applied Inf. Tech., vol. 93 (1), Little Lion Scientific, Islamabad, Pakistan, Nov. 2016, pp. (174 - 184), ISSN 1992-8645. [Indexed: Scopus, Elsevier].
[Conf 17]J. Li, G. Chen, J. Li, R. Wang, "Availability Evaluation and Design Optimization of Multi-state Weighted k-out-of-n Systems", in Proc. IEEE Prognostics Syst. Health Manag. C, PHM-CHENGDU 2016, IEEE, Chengdu, China, 19-21 Oct., 2016, pp. (1 - 6), ISBN 978-1-5090-2778-1, ISSN 2166-5656, DOI: 10.1109/PHM.2016.7819791. [Indexed: ISI Web of Science, Thomson Reuters].
[Conf 16]B. Waschneck, T. Bauernhansl, T. Altenmuller, A. Kyek, "Production Scheduling in Complex Job Shops from an Industrie 4.0 Perspective: A Review and Challenges in the Semiconductor Industry", in Proc. SAMI@ iKNOW 2016, SAMI@ iKNOW 2016, Graz, AT, 18-19 Oct., 2016, pp. (1 - 12), ISSN 1613-0073. [Indexed: Scopus, Elsevier].
[Conf 15]A. Masood, Y. Mei, G. Chen, M. Zhang, "Many-Objective Genetic Programming for Job-Shop Scheduling", in Proc. IEEE Congress Evol. Comput., CEC 2016, IEEE, Vancouver, Canada, 24-29 Jul., 2016, pp. (1 - 8), ISBN 978-1-5090-0622-9. [Indexed: ISI Web of Science, Thomson Reuters].
[Jrnl 14]V. S. Jorapur, V. S. Puranik, A. S. Deshpande, M. Sharma, "A Promising Initial Population Based Genetic Algorithm for Job Shop Scheduling Problem", J Soft. Eng. Applic., vol. 9, Scientific Research Publishing, Wuhan, China, May. 2016, pp. (208 - 214), ISSN 1945-3116.
[Jrnl 13]J. Branke, . Su Nguyen, C. W. Pickardt, M. Zhang, "Automated Design of Production Scheduling Heuristics: A Review", IEEE Trans. Evol. Comput., vol. 20 (1), IEEE, USA, Feb. 2016, pp. (110 - 124), ISSN 1089-778X, DOI: 10.1109/TEVC.2015.2429314. [Indexed: ISI Web of Science, Thomson Reuters].
[Jrnl 12]A. Turkyilmaz, S. Bulkan, "A hybrid algorithm for total tardiness minimisation in flexible job shop: genetic algorithm with parallel VNS execution", Int. J Prod. Res., vol. 53 (6), Taylor & Francis Ltd., Oxon, UK, Mar. 2015, pp. (1832 - 1848), ISSN 0020-7543, DOI: 10.1080/00207543.2014.962113. [Indexed: ISI Web of Science, Thomson Reuters].
[Jrnl 11]G. Foster, C. Turner, S. Ferguson, J. Donndelinger, "Creating targeted initial populations for genetic product searches in heterogeneous markets", Eng. Optimiz., vol. 46 (12), Taylor & Francis Ltd., Oxon, UK, Dec. 2014, pp. (1729 - 1747), ISSN 0305-215X, DOI: 10.1080/0305215X.2013.861458. [Indexed: ISI Web of Science, Thomson Reuters].
[Jrnl 10]S. Abdullah, M. Abdolrazzagh-Nezhad, "Fuzzy job-shop scheduling problems: A review", Inform. Sciences, vol. 278, Elsevier Science B.V., The Netherlands, Sep. 2014, pp. (380 - 407), ISSN 0020-0255, DOI: 10.1016/j.ins.2014.03.060. [Indexed: ISI Web of Science, Thomson Reuters].
[Jrnl 9]M. Abdolrazzagh-Nezhad, S. Abdullah, "Robust Intelligent Construction Procedure for Job-Shop Scheduling", Inf. Tech. Control, vol. 43 (3), Kaunas University of Technology, Kaunas, Lithuania, Sep. 2014, pp. (217 - 229), ISSN 1392-124X, DOI: 10.5755/j01.itc.43.3.3536. [Indexed: ISI Web of Science, Thomson Reuters].
[Jrnl 8]T. T. Dang, "Combination of dispatching rules and prediction for solving multi-objective scheduling problems", Int. J Prod. Res., vol. 51 (17), Taylor & Francis Ltd., Oxon, UK, Sep. 2013, pp. (5180 - 5194), ISSN 0020-7543, DOI: 10.1080/00207543.2013.793857. [Indexed: ISI Web of Science, Thomson Reuters].
[Jrnl 7]N. Nedic, G. Svenda, "Workflow Management System for DMS", Inf. Tech. Control, vol. 42 (4), Kaunas University of Technology, Kaunas, Lithuania, 2013, pp. (373 - 385), ISSN 1392-124X, DOI: 10.5755/j01.itc.42.4.4546. [Indexed: ISI Web of Science, Thomson Reuters].
[Conf 6]A. A. Boushaala, M. A. Shouman, S. Esheem, "Genetic Algorithm based on Some Heuristic Rules for Job Shop Scheduling Problem", in Proc. 3-rd Int. C Ind. Engl. Oper. Manag., IEOM 2012, IEOM Society, Istanbul, Turkey, 03-06 Jul., 2012, pp. (280 - 288), ISBN 978-0-9855497-0-1.
[Jrnl 5]Y. Liu, S. Sun, S. Yang, C. Chuang, "Application of genetic algorithm in production scheduling: A case study on the food processing business", Inform. J, vol. 15 (12 C), International Information Institute, Koganei, JP, Jan. 2012, pp. (6063 - 6075), ISSN 1343-4500. [Indexed: Scopus, Elsevier].
[Conf 4]R. Milimonfared, R. M. Marian, Z. Hajiabolhasani, "A Genetic Algorithm Approach for Modelling and Optimisation of MAJSP - Part II: GA operators and results", in Proc. IEEE Int. C Ind. Eng. and Eng. Manag., IEEM 2011, IEEE, Singapore, 06-09 Dec., 2011, pp. (1279 - 1283), ISBN 978-1-4577-0740-7, ISSN 2157-3611, DOI: 10.1109/IEEM.2011.6118122. [Indexed: ISI Web of Science, Thomson Reuters].
[Jrnl 3]H. Cao, L. Jia, G. Si, Y. Zhang, "A Variable Selection Method for Pulverizing Capability Prediction of Tumbling Mill Based on Improved Hybrid Genetic Algorithm", Inf. Tech. Control, vol. 40 (3), Kaunas University of Technology, Kaunas, Lithuania, 2011, pp. (210 - 217), ISSN 1392-124X. [Indexed: ISI Web of Science, Thomson Reuters].
[Conf 2]Y. C. Liu, S. M. Yang, C. Y. Chuang, "On the Improvement of Binary Genetic Algorithms with Experienced Priority Rules in Project Scheduling", in Proc. Int. C Logistics Transp. and Int. C Business Econ., ICLT_ICBE 2010, UP Organizer and Publication Co., Queenstown, New Zealand, 16-18 Dec., 2010, pp. (1 - 7), ISBN 978-974-11-1350-7.
[Jrnl 1]N. Nedic, S. Vukmirovic, A. Erdeljan, L. Imre, D. Capko, "A Genetic Algorithm Approach for Utility Management System Workflow Scheduling", Inf. Tech. Control, vol. 39 (4), Kaunas University of Technology, Kaunas, Lithuania, 2010, pp. (310 - 316), ISSN 1392-124X. [Indexed: ISI Web of Science, Thomson Reuters].