Abstract
Assembly line balancing problem is the process of assigning a set of tasks to a group of stations, considering the precedence relations between tasks. Precedence relations are commonly definite; however, tasks may have alternative precedence relations due to different mounting alternatives. In the presence of alternative precedence relations, the classical balancing problem becomes more complicated given that two interdependent problems, namely selection and balancing, must be solved hierarchically. This type of balancing problem is named as the Alternative Subgraph Assembly Line Balancing Problem (ASALBP). This current paper concerns itself to develop an efficient solution procedure for the ASALBP by hybridizing the firefly and bat algorithms. The proposed hybrid algorithm is evaluated on a set of benchmark problems taken from the related literature and numerically compared against the standard firefly and bat algorithms, and some formerly developed heuristic methods. Computational results reveal the satisfactory performance of the proposed algorithm in solving ASALBP instances.
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Abbreviations
- ASALBP:
-
Alternative subgraph assembly line balancing problem
- ALBP:
-
Assembly line balancing problem
- SALBP:
-
Simple assembly line balancing problem
- GALBP:
-
Generalized assembly line balancing problem
- GRASP:
-
Greedy randomized adaptive search procedure
- FA:
-
Firefly algorithm
- BA:
-
Bat algorithm
- HFAB:
-
Hybrid firefly and bat
- ALBESP:
-
Assembly line balancing and equipment selection problem
References
Scholl A (1999) Balancing and sequencing assembly lines, 2nd edn. Physica-Verlag HD, Heidelberg
Baybars I (1986) A survey of exact algorithms for the simple assembly line balancing problem. Manage Sci 32:909–932. https://doi.org/10.1287/mnsc.32.8.909
Becker C, Scholl A (2006) A survey on problems and methods in generalized assembly line balancing. Eur J Oper Res 168(3):694–715. https://doi.org/10.1016/j.ejor.2004.07.023
Boysen N, Fliedner M, Scholl A (2007) A classification of assembly line balancing problems. Eur J Oper Res 183:674–693. https://doi.org/10.1016/j.ejor.2006.10.010
Battaïa O, Dolgui A (2013) A taxonomy of line balancing problems and their solutionapproaches. Int J Prod Econ 142(2):259–277. https://doi.org/10.1016/j.ijpe.2012.10.020
Pinto P, Dannenbring D, Khumawala B (1983) Assembly line balancing with processing alternatives: an application. Manage Sci 29:817–830. https://doi.org/10.1287/mnsc.29.7.817
Das S, Nagendra P (1997) Selection of routes in a flexible manufacturing facility. Int J Prod Econ 48:237–247. https://doi.org/10.1016/S0925-5273(96)00106-5
Bukchin J, Tzur M (2000) Designs of flexible assembly line minimize equipment cost. Institute Ind Eng Transact 32:585–598. https://doi.org/10.1080/07408170008967418
Senin N, Gropetti R, Wallace DR (2000) Concurrent assembly planning with genetic algorithms. Robot Comput Integrat Manuf 16:65–72. https://doi.org/10.1016/S0736-5845(99)00058-7
Capacho L, Pastor R (2005) ASALBP: The alternative subgraphs assembly line balancing problem. Technical Report: IOC−DT−P−2005−5. UPC. Barcelona, Spain
Capacho L, Pastor R (2008) ASALBP: The alternative subgraphs assembly line balancing problem. Int J Prod Res 46(13):3503–3516. https://doi.org/10.1080/00207540701197010
Yang XS (2008) Nature – inspired metaheuristic algorithm, 2nd edn. Luniver Press, England
Yang XS (2010) A new metaheuristic bat-inspired algorithm. In Nature inspired cooperative strategies for optimization (NICSO 2010) (pp. 65–74). Springer, Berlin, Heidelberg
Capacho L, Pastor R (2006) The ASALB problem with processing alternatives involving different tasks: definition, formalization and resolution. In International Conference on Computational Science and Its Applications (pp. 554–563). Springer, Berlin, Heidelberg
Park K, Park S, Kim W (1997) A heuristic for an assembly line balancing problem with incompatibility, range, and partial precedence constraints. Comput Ind Eng 32(2):321–332. https://doi.org/10.1016/S0360-8352(96)00301-4
Capacho L, Pastor R, Guschinskaya O, Dolgui A (2006) Heuristic methods to solve the alternative subgraphs assembly line balancing problem. In 2006 IEEE international conference on automation science and engineering (pp. 501–506). IEEE
Capacho L, Guschinskaya O, Dolgui A, Pastor R (2006) Approximation methods to solve the alternative subgraphs assembly line balancing problem. Technical Report G2I-EMSE 2006–500–003, Ecole des Mines de Saint Etienne, France
Capacho L, Guschinskaya O, Dolgui A, Pastor R (2006) A comprehensive comparative analysis of heuristic methods for the alternative subgraphs assembly line balancing problem. Research Report: G2I-EMSE 2006–500–005, Ecole des Mines de Saint Etienne, France.
Capacho L, Pastor R, Dolgui A, Guschinskaya O (2009) An evaluation of constructive heuristic methods for solving the alternative subgraphs assembly line balancing problem. J Heurist 15(2):109–132. https://doi.org/10.1007/s10732-007-9063-x
Scholl A, Boysen N, Fliedner M (2009) Optimally solving the alternative subgraphs assembly line balancing problem. Ann Oper Res 172:243–258. https://doi.org/10.1007/s10479-009-0578-4
Capacho L, Pastor R (2011) A metaheuristic approach to solve the alternative subgraphs assembly line balancing problem. In Assembly Line-Theory and Practice (pp. 554–563). IntechOpen
Leiber D, Vuong AT, Reinhart G (2022) Alternative subgraphs assembly line balancing problem with resource selection and parallel stations. Eng Optim 54(11):1903–1918. https://doi.org/10.1080/0305215X.2021.1964493
Agarwal T, Kumar V (2022) A systematic review on bat algorithm: Theoretical foundation, variants, and applications. Arch Comput Methods Eng 29:2707–2736. https://doi.org/10.1007/s11831-021-09673-9
Kumar V, Kumar D (2021) A systematic review on firefly algorithm: past, present, and future. Arch Comput Methods Eng 28:3269–3291. https://doi.org/10.1007/s11831-020-09498-y
Oesterle J, Amodeo L, Yalaoui F (2019) A comparative study of multi-objective algorithms for the assembly line balancing and equipment selection problem under consideration of product design alternatives. J Intell Manuf 30:1021–1046. https://doi.org/10.1007/s10845-017-1298-2
Battaïa O, Dolgui A (2022) Hybridizations in line balancing problems: a comprehensive review on new trends and formulations. Int J Prod Econ 50:108673. https://doi.org/10.1016/j.ijpe.2022.108673
Arunarani AR, Manjula D, Sugumaran V (2017) FFBAT: A security and cost-aware workflow scheduling approach combining firefly and bat algorithms. Concurrency Comput Pract Exper 29(24):e4295. https://doi.org/10.1002/cpe.4295
Sureshkumar T, Lingaraj M, Anand B, Premkumar T (2018) Hybrid firefly bat algorithm (HFBA)–based network security policy enforcement for PSA. Int J Commun Syst 31(14):e3740. https://doi.org/10.1002/dac.3740
Chen G, Qian J, Zhang Z, Sun Z (2019) Multi-objective optimal power flow based on hybrid firefly-bat algorithm and constraints-prior object-fuzzy sorting strategy. IEEE Access 7:139726–139745. https://doi.org/10.1109/ACCESS.2019.2943480
Guo L, Wang G-G, Wang H, Wang D (2013) An effective hybrid firefly algorithm with harmony search for global numerical optimization. Scient World J Article ID 125625, 9 pages. https://doi.org/10.1155/2013/125625
Yang XS, He X (2013) Bat algorithm: literature review and applications. Int J Bio-inspir Comput 5(3):141–149. https://doi.org/10.1504/IJBIC.2013.055093
Helgeson WB, Birnie DP (1961) Assembly line balancing using the ranked positional weight technique. J Ind Eng 12(6):394–398
Taguchi G (1986) Introduction to Quality engineering: designing quality into products and processes, 1st ed., White Plains: Asian Productivity Organization
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Ümmühan Palamut: Conceptualization, Methodology, Software, Data curation, Writing- Original draft preparation, Validation, Writing- Reviewing and Editing. Şener Akpinar: Conceptualization, Methodology, Software, Data curation, Writing- Original draft preparation, Validation, Writing- Reviewing and Editing, Supervision.
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Palamut, Ü., Akpinar, Ş. A hybrid metaheuristic based on the firefly and bat algorithms to solve the alternative subgraphs assembly line balancing problem. Prod. Eng. Res. Devel. (2023). https://doi.org/10.1007/s11740-023-01246-y
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DOI: https://doi.org/10.1007/s11740-023-01246-y