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Year 2024, Volume: 1 Issue: 1, 1 - 10, 26.04.2024

Abstract

References

  • [1] D T Pham, A Ghanbarzadeh, E Koc, S Otri, S Rahim and M Zaidi (2005) The Bees Algorithm, Technical Note, Manufacturing Engineering Centre, Cardiff University, UK
  • [2] D T Pham, A Ghanbarzadeh, E Koç, S Otri, S Rahim and M Zaidi (2006). The Bees Algorithm - a novel tool for complex optimisation problems, Proceedings of the 2nd Virtual International Conference on Intelligent Production Machines and Systems, D T Pham, E E Eldukhri and A J Soroka (eds), Elsevier (Oxford) (2006), 454-460, ISBN 0-08-045157-8
  • [3] Q T Pham, D T Pham and M Castellani (2012). A modified bees algorithm and a statistics-based method for tuning its parameters, Proceedings of Institution of Mechanical Engineers, Part I, Volume 226, 287-301, ISSN 0954-4054
  • [4] M C Ang, D T Pham and K W Ng (2009). Application of the Bees Algorithm with TRIZ-inspired operators for PCB assembly planning, Proceedings of the 5th Virtual International Conference on Innovative Production Machines and Systems, D T Pham, E E Eldukhri and A J Soroka (eds), Whittles (Dunbeath, Caithness) and CRC Press (Boca Raton, FL), 405-410, ISBN 978-1-84995-007-7W
  • [5] D T Pham and A Haj Darwish (2010). Using the Bees Algorithm with Kalman filtering to train an Artificial Neural Network for Pattern Classification, Proceedings of Institution of Mechanical Engineers, Part I, Volume 224, 885-892, ISSN 0959 6518
  • [6] A Hussein, S Sahran and S N H Sheikh Abdullah (2017). The variants of the Bees Algorithm (BA): a survey. Artif Intell Rev, 47, 67–121.
  • [7] A H Ismail (2021). Enhancing the Bees Algorithm using the Traplining Metaphor, PhD Thesis, University of Birmingham, UK.
  • [8] M Packianather, M Landy and D T Pham (2009). Enhancing the speed of the Bees Algorithm using pheromone-based recruitment classifiers, Proc IEEE 7th International Conference on Industrial Informatics (INDIN 2009), Cardiff, UK, 789-794, ISBN: 978-142443760-3
  • [9] D T Pham and M Sholedolu (2008). Using a hybrid PSO-Bees Algorithm to train neural networks for wood defect classification, Proceedings of the 4th Virtual International Conference on Innovative Production Machines and Systems, D T Pham, E E Eldukhri and A J Soroka (eds), Whittles (Dunbeath, Caithness) and CRC Press (Boca Raton, FL), 385-390, ISBN 978-1-4398-0117-8
  • [10] A T Sadiq and A G Hamad (2010). BSA: A hybrid bees’ simulated annealing algorithm to solve optimization and NP-complete problems. Eng. & Tech. Journal, 28(2), 271-281
  • [11] M A Masmoudi, M Hosny, K Braekers and A Dammak (2016). Three effective metaheuristics to solve the multi-depot multi-trip heterogeneous dial-a-ride problem, Transportation Research Part E: Logistics and Transportation Review, 96, 60-80, ISSN 1366-5545, https://doi.org/10.1016/j.tre.2016.10.002
  • [12] T T M Anh and T D Vi (2023). Hybrid Genetic-Bees Algorithm in Multi-layer Perceptron Optimization. In: Saraswat, M., Chowdhury, C., Kumar Mandal, C., Gandomi, A.H. (eds) Proceedings of International Conference on Data Science and Applications. Lecture Notes in Networks and Systems, 552, Springer, Singapore. https://doi.org/10.1007/978-981-19-6634-7_11
  • [13] J Gholami and S Mohammadi (2018). A Novel Combination of Bees and Firefly Algorithm to Optimize Continuous Problems, Proceedings of 8th International Conference on Computer and Knowledge Engineering (ICCKE), Mashhad, Iran, 40-46, https://doi.org/10.1109/ICCKE.2018.8566263
  • [14] H Deghbouch and F Debbat (2022). Hybrid algorithm for node deployment with the guarantee of connectivity in wireless sensor networks, Informatica, 46(8), 147-164, https://doi.org/10.31449/inf.v46i8.3370
  • [15] H B Tolabi, M H Ali, S B M Ayob and M Rizwan (2014). Novel hybrid fuzzy-Bees algorithm for optimal feeder multi-objective reconfiguration by considering multiple-distributed generation, Energy, 71, 507-515, https://doi.org/10.1016/j.energy.2014.04.099
  • [16] S Ebrahimpoor, V Kiarostami, M Khosravi, M Davallo and A Ghaedi (2019). Bees metaheuristic algorithm with the aid of artificial neural networks for optimization of acid red 27 dye adsorption onto novel polypyrrole/SrFe12O19/graphene oxide nanocomposite. Polym. Bull., 76, 6529–6553, https://doi.org/10.1007/s00289-019-02700-7
  • [17] O Abdusalam, F Anayi and M Packianather (2023). Three-Phase Power Transformer Fault Diagnosis Based on Support Vector Machines and Bees Algorithm, Proceedings 2023 IEEE 3rd International Conference in Power Engineering Applications (ICPEA), Putrajaya, Malaysia, 145-150, https://doi.org/10.1109/ICPEA56918.2023.10093147
  • [18] N M H Alamri, M Packianather and S Bigot (2022). Deep Learning: Parameter Optimization Using Proposed Novel Hybrid Bees Bayesian Convolutional Neural Network, Applied Artificial Intelligence, 36(1), https://doi.org/10.1080/08839514.2022.2031815
  • [19] Y Song, L Xing and Y Chen (2023). Application of the dual-population Bees Algorithm in a parallel machine scheduling problem with a time window. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_14
  • [20] A H Ismail, W Ruslan and D T Pham (2023). A user-friendly Bees Algorithm for continuous and combinatorial optimisation, Cogent Engineering, 10:2, https://doi.org/10.1080/23311916.2023.2278257
  • [21] Y Laili, F Tao, D T Pham, Y Wang and L Zhang (2019). Robotic disassembly re-planning using a two-pointer detection strategy and a super-fast bees algorithm, Robotics and Computer-Integrated Manufacturing, 59, 130-142, https://doi.org/10.1016/j.rcim.2019.04.00
  • [22] M Packianather, T Alexopoulos and S Squire, S. (2023). The application of the Bees Algorithm in a digital twin for optimising the wire electrical discharge machining (WEDM) process parameters. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_3
  • [23] S Conte and D M d’Addona (2023). Bees Algorithm models for the identification and measurement of tool wear. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_7
  • [24] M Ay, A Baykasoglu, L Ozbakir and S Kulluk (2023). A case study with the BEE-Miner Algorithm: defects on the production line. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_4
  • [25] S Zeybek (2023). Prediction of the remaining useful life of engines for remanufacturing using a semi-supervised deep learning model trained by the Bees Algorithm. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_21
  • [26] N Shatnawi, S Sahran and M F Nasrudin (2023). Memory-based Bees Algorithm with Lévy Flights for multilevel image thresholding. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_11
  • [27] M Castellani, L Baronti, S Zheng and F Lan (2023). Shape recognition for industrial robot manipulation with the Bees Algorithm. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_6
  • [28] F Lan, M Castellani, Y Wang and S Zheng (2023). Global optimisation for point cloud registration with the Bees Algorithm. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_8
  • [29] O Öztürk, M A Şen, M Kalyoncu and H S Halkacı (2023). An application of the Bees Algorithm to pulsating hydroforming. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_5
  • [30] M Şahin and S Çakıroğlu (2023). Automatic PID tuning toolkit using the Multi-Objective Bees Algorithm. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_9
  • [31] M Kashkash, A Haj Darwish and A Joukhadar (2023). Α new method to generate the initial population of the Bees Algorithm for robot path planning in a static environment. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_12
  • [32] O Acar, H Sağlam and Z Şaka (2023). The effect of Harmony Memory integration into the Bees Algorithm. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_10
  • [33] M C Ang and K W Ng (2023). Minimising printed circuit board assembly time using the Bees Algorithm with TRIZ-inspired operators. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_2
  • [34] C Wang, T Chen and Z Li (2023). Method for the production planning and scheduling of a flexible manufacturing plant based on the Bees Algorithm. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_13
  • [35] Y Li, C Peng, Y Laili and L Zhang (2023). A parallel multi-indicator-assisted dynamic Bees Algorithm for cloud-edge collaborative manufacturing task scheduling. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_15
  • [36] M Caterino, M Fera, R Macchiaroli and D T Pham (2023). Task optimisation for a modern cloud remanufacturing system using the Bees Algorithm. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_20
  • [37] J Liu, Q Liu, Z Zhou, D T Pham, W Xu and Y Fang (2023). Collaborative optimisation of robotic disassembly planning problems using the Bees Algorithm. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_18
  • [38] N Hartono, F Javier Ramírez and D T Pham (2023). Optimisation of robotic disassembly sequence plans for sustainability using the multi-objective Bees Algorithm. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_19
  • [39] E Mastrocinque (2023). Supply chain design and multi-objective optimisation with the Bees Algorithm. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_17
  • [40] A H Ismail and D T Pham (2023). Bees traplining metaphors for the Vehicle Routing Problem using a decomposition approach. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_16

The Bees Algorithm and Its Applications in Production and Manufacturing

Year 2024, Volume: 1 Issue: 1, 1 - 10, 26.04.2024

Abstract

Abstract— With the advent of the Fourth Industrial Revolution, production and manufacturing processes and systems have become more complex. Obtaining the best performance from them requires efficient and effective optimisation techniques that do not depend on the availability of process or system models. Such models are usually either not obtainable or mathematically intractable due to the high degrees of nonlinearities and uncertainties in the processes and systems to be represented. The Bees Algorithm is a powerful swarm-based intelligent optimisation metaheuristic inspired by the foraging behaviour of honeybees. The algorithm is conceptually elegant and extremely easy to apply. It has attracted users from virtually all fields of engineering and natural, physical, medical and social sciences. This article reviews the original Bees Algorithm and some of its recent enhancements and gives examples of its applications to optimisation problems in production and manufacturing. The aim is to demonstrate the simplicity, effectiveness and versatility of the algorithm and encourage its further adoption by engineers and researchers across the world to realise smart and sustainable manufacturing and production in the age of Industry 4.0 and beyond.

Thanks

The authors appreciate the invitation of the Editor-in-Chief Professor Dr. Güneş Gençyılmaz to write this paper. They also wish to thank all the researchers whose work is reported in the paper for their contributions to the development and application of the Bees Algorithm.

References

  • [1] D T Pham, A Ghanbarzadeh, E Koc, S Otri, S Rahim and M Zaidi (2005) The Bees Algorithm, Technical Note, Manufacturing Engineering Centre, Cardiff University, UK
  • [2] D T Pham, A Ghanbarzadeh, E Koç, S Otri, S Rahim and M Zaidi (2006). The Bees Algorithm - a novel tool for complex optimisation problems, Proceedings of the 2nd Virtual International Conference on Intelligent Production Machines and Systems, D T Pham, E E Eldukhri and A J Soroka (eds), Elsevier (Oxford) (2006), 454-460, ISBN 0-08-045157-8
  • [3] Q T Pham, D T Pham and M Castellani (2012). A modified bees algorithm and a statistics-based method for tuning its parameters, Proceedings of Institution of Mechanical Engineers, Part I, Volume 226, 287-301, ISSN 0954-4054
  • [4] M C Ang, D T Pham and K W Ng (2009). Application of the Bees Algorithm with TRIZ-inspired operators for PCB assembly planning, Proceedings of the 5th Virtual International Conference on Innovative Production Machines and Systems, D T Pham, E E Eldukhri and A J Soroka (eds), Whittles (Dunbeath, Caithness) and CRC Press (Boca Raton, FL), 405-410, ISBN 978-1-84995-007-7W
  • [5] D T Pham and A Haj Darwish (2010). Using the Bees Algorithm with Kalman filtering to train an Artificial Neural Network for Pattern Classification, Proceedings of Institution of Mechanical Engineers, Part I, Volume 224, 885-892, ISSN 0959 6518
  • [6] A Hussein, S Sahran and S N H Sheikh Abdullah (2017). The variants of the Bees Algorithm (BA): a survey. Artif Intell Rev, 47, 67–121.
  • [7] A H Ismail (2021). Enhancing the Bees Algorithm using the Traplining Metaphor, PhD Thesis, University of Birmingham, UK.
  • [8] M Packianather, M Landy and D T Pham (2009). Enhancing the speed of the Bees Algorithm using pheromone-based recruitment classifiers, Proc IEEE 7th International Conference on Industrial Informatics (INDIN 2009), Cardiff, UK, 789-794, ISBN: 978-142443760-3
  • [9] D T Pham and M Sholedolu (2008). Using a hybrid PSO-Bees Algorithm to train neural networks for wood defect classification, Proceedings of the 4th Virtual International Conference on Innovative Production Machines and Systems, D T Pham, E E Eldukhri and A J Soroka (eds), Whittles (Dunbeath, Caithness) and CRC Press (Boca Raton, FL), 385-390, ISBN 978-1-4398-0117-8
  • [10] A T Sadiq and A G Hamad (2010). BSA: A hybrid bees’ simulated annealing algorithm to solve optimization and NP-complete problems. Eng. & Tech. Journal, 28(2), 271-281
  • [11] M A Masmoudi, M Hosny, K Braekers and A Dammak (2016). Three effective metaheuristics to solve the multi-depot multi-trip heterogeneous dial-a-ride problem, Transportation Research Part E: Logistics and Transportation Review, 96, 60-80, ISSN 1366-5545, https://doi.org/10.1016/j.tre.2016.10.002
  • [12] T T M Anh and T D Vi (2023). Hybrid Genetic-Bees Algorithm in Multi-layer Perceptron Optimization. In: Saraswat, M., Chowdhury, C., Kumar Mandal, C., Gandomi, A.H. (eds) Proceedings of International Conference on Data Science and Applications. Lecture Notes in Networks and Systems, 552, Springer, Singapore. https://doi.org/10.1007/978-981-19-6634-7_11
  • [13] J Gholami and S Mohammadi (2018). A Novel Combination of Bees and Firefly Algorithm to Optimize Continuous Problems, Proceedings of 8th International Conference on Computer and Knowledge Engineering (ICCKE), Mashhad, Iran, 40-46, https://doi.org/10.1109/ICCKE.2018.8566263
  • [14] H Deghbouch and F Debbat (2022). Hybrid algorithm for node deployment with the guarantee of connectivity in wireless sensor networks, Informatica, 46(8), 147-164, https://doi.org/10.31449/inf.v46i8.3370
  • [15] H B Tolabi, M H Ali, S B M Ayob and M Rizwan (2014). Novel hybrid fuzzy-Bees algorithm for optimal feeder multi-objective reconfiguration by considering multiple-distributed generation, Energy, 71, 507-515, https://doi.org/10.1016/j.energy.2014.04.099
  • [16] S Ebrahimpoor, V Kiarostami, M Khosravi, M Davallo and A Ghaedi (2019). Bees metaheuristic algorithm with the aid of artificial neural networks for optimization of acid red 27 dye adsorption onto novel polypyrrole/SrFe12O19/graphene oxide nanocomposite. Polym. Bull., 76, 6529–6553, https://doi.org/10.1007/s00289-019-02700-7
  • [17] O Abdusalam, F Anayi and M Packianather (2023). Three-Phase Power Transformer Fault Diagnosis Based on Support Vector Machines and Bees Algorithm, Proceedings 2023 IEEE 3rd International Conference in Power Engineering Applications (ICPEA), Putrajaya, Malaysia, 145-150, https://doi.org/10.1109/ICPEA56918.2023.10093147
  • [18] N M H Alamri, M Packianather and S Bigot (2022). Deep Learning: Parameter Optimization Using Proposed Novel Hybrid Bees Bayesian Convolutional Neural Network, Applied Artificial Intelligence, 36(1), https://doi.org/10.1080/08839514.2022.2031815
  • [19] Y Song, L Xing and Y Chen (2023). Application of the dual-population Bees Algorithm in a parallel machine scheduling problem with a time window. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_14
  • [20] A H Ismail, W Ruslan and D T Pham (2023). A user-friendly Bees Algorithm for continuous and combinatorial optimisation, Cogent Engineering, 10:2, https://doi.org/10.1080/23311916.2023.2278257
  • [21] Y Laili, F Tao, D T Pham, Y Wang and L Zhang (2019). Robotic disassembly re-planning using a two-pointer detection strategy and a super-fast bees algorithm, Robotics and Computer-Integrated Manufacturing, 59, 130-142, https://doi.org/10.1016/j.rcim.2019.04.00
  • [22] M Packianather, T Alexopoulos and S Squire, S. (2023). The application of the Bees Algorithm in a digital twin for optimising the wire electrical discharge machining (WEDM) process parameters. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_3
  • [23] S Conte and D M d’Addona (2023). Bees Algorithm models for the identification and measurement of tool wear. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_7
  • [24] M Ay, A Baykasoglu, L Ozbakir and S Kulluk (2023). A case study with the BEE-Miner Algorithm: defects on the production line. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_4
  • [25] S Zeybek (2023). Prediction of the remaining useful life of engines for remanufacturing using a semi-supervised deep learning model trained by the Bees Algorithm. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_21
  • [26] N Shatnawi, S Sahran and M F Nasrudin (2023). Memory-based Bees Algorithm with Lévy Flights for multilevel image thresholding. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_11
  • [27] M Castellani, L Baronti, S Zheng and F Lan (2023). Shape recognition for industrial robot manipulation with the Bees Algorithm. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_6
  • [28] F Lan, M Castellani, Y Wang and S Zheng (2023). Global optimisation for point cloud registration with the Bees Algorithm. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_8
  • [29] O Öztürk, M A Şen, M Kalyoncu and H S Halkacı (2023). An application of the Bees Algorithm to pulsating hydroforming. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_5
  • [30] M Şahin and S Çakıroğlu (2023). Automatic PID tuning toolkit using the Multi-Objective Bees Algorithm. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_9
  • [31] M Kashkash, A Haj Darwish and A Joukhadar (2023). Α new method to generate the initial population of the Bees Algorithm for robot path planning in a static environment. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_12
  • [32] O Acar, H Sağlam and Z Şaka (2023). The effect of Harmony Memory integration into the Bees Algorithm. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_10
  • [33] M C Ang and K W Ng (2023). Minimising printed circuit board assembly time using the Bees Algorithm with TRIZ-inspired operators. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_2
  • [34] C Wang, T Chen and Z Li (2023). Method for the production planning and scheduling of a flexible manufacturing plant based on the Bees Algorithm. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_13
  • [35] Y Li, C Peng, Y Laili and L Zhang (2023). A parallel multi-indicator-assisted dynamic Bees Algorithm for cloud-edge collaborative manufacturing task scheduling. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_15
  • [36] M Caterino, M Fera, R Macchiaroli and D T Pham (2023). Task optimisation for a modern cloud remanufacturing system using the Bees Algorithm. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_20
  • [37] J Liu, Q Liu, Z Zhou, D T Pham, W Xu and Y Fang (2023). Collaborative optimisation of robotic disassembly planning problems using the Bees Algorithm. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_18
  • [38] N Hartono, F Javier Ramírez and D T Pham (2023). Optimisation of robotic disassembly sequence plans for sustainability using the multi-objective Bees Algorithm. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_19
  • [39] E Mastrocinque (2023). Supply chain design and multi-objective optimisation with the Bees Algorithm. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_17
  • [40] A H Ismail and D T Pham (2023). Bees traplining metaphors for the Vehicle Routing Problem using a decomposition approach. In: Pham, D.T., Hartono, N. (eds) Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-031-14537-7_16
There are 40 citations in total.

Details

Primary Language English
Subjects Industrial Engineering
Journal Section Research Articles
Authors

Duc Pham

Yanjie Song This is me

Yuanjun Laili This is me

Asrul Ismail This is me

Natalia Hartono This is me

Michael Packianather This is me

Marco Castellani This is me

Publication Date April 26, 2024
Submission Date March 7, 2024
Acceptance Date March 9, 2024
Published in Issue Year 2024 Volume: 1 Issue: 1

Cite

IEEE D. Pham, “The Bees Algorithm and Its Applications in Production and Manufacturing”, IJAPR, vol. 1, no. 1, pp. 1–10, 2024.

IJAPR is affiliated with The Turkish Society for Production Research.

International Journal of Advances in Production Research © 2024 is licensed under CC BY-NC 4.0.