A hybrid algorithm combining genetic algorithm and variable neighborhood search for process sequencing optimization of large-size problem

References

• Adibi, M. A., and J. Shahrabi. 2014. “A Clustering-based Modified Variable Neighborhood Search Algorithm for A Dynamic Job Shop Scheduling Problem.” International Journal of Advanced Manufacturing Technology 70 (9–12): 1955–1961. doi:10.1007/s00170-013-5354-6.
   Web of Science ®Google Scholar
• Bakhtiari, H., M. Karimi, and S. Rezazadeh. 2016. “Modeling, Analysis and Multi-Objective Optimization of Twist Extrusion Process Using Predictive Models and Meta-Heuristic Approaches, Based on Finite Element Results.” Journal of Intelligent Manufacturing 27 (2): 463–473. doi:10.1007/s10845-014-0879-6.
   Web of Science ®Google Scholar
• Blanch, R., N. Pellicer, M. L. G.-Romeu, and J. Ciurana. 2011. “Machining Processes Time Calculating Tool Integrated in Computer Aided Process Planning (CAPP) for Small and Medium Enterprises (Smes).” International Journal of Computer Integrated Manufacturing 24 (1): 40–52. doi:10.1080/09511921003608023.
   Web of Science ®Google Scholar
• Chang, H. C., and T. K. Liu. 2017. “Optimisation of Distributed Manufacturing Flexible Job Shop Scheduling by Using Hybrid Genetic Algorithms.” Journal of Intelligent Manufacturing 28 (8): 1973–1986. doi:10.1007/s10845-015-1084-y.
   Web of Science ®Google Scholar
• Costa, A., F. A. Cappadonna, and S. Fichera. 2017. “A Hybrid Genetic Algorithm for Minimizing Makespan in A Flow-Shop Sequence-Dependent Group Scheduling Problem.” Journal of Intelligent Manufacturing 28 (6): 1269–1283. doi:10.1007/s10845-015-1049-1.
   Web of Science ®Google Scholar
• Cui, W. W., Z. Q. Lu, B. H. Zhou, C. Li, and X. L. Han. 2016. “A Hybrid Genetic Algorithm for Non-permutation Flow Shop Scheduling Problems with Unavailability Constraints.” International Journal of Computer Integrated Manufacturing 29 (9): 944–961. doi:10.1080/0951192X.2015.1130247.
   Web of Science ®Google Scholar
• Deja, M., and M. S. Siemiatkowski. 2018. “Machining Process Sequencing and Machine Assignment in Generative Feature-Based CAPP for Mill-Turn Parts.” Journal of Manufacturing Systems 48: 49–62. doi:10.1016/j.jmsy.2018.06.001.
   Web of Science ®Google Scholar
• Dou, J. P., J. Li, and C. Su. 2018. “A Discrete Particle Swarm Optimisation for Operation Sequencing in CAPP.” International Journal of Production Research 56 (11): 3795–3814. doi:10.1080/00207543.2018.1425015.
   Web of Science ®Google Scholar
• Kafashi, S. 2011. “Integrated Setup Planning and Operation Sequencing (ISOS) Using Genetic Algorithm.” International Journal of Advanced Manufacturing Technology 56 (5–8): 589–600. doi:10.1007/s00170-011-3202-0.
   Web of Science ®Google Scholar
• Kafashi, S., M. Shakeri, and V. Abedini. 2012. “Automated Setup Planning in CAPP: A Modified Particle Swarm Optimisation-Based Approach.” International Journal of Production Research 50 (15): 4127–4140. doi:10.1080/00207543.2011.592157.
   Web of Science ®Google Scholar
• Koken, P., H. Seok, and S. W. Yoon. 2018. “A Simulated Annealing Algorithm with Neighbourhood List for Capacitated Dynamic Lot-Sizing Problem with Returns and Hybrid Products.” International Journal of Computer Integrated Manufacturing 31 (8): 739–747. doi:10.1080/0951192X.2017.1413250.
   Web of Science ®Google Scholar
• Leo, K. S. P. 2017. “State of the Art-Intense Review on Artificial Intelligence Systems Application in Process Planning and Manufacturing.” Engineering Applications of Artificial Intelligence 65: 294–329. doi:10.1016/j.engappai.2017.08.005.
   Web of Science ®Google Scholar
• Lian, K. L., C. Y. Zhang, X. Y. Shao, and Y. H. Zeng. 2011. “A Multi-Dimensional Tabu Search Algorithm for the Optimization of Process Planning.” Science China Technological Sciences 54 (12): 3211–3219. doi:10.1007/s11431-011-4594-7.
   Web of Science ®Google Scholar
• Luo, Y. B. 2015. “Topological Sorting-Based Two-Stage Nested Ant Colony Algorithm for Job-Shop Scheduling Problem.” Journal of Mechanical Engineering 51 (8): 178–184. doi:10.3901/JME.2015.08.178.
   Google Scholar
• Luo, Y. B. 2016. “Simulation Experiment Exploration of Genetic Algorithm’s Convergence over the Relationship Advantage Problem.” Mathematical Problems in Engineering 2016: 1–10. doi:10.1155/2016/4527402.
   Web of Science ®Google Scholar
• Luo, Y. B. 2017. “Nested Optimization Method Combining Complex Method and Ant Colony Optimization to Solve JSSP with Complex Associated Processes.” Journal of Intelligent Manufacturing 28 (8): 1801–1815. doi:10.1007/s10845-015-1065-1.
   Web of Science ®Google Scholar
• Luo, Y. B., and P. Y. Waden. 2017. “The Improved Ant Colony Optimization Algorithm for MLP considering the Advantage from Relationship.” Mathematical Problems In Engineering 2017: 1–11. doi:10.1155/2017/3920327.
   Web of Science ®Google Scholar
• Macedo, R., C. Alves, S. Hanafi, B. Jarboui, N. Mladenović, B. Ramos, J. M. Valério de Carvalho. 2015. “Skewed General Variable Neighborhood Search for the Location Routing Scheduling Problem.” Computers and Operations Research 61 (9): 143–152. doi:10.1016/j.cor.2015.03.011.
   Google Scholar
• Mejia, G., and K. Nino. 2017. “A New Hybrid Filtered Beam Search Algorithm for Deadlock-Free Scheduling of Flexible Manufacturing Systems Using Petri Nets.” Computers and Industrial Engineering 108: 165–176. doi:10.1016/j.cie.2017.04.034.
   Web of Science ®Google Scholar
• Miljkovic, Z., and M. Petrovic. 2017. “Application of Modified Multi-Objective Particle Swarm Optimisation Algorithm for Flexible Process Planning Problem.” International Journal of Computer Integrated Manufacturing 30 (2–3): 271–291. doi:10.1080/0951192X.2016.1145804.
   Web of Science ®Google Scholar
• Moghadam, A. M., K. Y. Wong, and H. Piroozfard. 2017. “Solving A Hybrid Jobshop Scheduling Problem with Space Constraints and Reentrant Processes by Using an Improved Hybrid Genetic Algorithm: A Case Study.” International Journal Of Industrial Engineering: Theory Applications And Practice 24 (5): 483–504.
   Web of Science ®Google Scholar
• Nallakumarasamy, G., P. S. S. Srinivasan, R. K. Venkatesh, and R. Malayalamurthi. 2011. “Optimization of Operation Sequencing in CAPP Using Simulated Annealing Technique (SAT).” International Journal of Advanced Manufacturing Technology 54 (5–8): 721–728. doi:10.1007/s00170-010-2977-8.
   Web of Science ®Google Scholar
• Ouali, A., D. Allouche, S. de Givry, S. Loudni, Y. Lebbah, L. Loukil, P. Boizumault. 2020. “Variable Neighborhood Search for Graphical Model Energy Minimization.” Artificial Intelligence 278: 103194. doi:10.1016/j.artint.2019.103194.
   Web of Science ®Google Scholar
• Pacheco, J., S. Porras, S. Casado, B. Baruque. 2018. “Variable Neighborhood Search with Memory for a Single-machine Scheduling Problem with Periodic Maintenance and Sequence-dependent Set-up Times.” Knowledge-Based Systems 145 (4): 1–14. doi:10.1016/j.knosys.2018.01.018.
   Google Scholar
• Phung, L. X., T. D. Van, S. V. Hoang, and S. H. Truong. 2017. “Effective Method of Operation Sequence Optimization in CAPP Based on Modified Clustering Algorithm.” Journal of Advanced Mechanical Design, Systems and Manufacturing 11 (1): 1–12. doi:10.1299/Jamdsm.2017jamdsm0001.
   Web of Science ®Google Scholar
• Renna, P. 2017. “A Decision Investment Model to Design Manufacturing Systems Based on A Genetic Algorithm and Monte-Carlo Simulation.” International Journal of Computer Integrated Manufacturing 30 (6): 590–605. doi:10.1080/0951192X.2016.1187299.
   Web of Science ®Google Scholar
• Sánchez-Oro, J., N. Mladenović, and A. Duarte. 2017. “General Variable Neighborhood Search for Computing Graph Separators.” Optimization Letters 11 (6): 1069–1089. doi:10.1007/s11590-014-0793-z.
   Web of Science ®Google Scholar
• Sevkli, A. Z., and K. A. Hamza. 2019. “General Variable Neighborhood Search for Solving Sudoku Puzzles: Unfiltered and Filtered Models.” Soft Computing 2 (15): 6585–6601. doi:10.1007/s00500-018-3307-6.
   Google Scholar
• Singh, S., and S. Deb. 2014. “An Intelligent Methodology for Optimising Machining Operation Sequence by Ant System Algorithm.” International Journal of Industrial and Systems Engineering 16 (4): 451–471. doi:10.1504/IJISE.2014.060654.
   Google Scholar
• Sowmiya, N., G. N. Srinivasa, B. Valarmathi, and S. G. Ponnambalam. 2017. “CORA - A Heuristic Approach to Machine-Part Cell Formation in the Presence of Alternative Process Plans.” International Journal of Advanced Manufacturing Technology 91 (9–12): 4275–4297. doi:10.1007/s00170-017-0038-2.
   Web of Science ®Google Scholar
• Su, Y. L., X. N. Chu, D. P. Chen, and X. W. Sun. 2018. “A Genetic Algorithm for Operation Sequencing in CAPP Using Edge Selection Based Encoding Strategy.” Journal of Intelligent Manufacturing 29 (2): 313–332. doi:10.1007/s10845-015-1109-6.
   Web of Science ®Google Scholar
• Wang, J. F., X. L. Fan, A. L. Zhao, and M. Q. Yang. 2015. “A Hybrid Bat Algorithm for Process Planning Problem.” IFAC-Papersonline 48 (3): 1708–1713. doi:10.1016/j.ifacol.2015.06.332.
   Google Scholar
• Xia, H., X. Y. Li, and L. Gao. 2016. “A Hybrid Genetic Algorithm with Variable Neighborhood Search for Dynamic Integrated Process Planning and Scheduling.” Computers and Industrial Engineering 102 (12): 99–112. doi:10.1016/j.cie.2016.10.015.
   Google Scholar
• Xu, Z. F., and Y. G. Cai. 2018. “Variable Neighborhood Search for Consistent Vehicle Routing Problem.” Expert Systems with Applications 113 (12): 66–76. doi:10.1016/j.eswa.2018.07.007.
   Google Scholar
• Yuce, B., F. Fruggiero, M. S. Packianather, D. T. Pham, E. Mastrocinque, A. Lambiase, and M. Fera. 2017. “Hybrid Genetic Bees Algorithm Applied to Single Machine Scheduling with Earliness and Tardiness Penalties.” Computers and Industrial Engineering 113: 842–858. doi:10.1016/j.cie.2017.07.018.
   Web of Science ®Google Scholar
• Zhang, G. H., L. J. Zhang, X. H. Song, Y. Wang, C. Zhou. 2019. “A Variable Neighborhood Search Based Genetic Algorithm for Flexible Job Shop Scheduling Problem.” Cluster Computing 22 (9): 11561–11572. doi:10.1007/s10586-017-1420-4.
   Google Scholar