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An effective hybrid genetic algorithm and tabu search for flexible job shop scheduling problem

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  1. YoungSu Yun & Anudari Chuluunsukh & Mitsuo Gen, 2020. "Sustainable Closed-Loop Supply Chain Design Problem: A Hybrid Genetic Algorithm Approach," Mathematics, MDPI, vol. 8(1), pages 1-19, January.
  2. Hyun Cheol Lee & Chunghun Ha, 2019. "Sustainable Integrated Process Planning and Scheduling Optimization Using a Genetic Algorithm with an Integrated Chromosome Representation," Sustainability, MDPI, vol. 11(2), pages 1-23, January.
  3. Seyed Mahdi Homayouni & Dalila B. M. M. Fontes, 2021. "Production and transport scheduling in flexible job shop manufacturing systems," Journal of Global Optimization, Springer, vol. 79(2), pages 463-502, February.
  4. Lu Sun & Lin Lin & Haojie Li & Mitsuo Gen, 2019. "Cooperative Co-Evolution Algorithm with an MRF-Based Decomposition Strategy for Stochastic Flexible Job Shop Scheduling," Mathematics, MDPI, vol. 7(4), pages 1-20, March.
  5. Leilei Meng & Biao Zhang & Kaizhou Gao & Peng Duan, 2022. "An MILP Model for Energy-Conscious Flexible Job Shop Problem with Transportation and Sequence-Dependent Setup Times," Sustainability, MDPI, vol. 15(1), pages 1-14, December.
  6. Dung-Ying Lin & Tzu-Yun Huang, 2021. "A Hybrid Metaheuristic for the Unrelated Parallel Machine Scheduling Problem," Mathematics, MDPI, vol. 9(7), pages 1-20, April.
  7. An, Youjun & Chen, Xiaohui & Hu, Jiawen & Zhang, Lin & Li, Yinghe & Jiang, Junwei, 2022. "Joint optimization of preventive maintenance and production rescheduling with new machine insertion and processing speed selection," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
  8. Jose L. Andrade-Pineda & David Canca & Pedro L. Gonzalez-R & M. Calle, 2020. "Scheduling a dual-resource flexible job shop with makespan and due date-related criteria," Annals of Operations Research, Springer, vol. 291(1), pages 5-35, August.
  9. Lunardi, Willian T. & Birgin, Ernesto G. & Ronconi, Débora P. & Voos, Holger, 2021. "Metaheuristics for the online printing shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 293(2), pages 419-441.
  10. Teeradech Laisupannawong & Boonyarit Intiyot & Chawalit Jeenanunta, 2021. "Mixed-Integer Linear Programming Model and Heuristic for Short-Term Scheduling of Pressing Process in Multi-Layer Printed Circuit Board Manufacturing," Mathematics, MDPI, vol. 9(6), pages 1-25, March.
  11. Braune, Roland & Benda, Frank & Doerner, Karl F. & Hartl, Richard F., 2022. "A genetic programming learning approach to generate dispatching rules for flexible shop scheduling problems," International Journal of Production Economics, Elsevier, vol. 243(C).
  12. Ahmadi, Sobhan & Akgunduz, Ali, 2023. "Airport operations with electric-powered towing alternatives under stochastic conditions," Journal of Air Transport Management, Elsevier, vol. 109(C).
  13. Xianbo Xiang & Caoyang Yu & He Xu & Stuart X. Zhu, 2018. "Optimization of Heterogeneous Container Loading Problem with Adaptive Genetic Algorithm," Complexity, Hindawi, vol. 2018, pages 1-12, November.
  14. Xiaoqiu Shi & Wei Long & Yanyan Li & Dingshan Deng, 2020. "Multi-population genetic algorithm with ER network for solving flexible job shop scheduling problems," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-23, May.
  15. Xuan Jing & Xifan Yao & Min Liu & Jiajun Zhou, 2024. "Multi-agent reinforcement learning based on graph convolutional network for flexible job shop scheduling," Journal of Intelligent Manufacturing, Springer, vol. 35(1), pages 75-93, January.
  16. Fei Luan & Zongyan Cai & Shuqiang Wu & Shi Qiang Liu & Yixin He, 2019. "Optimizing the Low-Carbon Flexible Job Shop Scheduling Problem with Discrete Whale Optimization Algorithm," Mathematics, MDPI, vol. 7(8), pages 1-17, August.
  17. Mohamed Habib Zahmani & Baghdad Atmani, 2021. "Multiple dispatching rules allocation in real time using data mining, genetic algorithms, and simulation," Journal of Scheduling, Springer, vol. 24(2), pages 175-196, April.
  18. Alejandro Vital-Soto & Mohammed Fazle Baki & Ahmed Azab, 2023. "A multi-objective mathematical model and evolutionary algorithm for the dual-resource flexible job-shop scheduling problem with sequencing flexibility," Flexible Services and Manufacturing Journal, Springer, vol. 35(3), pages 626-668, September.
  19. Jian Zhang & Guofu Ding & Yisheng Zou & Shengfeng Qin & Jianlin Fu, 2019. "Review of job shop scheduling research and its new perspectives under Industry 4.0," Journal of Intelligent Manufacturing, Springer, vol. 30(4), pages 1809-1830, April.
  20. Neumann, Anas & Hajji, Adnene & Rekik, Monia & Pellerin, Robert, 2024. "Integrated planning and scheduling of engineer-to-order projects using a Lamarckian Layered Genetic Algorithm," International Journal of Production Economics, Elsevier, vol. 267(C).
  21. Husam Suleiman, 2022. "A Cost-Aware Framework for QoS-Based and Energy-Efficient Scheduling in Cloud–Fog Computing," Future Internet, MDPI, vol. 14(11), pages 1-21, November.
  22. Ivan Lorencin & Nikola Anđelić & Vedran Mrzljak & Zlatan Car, 2019. "Genetic Algorithm Approach to Design of Multi-Layer Perceptron for Combined Cycle Power Plant Electrical Power Output Estimation," Energies, MDPI, vol. 12(22), pages 1-26, November.
  23. Dauzère-Pérès, Stéphane & Ding, Junwen & Shen, Liji & Tamssaouet, Karim, 2024. "The flexible job shop scheduling problem: A review," European Journal of Operational Research, Elsevier, vol. 314(2), pages 409-432.
  24. Qihao Liu & Xinyu Li & Liang Gao, 2021. "Mathematical modeling and a hybrid evolutionary algorithm for process planning," Journal of Intelligent Manufacturing, Springer, vol. 32(3), pages 781-797, March.
  25. Fei Luan & Zongyan Cai & Shuqiang Wu & Tianhua Jiang & Fukang Li & Jia Yang, 2019. "Improved Whale Algorithm for Solving the Flexible Job Shop Scheduling Problem," Mathematics, MDPI, vol. 7(5), pages 1-14, April.
  26. Zhe Zhang & Xiaoling Song & Huijun Huang & Yong Yin & Benjamin Lev, 2022. "Scheduling problem in seru production system considering DeJong’s learning effect and job splitting," Annals of Operations Research, Springer, vol. 312(2), pages 1119-1141, May.
  27. Lihui Zhang & Riletu Ge & Jianxue Chai, 2019. "Prediction of China’s Energy Consumption Based on Robust Principal Component Analysis and PSO-LSSVM Optimized by the Tabu Search Algorithm," Energies, MDPI, vol. 12(1), pages 1-19, January.
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