How to cite this paper
Tóth, N & Kulcsár, G. (2021). New models and algorithms to solve integrated problems of production planning and control taking into account worker skills in flexible manufacturing systems.International Journal of Industrial Engineering Computations , 12(4), 381-400.
Refrences
Al-Hinai, N., & Piya, S. (2015). Jobshop scheduling for skill-dependent Make-to-order system. 2015 International Conference on Industrial Engineering and Operations Management (IEOM), 1354–1358.
Amjad, M. K., Butt, S. I., Kousar, R., Ahmad, R., Agha, M. H., Faping, Z., Anjum, N., & Asgher, U. (2018). Recent Research Trends in Genetic Algorithm Based Flexible Job Shop Scheduling Problems. Mathematical Problems in Engineering, 2018, 1–32.
Bányai, T., Landschützer, C., & Bányai, Á. (2018). Markov-Chain Simulation-Based Analysis of Human Resource Structure: How Staff Deployment and Staffing Affect Sustainable Human Resource Strategy. Sustainability, 10(10), 3692
Barrera-Diaz, C. A., Oscarsson, J., Lidberg, S., & Sellgren, T. (2018). Discrete Event Simulation Output Data-Handling System in an Automotive Manufacturing Plant. Procedia Manufacturing, 25, 23–30.
Bożejko, W., Uchroński, M., & Wodecki, M. ł. (2010). Parallel hybrid metaheuristics for the flexible job shop problem. Computers & Industrial Engineering, 59(2), 323–333.
Brucker, P. (2007). Scheduling Algorithms (5th ed.). Springer.
Brucker, P., Sotskov, Y. N., & Werner, F. (2007). Complexity of shop-scheduling problems with fixed number of jobs: a survey. Mathematical Methods of Operations Research, 65(3), 461–481.
Chung, C. A. (1996). Human issues influencing the successful implementation of advanced manufacturing technology. Journal of Engineering and Technology Management, 13(3–4), 283–299.
Chawla, V. K., Chanda, A. K., & Angra, S. (2018). Scheduling of multi load AGVs in FMS by modified memetic particle swarm optimization algorithm. Journal of Project Management, 39–54.
Durmaz, H., & Koyuncu, M. (2019). Optimization of Assignment Problems In Production Lines With Different Skilled Labor Levels. International Advanced Researches and Engineering Journal, 123–136.
Ferjani, A., Ammar, A., Pierreval, H., & Elkosantini, S. (2017). A simulation-optimization based heuristic for the online assignment of multi-skilled workers subjected to fatigue in manufacturing systems. Computers & Industrial Engineering, 112, 663–674
Fu, H. C., & Liu, P. (2019). A Multi-Objective Optimization Model Based on Non-Dominated Sorting Genetic Algorithm. International Journal of Simulation Modelling, 18(3), 510–520.
Gao, K. Z., Suganthan, P. N., Pan, Q. K., & Tasgetiren, M. F. (2015). An effective discrete harmony search algorithm for flexible job shop scheduling problem with fuzzy processing time. International Journal of Production Research, 53(19), 5896–5911.
Gao, K. Z., Suganthan, P. N., Pan, Q. K., Tasgetiren, M. F., & Sadollah, A. (2016). Artificial bee colony algorithm for scheduling and rescheduling fuzzy flexible job shop problem with new job insertion. Knowledge-Based Systems, 109, 1–16.
Gania, I. P., Stachowiak, A., & Oleśków-Szłapka, J. (2018). Flexible manufacturing systems: Industry 4.0 solution. DEStech Transactions on Engineering and Technology Research, icpr, 57–62.
Ida, K., & Oka, K. (2011). Flexible job-shop scheduling problem by genetic algorithm. Electrical Engineering in Japan, 177(3), 28–35.
Jeet, K., Dhir, R., & Singh, P. (2016). Hybrid Black Hole Algorithm for Bi-Criteria Job Scheduling on Parallel Machines. International Journal of Intelligent Systems and Applications, 8(4), 1–17.
Jia, S., & Hu, Z.-H. (2014). Path-relinking Tabu search for the multi-objective flexible job shop scheduling problem. Computers & Operations Research, 47, 11–26.
Karwowski, W. (2005). Ergonomics and human factors: the paradigms for science, engineering, design, technology and management of human-compatible systems. Ergonomics, 48(5), 436–463.
Kikolski, M. (2016). Identification of production bottlenecks with the use of Plant Simulation software. Ekonomia i Zarzadzanie, 8(4), 103–112.
Kumar, S., Goyal, A., & Singhal, A. (2017). Manufacturing Flexibility and its Effect on System Performance. Jordan Journal of Mechanical and Industrial Engineering, 11(2), 105–112.
Kundu, K., Rossini, M., & Portioli-Staudacher, A. (2019). A study of a kanban based assembly line feeding system through integration of simulation and particle swarm optimization. International Journal of Industrial Engineering Computations, 421–442
Lin, C., & Gen, M. (2008). Multi-criteria human resource allocation for solving multistage combinatorial optimization problems using multiobjective hybrid genetic algorithm. Expert Systems with Applications, 34(4), 2480–2490.
Lin, R., Zhou, G., Liu, A., Lu, H., & Li, T. (2016). Impact of Personnel Flexibility on Job Shop Scheduling. Scientific Programming, 2016, 1–8.
Liu, S. Q., Kozan, E., Masoud, M., Zhang, Y., & Chan, F. T. S. (2017). Job shop scheduling with a combination of four buffering constraints. International Journal of Production Research, 56(9), 3274–3293.
Longo, F., Nicoletti, L., & Padovano, A. (2017). Smart operators in industry 4.0: A human-centered approach to enhance operators’ capabilities and competencies within the new smart factory context. Computers & Industrial Engineering, 113, 144–159.
Luh, G.-C., & Lee, S.-W. (2006). Abacterial evolutionary algorithm for the job shop scheduling problem. Journal of the Chinese Institute of Industrial Engineers, 23(3), 185–191.
Michalos, G., Makris, S., Papakostas, N., Mourtzis, D., & Chryssolouris, G. (2010). Automotive assembly technologies review: challenges and outlook for a flexible and adaptive approach. CIRP Journal of Manufacturing Science and Technology, 2(2), 81–91.
Oliveira, M., Arica, E., Pinzone, M., Fantini, P., & Taisch, M. (2019). Human-Centered Manufacturing Challenges Affecting European Industry 4.0 Enabling Technologies. HCI International 2019 – Late Breaking Papers, 507–517.
Peruzzini, M., & Pellicciari, M. (2017). A framework to design a human-centred adaptive manufacturing system for aging workers. Advanced Engineering Informatics, 33, 330–349.
Pongchairerks, P., & Kachitvichyanukul, V. (2009). A Particle Swarm Optimization Algorithm On Job-Shop Scheduling Problems With Multi-Purpose Machines. Asia-Pacific Journal of Operational Research, 26(02), 161–184.
Ruiz, R., & Vázquez-Rodríguez, J. A. (2010). The hybrid flow shop scheduling problem. European Journal of Operational Research, 205(1), 1–18.
Shannon, C. E. (1948). A Mathematical Theory of Communication. Bell System Technical Journal, 27(4), 623–656.
Shivanand, H. K. (2006). Flexible Manufacturing System. New Age International.
Sirovetnukul, R., & Chutima, P. (2010). The Impact of Walking Time on U-Shaped Assembly Line Worker Allocation Problems. Engineering Journal, 14(2), 53–78.
Sotskov, Y. N., & Shakhlevich, N. V. (1995). NP-hardness of shop-scheduling problems with three jobs. Discrete Applied Mathematics, 59(3), 237–266.
Sun, W., Pan, Y., Lu, X., & Ma, Q. (2010). Research on flexible job-shop scheduling problem based on a modified genetic algorithm. Journal of Mechanical Science and Technology, 24(10), 2119–2125.
Sungur, B., & Yavuz, Y. (2015). Assembly line balancing with hierarchical worker assignment. Journal of Manufacturing Systems, 37, 290–298.
Udaiyakumar, K. C., & Chandrasekaran, M. (2014). Application of Firefly Algorithm in Job Shop Scheduling Problem for Minimization of Makespan. Procedia Engineering, 97, 1798–1807.
Wang, L., Cai, J., Li, M., & Liu, Z. (2017). Flexible Job Shop Scheduling Problem Using an Improved Ant Colony Optimization. Scientific Programming, 2017, 1–11.
Wang, Y., Yang, O., & Wang, S. N. (2019). A Solution to Single-Machine Inverse Job-Shop Scheduling Problem. International Journal of Simulation Modelling, 18(2), 335–343.
Yang, M. S., Ba, L., Liu, Y., Zheng, H. Y., Yan, J. T., Gao, X. Q., & Xiao, J. M. (2019). An Improved Genetic Simulated Annealing Algorithm for Stochastic Two-Sided Assembly Line Balancing Problem. International Journal of Simulation Modelling, 18(1), 175–186.
Yang, X.-S., Karamanoglu, M., & He, X. (2013). Multi-objective Flower Algorithm for Optimization. Procedia Computer Science, 18, 861–868.
Yazdani, M., Gholami, M., Zandieh, M., & Mousakhani, M. (2009). A Simulated Annealing Algorithm for Flexible Job-Shop Scheduling Problem. Journal of Applied Sciences, 9(4), 662–670.
Zaher, H., Ragaa, N., & Sayed, H. (2017). A novel Improved Bat Algorithm for Job Shop Scheduling Problem. International Journal of Computer Applications, 164(5), 24–30.
Zhang, Q., Manier, H., & Manier, M.-A. (2013). A modified shifting bottleneck heuristic and disjunctive graph for job shop scheduling problems with transportation constraints. International Journal of Production Research, 52(4), 985–1002.
Zhang, R. (2013). A Simulated Annealing-Based Heuristic Algorithm for Job Shop Scheduling to Minimize Lateness. International Journal of Advanced Robotic Systems, 10(4), 214.
Ziaee, M. (2014). Job shop scheduling with makespan objective: A heuristic approach. International Journal of Industrial Engineering Computations, 5(2), 273–280.
Zijm, W. H. M. (2000). Towards intelligent manufacturing planning and control systems. OR Spectrum, 22(3), 313–345.
Zinder, Y., Ha Do, V., & Oğuz, C. (2005). Computational complexity of some scheduling problems with multiprocessor tasks. Discrete Optimization, 2(4), 391–408
Zupan, H., & Herakovic, N. (2015). Production line balancing with discrete event simulation: A case study. IFAC-PapersOnLine, 48(3), 2305–2311
Amjad, M. K., Butt, S. I., Kousar, R., Ahmad, R., Agha, M. H., Faping, Z., Anjum, N., & Asgher, U. (2018). Recent Research Trends in Genetic Algorithm Based Flexible Job Shop Scheduling Problems. Mathematical Problems in Engineering, 2018, 1–32.
Bányai, T., Landschützer, C., & Bányai, Á. (2018). Markov-Chain Simulation-Based Analysis of Human Resource Structure: How Staff Deployment and Staffing Affect Sustainable Human Resource Strategy. Sustainability, 10(10), 3692
Barrera-Diaz, C. A., Oscarsson, J., Lidberg, S., & Sellgren, T. (2018). Discrete Event Simulation Output Data-Handling System in an Automotive Manufacturing Plant. Procedia Manufacturing, 25, 23–30.
Bożejko, W., Uchroński, M., & Wodecki, M. ł. (2010). Parallel hybrid metaheuristics for the flexible job shop problem. Computers & Industrial Engineering, 59(2), 323–333.
Brucker, P. (2007). Scheduling Algorithms (5th ed.). Springer.
Brucker, P., Sotskov, Y. N., & Werner, F. (2007). Complexity of shop-scheduling problems with fixed number of jobs: a survey. Mathematical Methods of Operations Research, 65(3), 461–481.
Chung, C. A. (1996). Human issues influencing the successful implementation of advanced manufacturing technology. Journal of Engineering and Technology Management, 13(3–4), 283–299.
Chawla, V. K., Chanda, A. K., & Angra, S. (2018). Scheduling of multi load AGVs in FMS by modified memetic particle swarm optimization algorithm. Journal of Project Management, 39–54.
Durmaz, H., & Koyuncu, M. (2019). Optimization of Assignment Problems In Production Lines With Different Skilled Labor Levels. International Advanced Researches and Engineering Journal, 123–136.
Ferjani, A., Ammar, A., Pierreval, H., & Elkosantini, S. (2017). A simulation-optimization based heuristic for the online assignment of multi-skilled workers subjected to fatigue in manufacturing systems. Computers & Industrial Engineering, 112, 663–674
Fu, H. C., & Liu, P. (2019). A Multi-Objective Optimization Model Based on Non-Dominated Sorting Genetic Algorithm. International Journal of Simulation Modelling, 18(3), 510–520.
Gao, K. Z., Suganthan, P. N., Pan, Q. K., & Tasgetiren, M. F. (2015). An effective discrete harmony search algorithm for flexible job shop scheduling problem with fuzzy processing time. International Journal of Production Research, 53(19), 5896–5911.
Gao, K. Z., Suganthan, P. N., Pan, Q. K., Tasgetiren, M. F., & Sadollah, A. (2016). Artificial bee colony algorithm for scheduling and rescheduling fuzzy flexible job shop problem with new job insertion. Knowledge-Based Systems, 109, 1–16.
Gania, I. P., Stachowiak, A., & Oleśków-Szłapka, J. (2018). Flexible manufacturing systems: Industry 4.0 solution. DEStech Transactions on Engineering and Technology Research, icpr, 57–62.
Ida, K., & Oka, K. (2011). Flexible job-shop scheduling problem by genetic algorithm. Electrical Engineering in Japan, 177(3), 28–35.
Jeet, K., Dhir, R., & Singh, P. (2016). Hybrid Black Hole Algorithm for Bi-Criteria Job Scheduling on Parallel Machines. International Journal of Intelligent Systems and Applications, 8(4), 1–17.
Jia, S., & Hu, Z.-H. (2014). Path-relinking Tabu search for the multi-objective flexible job shop scheduling problem. Computers & Operations Research, 47, 11–26.
Karwowski, W. (2005). Ergonomics and human factors: the paradigms for science, engineering, design, technology and management of human-compatible systems. Ergonomics, 48(5), 436–463.
Kikolski, M. (2016). Identification of production bottlenecks with the use of Plant Simulation software. Ekonomia i Zarzadzanie, 8(4), 103–112.
Kumar, S., Goyal, A., & Singhal, A. (2017). Manufacturing Flexibility and its Effect on System Performance. Jordan Journal of Mechanical and Industrial Engineering, 11(2), 105–112.
Kundu, K., Rossini, M., & Portioli-Staudacher, A. (2019). A study of a kanban based assembly line feeding system through integration of simulation and particle swarm optimization. International Journal of Industrial Engineering Computations, 421–442
Lin, C., & Gen, M. (2008). Multi-criteria human resource allocation for solving multistage combinatorial optimization problems using multiobjective hybrid genetic algorithm. Expert Systems with Applications, 34(4), 2480–2490.
Lin, R., Zhou, G., Liu, A., Lu, H., & Li, T. (2016). Impact of Personnel Flexibility on Job Shop Scheduling. Scientific Programming, 2016, 1–8.
Liu, S. Q., Kozan, E., Masoud, M., Zhang, Y., & Chan, F. T. S. (2017). Job shop scheduling with a combination of four buffering constraints. International Journal of Production Research, 56(9), 3274–3293.
Longo, F., Nicoletti, L., & Padovano, A. (2017). Smart operators in industry 4.0: A human-centered approach to enhance operators’ capabilities and competencies within the new smart factory context. Computers & Industrial Engineering, 113, 144–159.
Luh, G.-C., & Lee, S.-W. (2006). Abacterial evolutionary algorithm for the job shop scheduling problem. Journal of the Chinese Institute of Industrial Engineers, 23(3), 185–191.
Michalos, G., Makris, S., Papakostas, N., Mourtzis, D., & Chryssolouris, G. (2010). Automotive assembly technologies review: challenges and outlook for a flexible and adaptive approach. CIRP Journal of Manufacturing Science and Technology, 2(2), 81–91.
Oliveira, M., Arica, E., Pinzone, M., Fantini, P., & Taisch, M. (2019). Human-Centered Manufacturing Challenges Affecting European Industry 4.0 Enabling Technologies. HCI International 2019 – Late Breaking Papers, 507–517.
Peruzzini, M., & Pellicciari, M. (2017). A framework to design a human-centred adaptive manufacturing system for aging workers. Advanced Engineering Informatics, 33, 330–349.
Pongchairerks, P., & Kachitvichyanukul, V. (2009). A Particle Swarm Optimization Algorithm On Job-Shop Scheduling Problems With Multi-Purpose Machines. Asia-Pacific Journal of Operational Research, 26(02), 161–184.
Ruiz, R., & Vázquez-Rodríguez, J. A. (2010). The hybrid flow shop scheduling problem. European Journal of Operational Research, 205(1), 1–18.
Shannon, C. E. (1948). A Mathematical Theory of Communication. Bell System Technical Journal, 27(4), 623–656.
Shivanand, H. K. (2006). Flexible Manufacturing System. New Age International.
Sirovetnukul, R., & Chutima, P. (2010). The Impact of Walking Time on U-Shaped Assembly Line Worker Allocation Problems. Engineering Journal, 14(2), 53–78.
Sotskov, Y. N., & Shakhlevich, N. V. (1995). NP-hardness of shop-scheduling problems with three jobs. Discrete Applied Mathematics, 59(3), 237–266.
Sun, W., Pan, Y., Lu, X., & Ma, Q. (2010). Research on flexible job-shop scheduling problem based on a modified genetic algorithm. Journal of Mechanical Science and Technology, 24(10), 2119–2125.
Sungur, B., & Yavuz, Y. (2015). Assembly line balancing with hierarchical worker assignment. Journal of Manufacturing Systems, 37, 290–298.
Udaiyakumar, K. C., & Chandrasekaran, M. (2014). Application of Firefly Algorithm in Job Shop Scheduling Problem for Minimization of Makespan. Procedia Engineering, 97, 1798–1807.
Wang, L., Cai, J., Li, M., & Liu, Z. (2017). Flexible Job Shop Scheduling Problem Using an Improved Ant Colony Optimization. Scientific Programming, 2017, 1–11.
Wang, Y., Yang, O., & Wang, S. N. (2019). A Solution to Single-Machine Inverse Job-Shop Scheduling Problem. International Journal of Simulation Modelling, 18(2), 335–343.
Yang, M. S., Ba, L., Liu, Y., Zheng, H. Y., Yan, J. T., Gao, X. Q., & Xiao, J. M. (2019). An Improved Genetic Simulated Annealing Algorithm for Stochastic Two-Sided Assembly Line Balancing Problem. International Journal of Simulation Modelling, 18(1), 175–186.
Yang, X.-S., Karamanoglu, M., & He, X. (2013). Multi-objective Flower Algorithm for Optimization. Procedia Computer Science, 18, 861–868.
Yazdani, M., Gholami, M., Zandieh, M., & Mousakhani, M. (2009). A Simulated Annealing Algorithm for Flexible Job-Shop Scheduling Problem. Journal of Applied Sciences, 9(4), 662–670.
Zaher, H., Ragaa, N., & Sayed, H. (2017). A novel Improved Bat Algorithm for Job Shop Scheduling Problem. International Journal of Computer Applications, 164(5), 24–30.
Zhang, Q., Manier, H., & Manier, M.-A. (2013). A modified shifting bottleneck heuristic and disjunctive graph for job shop scheduling problems with transportation constraints. International Journal of Production Research, 52(4), 985–1002.
Zhang, R. (2013). A Simulated Annealing-Based Heuristic Algorithm for Job Shop Scheduling to Minimize Lateness. International Journal of Advanced Robotic Systems, 10(4), 214.
Ziaee, M. (2014). Job shop scheduling with makespan objective: A heuristic approach. International Journal of Industrial Engineering Computations, 5(2), 273–280.
Zijm, W. H. M. (2000). Towards intelligent manufacturing planning and control systems. OR Spectrum, 22(3), 313–345.
Zinder, Y., Ha Do, V., & Oğuz, C. (2005). Computational complexity of some scheduling problems with multiprocessor tasks. Discrete Optimization, 2(4), 391–408
Zupan, H., & Herakovic, N. (2015). Production line balancing with discrete event simulation: A case study. IFAC-PapersOnLine, 48(3), 2305–2311