How to cite this paper
Assafra, K., Alaya, B., Zidi, S & Zrigui, M. (2024). Optimization of transport constraints and quality of service for joint resolution of uncertain scheduling and the job-shop problem with routing (JSSPR) as opposed to the job-shop problem with transport (JSSPT).Journal of Project Management, 9(2), 109-130.
Refrences
Abdolrazzagh-Nezhad, M .,& Abdullah, S. (2017). Job shop scheduling: Classification, constraints and objective func-tions. International Journal of Computer and Information Engineering, 11(4), 429-434.
Abukhader, R., & Kakoore, S. (2021). Artificial Intelligence for Vertical Farming–Controlling the Food Production.
Ahmadian, M. M., Salehipour, A., & Cheng, T. C. E. (2021). A meta-heuristic to solve the just-in-time job-shop sched-uling problem. European Journal of Operational Research, 288(1), 14-29.
Alaya, B. (2017, April). EE-(m, k)-Firm: A Method to Dynamic Service Level Management in Enterprise Environment. In International Conference on Enterprise Information Systems, 2, 114-122.
Álvarez-Gil, N., Rosillo, R., de la Fuente, D., & Pino, R. (2021). A discrete firefly algorithm for solving the flexible job-shop scheduling problem in a make-to-order manufacturing system. Central European Journal of Operations Research, 29, 1353-1374.
Baykasoğlu, A., Hamzadayi, A., & Köse, S. Y. (2014). Testing the performance of teaching–learning based optimization (TLBO) algorithm on combinatorial problems: Flow shop and job shop scheduling cases. Information Sciences, 276, 204-218.
Bueno, A., Godinho F., Moacir, F., & Alejandro, G. (2020). Smart production planning and control in the Industry 4.0 context. Computers industrial engineering, 149, 106774.
Cebi, C., Atac, E., & Sahingoz, O. K. (2020, July). Job shop scheduling problem and solution algorithms: a review. In 2020 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT),1-7.
Cordeau, J. F., & Laporte, G. (2003). A tabu search heuristic for the static multi-vehicle dial-a-ride prob-lem. Transportation Research Part B: Methodological, 37(6), 579-594.
Cunha, B., Madureira, A. M., Fonseca, B., & Coelho, D. (2020). Deep reinforcement learning as a job shop scheduling solver. In Hybrid Intelligent Systems: 18th International Conference on Hybrid Intelligent Systems (HIS 2018), 350-359.
Dean, W. (2015). Computational Complexity Theory, The Stanford Encyclopedia of Philosophy , Edward N. Zal-ta (ed.), https://plato.stanford.edu/archives/fall2021/entries/computational-complexity/>
Firat, M., & Woeginger, G. J. (2011). Analysis of the dial-a-ride problem of Hunsaker and Savelsbergh. Operations Re-search Letters, 39(1), 32-35.
Frihat, M., Hadj-Alouane, A. & Sadfi, C. (2022). Optimization of the integrated problem of employee timetabling and job shop scheduling. Computers & Operations Research, 137, 105332.
Gaham, M., Bouzouia, B., & Achour, N. (2018). An effective operations permutation-based discrete harmony search approach for the flexible job shop scheduling problem with makespan criterion. Applied Intelligence, 48, 1423-1441.
Gao, D., Wang, G. G., & Pedrycz, W. (2020). Solving fuzzy job-shop scheduling problem using DE algorithm improved by a selection mechanism. IEEE Transactions on Fuzzy Systems, 28(12), 3265-3275.
Gondran, M., Huguet, M. J., Lacomme, P., Quilliot, A., & Tchernev, N. (2018). A Dial-a-Ride evaluation for solving the job-shop with routing considerations. Engineering Applications of Artificial Intelligence, 74, 70-89.
Gondran, M., Lacomme, P., & Tchernev, N. (2017). Resolution of a job-shop with routing considering a quality of ser-vice for customer: JSSP with routing. In 7th International Conference on Industrial Engineering and Systems Man-agement (IESM).
Graham, R. L., Lawler, E. L., Lenstra, J. K., & Kan, A. R. (1979). Optimization and approximation in deterministic se-quencing and scheduling: a survey. In Annals of discrete mathematics , 5, 287-326.
Haifei, Y., Songjian, H., Dongsheng ,Y., Zhiyong,W., Wei ,F.,&Atila B.(2021). Job Shop Scheduling Based on Digital Twin Technology. Complexity, (2021),1-12 https://doi.org/10.1155/2021/8823273.
He, P., & Hao, J. K. (2023). Memetic search for the minmax multiple traveling salesman problem with single and mul-tiple depots. European Journal of Operational Research, 307(3), 1055-1070.
Hegen, X., Shuangyuan, S., Danni, R., & Jinjin, H. (2022). A survey of job shop scheduling problem: the types and models. Computers Operations Research, 142,105731, doi.org/10.1016/j.cor.2022.105731.
Hurink, J., & Knust, S. (2005). Tabu search algorithms for job-shop problems with a single transport robot. European journal of operational research, 162(1), 99-111.
Hussein, M., & Zayed, T. (2021). Critical factors for successful implementation of just-in-time concept in modular in-tegrated construction: A systematic review and meta-analysis. Journal of Cleaner Production, 284, 124716.
Jain, A. S., & Meeran, S. (1999). Deterministic job-shop scheduling: Past, present and future. European journal of op-erational research, 113(2), 390-434.
Jamili, A. (2016). Robust job shop scheduling problem: Mathematical models, exact and heuristic algorithms. Expert systems with Applications, 55, 341-350.
Kalshetty, Y. R., Adamuthe, A. C., & Kumar, S. P. (2020). Genetic algorithms with feasible operators for solving job shop scheduling problem. Journal of Science Resources, 64, 310-321.
Kardos, C., Laflamme, C., Gallina, V., & Sihn, W. (2021). Dynamic scheduling in a job-shop production system with reinforcement learning. Procedia CIRP, 97, 104-109.
Kechadi, M. T., Low, K. S., & Goncalves, G. (2013). Recurrent neural network approach for cyclic job shop scheduling problem. Journal of Manufacturing Systems, 32(4), 689-699.
Lacomme, P., Larabi, M., & Tchernev, N. (2013). Job-shop based framework for simultaneous scheduling of machines and automated guided vehicles. International Journal of Production Economics, 143(1), 24-34.
Lee, T., & Loong, Y. (2019). A review of scheduling problem and resolution methods in exible ow shop. International Journal of Industrial Engineering Computations, 10(1), 67-88.
Li, X., Xie, J., Ma, Q., Gao, L., & Li, P. (2022). Improved gray wolf optimizer for distributed flexible job shop schedul-ing problem. Science China Technological Sciences, 65(9), 2105-2115.
Mihoubi, B., Bouzouia, B., & Gaham, M. (2021). Reactive scheduling approach for solving a realistic flexible job shop scheduling problem. International journal of production research, 59(19), 5790-5808.
Mohan, J., Lanka, K., & Rao, A. N. (2019). A review of dynamic job shop scheduling techniques. Procedia Manufactur-ing, 30, 34-39.
Nouri, H. E., Driss, O. B., & Ghédira, K. (2016). A classification schema for the job shop scheduling problem with transportation resources: state-of-the-art review. In Artificial Intelligence Perspectives in Intelligent Systems: Pro-ceedings of the 5th Computer Science On-line Conference 2016 (CSOC2016), 1, 1-11.
Ojstersek, R., Brezocnik, M.,&Buchmeister, B. (2020). Multi-objective optimization of production scheduling with evolutionary computation. International Journal of Industrial Engineering Computations, 11(3), 359-376.
Pappas, I., Kourouthanassis, P., Giannakos, M.,& Lekakos, G. (2017). The interplay of online shopping motivations and experiential factors on personalized e-commerce. Telematics and informatics, 34(5), 730-742.
Parveen, S., & Ullah, H. (2010). Review on job-shop and flow-shop scheduling using. Journal of Mechanical Engineer-ing, 41(2), 130-146.
Prins, C. (2009). A GRASP× evolutionary local search hybrid for the vehicle routing problem. In Bio-inspired algo-rithms for the vehicle routing problem, 35-53.
Quinton, F., Hamaz, I., & Houssin, L. (2021). A Benders decomposition for the flexible cyclic jobshop problem. In 17th Internatinal Workshop on Project Management and Scheduling.
Saidat, S., Junoh, A. K., Wan Muhamad, W. Z. A., & Yahya, Z. (2022). Modified job shop scheduling via Taguchi method and genetic algorithm. Neural Computing and Applications, 1-18.
Smutnicki, C., & Pempera, J. (2022). Job Shop Scheduling with Transport by Automated Guided Vehicles. In 16th In-ternational Conference on Soft Computing Models in Industrial and Environmental Applications ,789-799.
Stein, D. M. (1978). Scheduling dial-a-ride transportation systems. Transportation Science, 12(3), 232-249.
Sun, X., & Noble, J. S. (1999). An approach to job shop scheduling with sequence-dependent setups. Journal of Manu-facturing Systems, 18(6), 416-430.
Türkyılmaz, A., Şenvar, Ö., Ünal, İ., & Bulkan, S. (2020). A research survey: heuristic approaches for solving multi ob-jective flexible job shop problems. Journal of Intelligent Manufacturing, 31, 1949-1983.
Ulusoy, G., Sivrikaya-Şerifoǧlu, F., & Bilge, Ü. (1997). A genetic algorithm approach to the simultaneous scheduling of machines and automated guided vehicles. Computers & Operations Research, 24(4), 335-351.
Vancheeswaran, R., & Townsend, M. A. (1993). Two-stage heuristic procedure for scheduling job shops. Journal of Manufacturing Systems, 12(4), 315-325.
Vital-Soto, A., Azab, A., & Baki, M. F. (2020). Mathematical modeling and a hybridized bacterial foraging optimiza-tion algorithm for the flexible job-shop scheduling problem with sequencing flexibility. Journal of Manufacturing Systems, 54, 74-93.
Xie, J., Gao, L., Peng, K., Li, X., & Li, H. (2019). Review on flexible job shop scheduling. IET collaborative intelligent manufacturing, 1(3), 67-77.
Yang, L., Li, J., Chao, F., Hackney, P., & Flanagan, M. (2021). Job shop planning and scheduling for manufacturers with manual operations. Expert Systems, 38(7), e12315.
Zeng, C., Tang, J., & Yan, C. (2015). Job-shop cell-scheduling problem with inter-cell moves and automated guided ve-hicles. Journal of Intelligent Manufacturing, 26, 845-859.
Zhang, F., Mei, Y., Nguyen, S., Tan, K. C., & Zhang, M. (2021). Multitask genetic programming-based generative hy-perheuristics: A case study in dynamic scheduling. IEEE Transactions on Cybernetics, 52(10), 10515-10528.
Zhang, H., Yang, Y., & Wu, F. (2022). Just-in-time single-batch-processing machine scheduling. Computers & Opera-tions Research, 140, 105675.
Zhang, M., Tao, F., & Nee, A. Y. C. (2021). Digital twin enhanced dynamic job-shop scheduling. Journal of Manufac-turing Systems, 58, 146-156.
Zhang, Q., Manier, H., & Manier, M. A. (2012). A genetic algorithm with tabu search procedure for flexible job shop scheduling with transportation constraints and bounded processing times. Computers & Operations Research, 39(7), 1713-1723.
Zhang, Q., Manier, H., & Manier, M. A. (2014). 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.
Zhou, B., & Liao, X. (2020). Particle filter and Levy flight-based decomposed multi-objective evolution hybridized par-ticle swarm for flexible job shop greening scheduling with crane transportation. Applied Soft Computing, 91, 106217.
Abukhader, R., & Kakoore, S. (2021). Artificial Intelligence for Vertical Farming–Controlling the Food Production.
Ahmadian, M. M., Salehipour, A., & Cheng, T. C. E. (2021). A meta-heuristic to solve the just-in-time job-shop sched-uling problem. European Journal of Operational Research, 288(1), 14-29.
Alaya, B. (2017, April). EE-(m, k)-Firm: A Method to Dynamic Service Level Management in Enterprise Environment. In International Conference on Enterprise Information Systems, 2, 114-122.
Álvarez-Gil, N., Rosillo, R., de la Fuente, D., & Pino, R. (2021). A discrete firefly algorithm for solving the flexible job-shop scheduling problem in a make-to-order manufacturing system. Central European Journal of Operations Research, 29, 1353-1374.
Baykasoğlu, A., Hamzadayi, A., & Köse, S. Y. (2014). Testing the performance of teaching–learning based optimization (TLBO) algorithm on combinatorial problems: Flow shop and job shop scheduling cases. Information Sciences, 276, 204-218.
Bueno, A., Godinho F., Moacir, F., & Alejandro, G. (2020). Smart production planning and control in the Industry 4.0 context. Computers industrial engineering, 149, 106774.
Cebi, C., Atac, E., & Sahingoz, O. K. (2020, July). Job shop scheduling problem and solution algorithms: a review. In 2020 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT),1-7.
Cordeau, J. F., & Laporte, G. (2003). A tabu search heuristic for the static multi-vehicle dial-a-ride prob-lem. Transportation Research Part B: Methodological, 37(6), 579-594.
Cunha, B., Madureira, A. M., Fonseca, B., & Coelho, D. (2020). Deep reinforcement learning as a job shop scheduling solver. In Hybrid Intelligent Systems: 18th International Conference on Hybrid Intelligent Systems (HIS 2018), 350-359.
Dean, W. (2015). Computational Complexity Theory, The Stanford Encyclopedia of Philosophy , Edward N. Zal-ta (ed.), https://plato.stanford.edu/archives/fall2021/entries/computational-complexity/>
Firat, M., & Woeginger, G. J. (2011). Analysis of the dial-a-ride problem of Hunsaker and Savelsbergh. Operations Re-search Letters, 39(1), 32-35.
Frihat, M., Hadj-Alouane, A. & Sadfi, C. (2022). Optimization of the integrated problem of employee timetabling and job shop scheduling. Computers & Operations Research, 137, 105332.
Gaham, M., Bouzouia, B., & Achour, N. (2018). An effective operations permutation-based discrete harmony search approach for the flexible job shop scheduling problem with makespan criterion. Applied Intelligence, 48, 1423-1441.
Gao, D., Wang, G. G., & Pedrycz, W. (2020). Solving fuzzy job-shop scheduling problem using DE algorithm improved by a selection mechanism. IEEE Transactions on Fuzzy Systems, 28(12), 3265-3275.
Gondran, M., Huguet, M. J., Lacomme, P., Quilliot, A., & Tchernev, N. (2018). A Dial-a-Ride evaluation for solving the job-shop with routing considerations. Engineering Applications of Artificial Intelligence, 74, 70-89.
Gondran, M., Lacomme, P., & Tchernev, N. (2017). Resolution of a job-shop with routing considering a quality of ser-vice for customer: JSSP with routing. In 7th International Conference on Industrial Engineering and Systems Man-agement (IESM).
Graham, R. L., Lawler, E. L., Lenstra, J. K., & Kan, A. R. (1979). Optimization and approximation in deterministic se-quencing and scheduling: a survey. In Annals of discrete mathematics , 5, 287-326.
Haifei, Y., Songjian, H., Dongsheng ,Y., Zhiyong,W., Wei ,F.,&Atila B.(2021). Job Shop Scheduling Based on Digital Twin Technology. Complexity, (2021),1-12 https://doi.org/10.1155/2021/8823273.
He, P., & Hao, J. K. (2023). Memetic search for the minmax multiple traveling salesman problem with single and mul-tiple depots. European Journal of Operational Research, 307(3), 1055-1070.
Hegen, X., Shuangyuan, S., Danni, R., & Jinjin, H. (2022). A survey of job shop scheduling problem: the types and models. Computers Operations Research, 142,105731, doi.org/10.1016/j.cor.2022.105731.
Hurink, J., & Knust, S. (2005). Tabu search algorithms for job-shop problems with a single transport robot. European journal of operational research, 162(1), 99-111.
Hussein, M., & Zayed, T. (2021). Critical factors for successful implementation of just-in-time concept in modular in-tegrated construction: A systematic review and meta-analysis. Journal of Cleaner Production, 284, 124716.
Jain, A. S., & Meeran, S. (1999). Deterministic job-shop scheduling: Past, present and future. European journal of op-erational research, 113(2), 390-434.
Jamili, A. (2016). Robust job shop scheduling problem: Mathematical models, exact and heuristic algorithms. Expert systems with Applications, 55, 341-350.
Kalshetty, Y. R., Adamuthe, A. C., & Kumar, S. P. (2020). Genetic algorithms with feasible operators for solving job shop scheduling problem. Journal of Science Resources, 64, 310-321.
Kardos, C., Laflamme, C., Gallina, V., & Sihn, W. (2021). Dynamic scheduling in a job-shop production system with reinforcement learning. Procedia CIRP, 97, 104-109.
Kechadi, M. T., Low, K. S., & Goncalves, G. (2013). Recurrent neural network approach for cyclic job shop scheduling problem. Journal of Manufacturing Systems, 32(4), 689-699.
Lacomme, P., Larabi, M., & Tchernev, N. (2013). Job-shop based framework for simultaneous scheduling of machines and automated guided vehicles. International Journal of Production Economics, 143(1), 24-34.
Lee, T., & Loong, Y. (2019). A review of scheduling problem and resolution methods in exible ow shop. International Journal of Industrial Engineering Computations, 10(1), 67-88.
Li, X., Xie, J., Ma, Q., Gao, L., & Li, P. (2022). Improved gray wolf optimizer for distributed flexible job shop schedul-ing problem. Science China Technological Sciences, 65(9), 2105-2115.
Mihoubi, B., Bouzouia, B., & Gaham, M. (2021). Reactive scheduling approach for solving a realistic flexible job shop scheduling problem. International journal of production research, 59(19), 5790-5808.
Mohan, J., Lanka, K., & Rao, A. N. (2019). A review of dynamic job shop scheduling techniques. Procedia Manufactur-ing, 30, 34-39.
Nouri, H. E., Driss, O. B., & Ghédira, K. (2016). A classification schema for the job shop scheduling problem with transportation resources: state-of-the-art review. In Artificial Intelligence Perspectives in Intelligent Systems: Pro-ceedings of the 5th Computer Science On-line Conference 2016 (CSOC2016), 1, 1-11.
Ojstersek, R., Brezocnik, M.,&Buchmeister, B. (2020). Multi-objective optimization of production scheduling with evolutionary computation. International Journal of Industrial Engineering Computations, 11(3), 359-376.
Pappas, I., Kourouthanassis, P., Giannakos, M.,& Lekakos, G. (2017). The interplay of online shopping motivations and experiential factors on personalized e-commerce. Telematics and informatics, 34(5), 730-742.
Parveen, S., & Ullah, H. (2010). Review on job-shop and flow-shop scheduling using. Journal of Mechanical Engineer-ing, 41(2), 130-146.
Prins, C. (2009). A GRASP× evolutionary local search hybrid for the vehicle routing problem. In Bio-inspired algo-rithms for the vehicle routing problem, 35-53.
Quinton, F., Hamaz, I., & Houssin, L. (2021). A Benders decomposition for the flexible cyclic jobshop problem. In 17th Internatinal Workshop on Project Management and Scheduling.
Saidat, S., Junoh, A. K., Wan Muhamad, W. Z. A., & Yahya, Z. (2022). Modified job shop scheduling via Taguchi method and genetic algorithm. Neural Computing and Applications, 1-18.
Smutnicki, C., & Pempera, J. (2022). Job Shop Scheduling with Transport by Automated Guided Vehicles. In 16th In-ternational Conference on Soft Computing Models in Industrial and Environmental Applications ,789-799.
Stein, D. M. (1978). Scheduling dial-a-ride transportation systems. Transportation Science, 12(3), 232-249.
Sun, X., & Noble, J. S. (1999). An approach to job shop scheduling with sequence-dependent setups. Journal of Manu-facturing Systems, 18(6), 416-430.
Türkyılmaz, A., Şenvar, Ö., Ünal, İ., & Bulkan, S. (2020). A research survey: heuristic approaches for solving multi ob-jective flexible job shop problems. Journal of Intelligent Manufacturing, 31, 1949-1983.
Ulusoy, G., Sivrikaya-Şerifoǧlu, F., & Bilge, Ü. (1997). A genetic algorithm approach to the simultaneous scheduling of machines and automated guided vehicles. Computers & Operations Research, 24(4), 335-351.
Vancheeswaran, R., & Townsend, M. A. (1993). Two-stage heuristic procedure for scheduling job shops. Journal of Manufacturing Systems, 12(4), 315-325.
Vital-Soto, A., Azab, A., & Baki, M. F. (2020). Mathematical modeling and a hybridized bacterial foraging optimiza-tion algorithm for the flexible job-shop scheduling problem with sequencing flexibility. Journal of Manufacturing Systems, 54, 74-93.
Xie, J., Gao, L., Peng, K., Li, X., & Li, H. (2019). Review on flexible job shop scheduling. IET collaborative intelligent manufacturing, 1(3), 67-77.
Yang, L., Li, J., Chao, F., Hackney, P., & Flanagan, M. (2021). Job shop planning and scheduling for manufacturers with manual operations. Expert Systems, 38(7), e12315.
Zeng, C., Tang, J., & Yan, C. (2015). Job-shop cell-scheduling problem with inter-cell moves and automated guided ve-hicles. Journal of Intelligent Manufacturing, 26, 845-859.
Zhang, F., Mei, Y., Nguyen, S., Tan, K. C., & Zhang, M. (2021). Multitask genetic programming-based generative hy-perheuristics: A case study in dynamic scheduling. IEEE Transactions on Cybernetics, 52(10), 10515-10528.
Zhang, H., Yang, Y., & Wu, F. (2022). Just-in-time single-batch-processing machine scheduling. Computers & Opera-tions Research, 140, 105675.
Zhang, M., Tao, F., & Nee, A. Y. C. (2021). Digital twin enhanced dynamic job-shop scheduling. Journal of Manufac-turing Systems, 58, 146-156.
Zhang, Q., Manier, H., & Manier, M. A. (2012). A genetic algorithm with tabu search procedure for flexible job shop scheduling with transportation constraints and bounded processing times. Computers & Operations Research, 39(7), 1713-1723.
Zhang, Q., Manier, H., & Manier, M. A. (2014). 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.
Zhou, B., & Liao, X. (2020). Particle filter and Levy flight-based decomposed multi-objective evolution hybridized par-ticle swarm for flexible job shop greening scheduling with crane transportation. Applied Soft Computing, 91, 106217.