How to cite this paper
Chaudhry, I., Rafique, A., Elbadawi, I., Aichouni, M., Usman, M., Boujelbene, M & Boudjemline, A. (2022). Integrated scheduling of machines and automated guided vehicles (AGVs) in flexible job shop environment using genetic algorithms.International Journal of Industrial Engineering Computations , 13(3), 343-362.
Refrences
Abdelmaguid, T. F., Nassef, A. O., Kamal, B. A., & Hassan, M. F. (2004). A hybrid GA/heuristic approach to the simultaneous scheduling of machines and automated guided vehicles. International Journal of Production Research, 42(2), 267-281.
Abderrahim, M., Bekrar, A., Trentesaux, D., Aissani, N., & Bouamrane, K. (2020). Bi-local search based variable neighborhood search for job-shop scheduling problem with transport constraints. Optimization Letters.
Adams, J., Balas, E., & Zawack, D. (1988). The Shifting Bottleneck Procedure for Job Shop Scheduling. Management Science, 34(3), 391-401.
Agrama, F. A. (2015, 3-5 March 2015). Versatile multi-objective genetic optimization for non-identical multi-storey building projects. Paper presented at the 2015 International Conference on Industrial Engineering and Operations Management (IEOM).
Amaral, J., & Kuettner, D. (2008). Analyzing Supply Chains at HP Using Spreadsheet Models. INFORMS Journal on Applied Analytics, 38(4), 228-240.
Amjad, M. K., Butt, S. I., Kousar, R., Ahmad, R., Agha, M. H., Faping, Z., . . . Asgher, U. (2018). Recent Research Trends in Genetic Algorithm Based Flexible Job Shop Scheduling Problems. Mathematical Problems in Engineering, 2018, 32 pages.
Arabpour Roghabadi, M., & Moselhi, O. (2021). Optimized crew selection for scheduling of repetitive projects. Engineering, Construction and Architectural Management, 28(6), 1517-1540.
Babu, A. G., Jerald, J., Haq, A. N., Luxmi, V. M., & Vigneswaralu, T. P. (2010). Scheduling of machines and automated guided vehicles in FMS using differential evolution. International Journal of Production Research, 48(16), 4683-4699.
Baruwa, O. T., & Piera, M. A. (2016). A coloured Petri net-based hybrid heuristic search approach to simultaneous scheduling of machines and automated guided vehicles. International Journal of Production Research, 54(16), 4773.
Bilge, Ü., & Ulusoy, G. (1995). A Time Window Approach to Simultaneous Scheduling of Machines and Material Handling System in an FMS. Operations Research, 43(6), 1058-1070.
Bin Md Fauadi, M. H. F., & Murata, T. (2010). Makespan Minimization of Machines and Automated Guided Vehicles Schedule Using Binary Particle Swarm Optimization. Lecture Notes in Engineering and Computer Science, 2182.
Chaudhry, I. A., Elbadawi, I. A., Usman, M., & Chughtai, M. T. (2018). Minimising Total Flowtime in a No-Wait Flow Shop (NWFS) using Genetic Algorithms. 2018, 38(3), 12.
Chaudhry, I. A., & Khan, A. A. (2016). A research survey: review of flexible job shop scheduling techniques. International Transactions in Operational Research, 23(3), 551–591.
Chaudhry, I. A., & Usman, M. (2017). Integrated process planning and scheduling using genetic algorithms. Technical Gazette, 24(5), 1401-1409.
Dang, Q.-V., Nguyen, C. T., & Rudová, H. (2019). Scheduling of mobile robots for transportation and manufacturing tasks. Journal of Heuristics, 25(2), 175-213.
Davis, L. (1991). Handbook of Genetic Algorithms. New York, USA: Van Nostrand Reinhold.
Deroussi, L., Gourgand, M., & Tchernev, N. (2008). A simple metaheuristic approach to the simultaneous scheduling of machines and automated guided vehicles. International Journal of Production Research, 46(8), 2143-2164.
Deroussi, L., & Norre, S. (2010). Simultaneous scheduling of machines and vehicles for the flexible job shop problem. Paper presented at the International Conference on Metaheuristics and Nature Inspired Computing, Djerba Island, Tunisia.
Đorđević Milutinović, L., Makajić-Nikolić, D., Antić, S., ŽIvić, M., & Lisec, A. (2021). CONTROL MODEL FOR GROUND CREW SCHEDULING PROBLEM AT SMALL AIRPORTS: CASE OF SERBIA. Transport (16484142), 36(3), 235-245.
Erol, R., Sahin, C., Baykasoglu, A., & Kaplanoglu, V. (2012). A multi-agent based approach to dynamic scheduling of machines and automated guided vehicles in manufacturing systems. Applied Soft Computing, 12(6), 1720-1732.
Farmakis, P. M., & Chassiakos, A. P. (2018). Genetic algorithm optimization for dynamic construction site layout planning. Organization, Technology and Management in Construction, 10(1), 1655–1664.
Fattahi, P., Saidi-Mehrabad, M., & Jolai, F. (2007). Mathematical modeling and heuristic approaches to flexible job shop scheduling problems. [Makespan]. Journal of Intelligent Manufacturing, 18(3), 331-342.
Fontes, D. B. M. M., & Homayouni, S. M. (2019). Joint production and transportation scheduling in flexible manufacturing systems. Journal of Global Optimization, 74(4), 879-908.
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.
Gu, W., Li, Y., Zheng, K., & Yuan, M. (2020). A bio-inspired scheduling approach for machines and automated guided vehicles in flexible manufacturing system using hormone secretion principle. Advances in Mechanical Engineering, 12(2), 1687814020907787.
Homayouni, S. M., & Fontes, D. B. M. M. (2019). Joint scheduling of production and transport with alternative job routing in flexible manufacturing systems. AIP Conference Proceedings, 2070(1), 020045.
Homayouni, S. M., & Fontes, D. B. M. M. (2021). Production and transport scheduling in flexible job shop manufacturing systems. Journal of Global Optimization, 79(2), 463-502.
Homayouni, S. M., Fontes, D. B. M. M., & Gonçalves, J. F. (2020). A multistart biased random key genetic algorithm for the flexible job shop scheduling problem with transportation. International Transactions in Operational Research, n/a(n/a).
Kacem, I., Hammadi, S., & Borne, P. (2002). Pareto-optimality approach for flexible job-shop scheduling problems: hybridization of evolutionary algorithms and fuzzy logic. [Min of makespan, workload of most loaded machine, total workload of machines]. Mathematics and Computers in Simulation, 60(3–5), 245-276.
Karimi, S., Ardalan, Z., Naderi, B., & Mohammadi, M. (2017). Scheduling flexible job-shops with transportation times: Mathematical models and a hybrid imperialist competitive algorithm. Applied Mathematical Modelling, 41, 667-682.
Kumar, M., Janardhana, R., & Rao, C. (2011). Simultaneous scheduling of machines and vehicles in an FMS environment with alternative routing. International Journal of Advanced Manufacturing Technology, 53(1-4), 339-351.
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.
Lyu, X., Song, Y., He, C., Lei, Q., & Guo, W. (2019). Approach to Integrated Scheduling Problems Considering Optimal Number of Automated Guided Vehicles and Conflict-Free Routing in Flexible Manufacturing Systems. IEEE Access, 7, 74909-74924.
Nouri, H. E., Driss, O. B., & Ghédira, K. (2016a). Hybrid metaheuristics for scheduling of machines and transport robots in job shop environment. Applied Intelligence, 45(3), 808-828.
Nouri, H. E., Driss, O. B., & Ghédira, K. (2016b). Simultaneous scheduling of machines and transport robots in flexible job shop environment using hybrid metaheuristics based on clustered holonic multiagent model. Computers & Industrial Engineering, 102, 488-501.
Nusen, P., Boonyung, W., Nusen, S., Panuwatwanich, K., Champrasert, P., & Kaewmoracharoen, M. (2021). Construction Planning and Scheduling of a Renovation Project Using BIM-Based Multi-Objective Genetic Algorithm. Applied Sciences, 11(11), 4716.
Othman, S. N., Mustaffa, N. H., & Sallehuddin, R. (2012, 25-27 Sept. 2012). Supply Chain Spreadsheet Simulation Optimization. Paper presented at the 2012 Fourth International Conference on Computational Intelligence, Modelling and Simulation.
Palisade. (1998). Evolver: The genetic algorithm super solver Version 4. New York, USA: Palisade Corporation.
Politis, S. S., Zhang, Z., Han, Z., Hasenbein, J. J., & Arellano, M. (2021). Stochastic Analysis of Network-Level Bridge Maintenance Needs Using Latin Hypercube Sampling. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 7(1), 04020049.
Reddy, B. S. P., & Rao, C. S. P. (2006). A hybrid multi-objective GA for simultaneous scheduling of machines and AGVs in FMS. International Journal of Advanced Manufacturing Technology, 31(5/6), 602-613.
Sahin, C., Demirtas, M., Erol, R., Baykasoğlu, A., & Kaplanoğlu, V. (2017). A multi-agent based approach to dynamic scheduling with flexible processing capabilities. Journal of Intelligent Manufacturing, 28(8), 1827-1845.
Salama, T. (2019). Multi-objective optimization for repetitive scheduling under uncertainty. Engineering, Construction and Architectural Management, 26(7), 1294-1320.
Shen, L., Dauzère-Pérès, S., & Neufeld, J. S. (2018). Solving the flexible job shop scheduling problem with sequence-dependent setup times. European Journal of Operational Research, 265(2), 503-516.
Souar, Y., & Mouffok, O. (2014). Using Genetic Algorithms in Integer Programming for Decision Support. Valahian Journal of Economic Studies, 5(1), 55-62.
Sperlich, A., Pfeiffer, D., Burgschweiger, J., Campbell, E., Beck, M., Gnirss, R., & Ernst, M. (2018). Energy Efficient Operation of Variable Speed Submersible Pumps: Simulation of a Ground Water Well Field. Water, 10(9), 1255.
Subbaiah, K., Nageswara Rao, M., & Narayana Rao, K. (2009). Scheduling of AGVs and machines in FMS with makespan criteria using sheep flock heredity algorithm. International Journal of Physical Sciences, 4.
Syswerda, G. (1989). Uniform Crossover in Genetic Algorithms. Paper presented at the Proceedings of the 3rd International Conference on Genetic Algorithms.
Türkyılmaz, A., Şenvar, Ö., Ünal, İ., & Bulkan, S. (2020). A research survey: heuristic approaches for solving multi objective flexible job shop problems. Journal of Intelligent Manufacturing, 31(8), 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.
Zhang, G. H., Sun, J. H., Liu, X., Wang, G. D., & Yang, Y. Y. (2019). Solving flexible job shop scheduling problems with transportation time based on improved genetic algorithm. Math Biosci Eng, 16(3), 1334-1347.
Zhang, Q., Manier, H., & Manier, M.-A. (2013). Metaheuristics for Job Shop Scheduling with Transportation. In B. Jarboui, P. Siarry, & J. Teghem (Eds.), Metaheuristics for Production Scheduling (pp. 465-493): John Wiley & Sons, Inc.
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.
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.
Zheng, K., Tang, D., Giret, A., Salido, M. A., & Sang, Z. (2018). A hormone regulation–based approach for distributed and on-line scheduling of machines and automated guided vehicles. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 232(1), 99-113.
Zheng, Y., Xiao, Y., & Seo, Y. (2014). A tabu search algorithm for simultaneous machine/AGV scheduling problem. International Journal of Production Research, 52(19), 5748-5763.
Abderrahim, M., Bekrar, A., Trentesaux, D., Aissani, N., & Bouamrane, K. (2020). Bi-local search based variable neighborhood search for job-shop scheduling problem with transport constraints. Optimization Letters.
Adams, J., Balas, E., & Zawack, D. (1988). The Shifting Bottleneck Procedure for Job Shop Scheduling. Management Science, 34(3), 391-401.
Agrama, F. A. (2015, 3-5 March 2015). Versatile multi-objective genetic optimization for non-identical multi-storey building projects. Paper presented at the 2015 International Conference on Industrial Engineering and Operations Management (IEOM).
Amaral, J., & Kuettner, D. (2008). Analyzing Supply Chains at HP Using Spreadsheet Models. INFORMS Journal on Applied Analytics, 38(4), 228-240.
Amjad, M. K., Butt, S. I., Kousar, R., Ahmad, R., Agha, M. H., Faping, Z., . . . Asgher, U. (2018). Recent Research Trends in Genetic Algorithm Based Flexible Job Shop Scheduling Problems. Mathematical Problems in Engineering, 2018, 32 pages.
Arabpour Roghabadi, M., & Moselhi, O. (2021). Optimized crew selection for scheduling of repetitive projects. Engineering, Construction and Architectural Management, 28(6), 1517-1540.
Babu, A. G., Jerald, J., Haq, A. N., Luxmi, V. M., & Vigneswaralu, T. P. (2010). Scheduling of machines and automated guided vehicles in FMS using differential evolution. International Journal of Production Research, 48(16), 4683-4699.
Baruwa, O. T., & Piera, M. A. (2016). A coloured Petri net-based hybrid heuristic search approach to simultaneous scheduling of machines and automated guided vehicles. International Journal of Production Research, 54(16), 4773.
Bilge, Ü., & Ulusoy, G. (1995). A Time Window Approach to Simultaneous Scheduling of Machines and Material Handling System in an FMS. Operations Research, 43(6), 1058-1070.
Bin Md Fauadi, M. H. F., & Murata, T. (2010). Makespan Minimization of Machines and Automated Guided Vehicles Schedule Using Binary Particle Swarm Optimization. Lecture Notes in Engineering and Computer Science, 2182.
Chaudhry, I. A., Elbadawi, I. A., Usman, M., & Chughtai, M. T. (2018). Minimising Total Flowtime in a No-Wait Flow Shop (NWFS) using Genetic Algorithms. 2018, 38(3), 12.
Chaudhry, I. A., & Khan, A. A. (2016). A research survey: review of flexible job shop scheduling techniques. International Transactions in Operational Research, 23(3), 551–591.
Chaudhry, I. A., & Usman, M. (2017). Integrated process planning and scheduling using genetic algorithms. Technical Gazette, 24(5), 1401-1409.
Dang, Q.-V., Nguyen, C. T., & Rudová, H. (2019). Scheduling of mobile robots for transportation and manufacturing tasks. Journal of Heuristics, 25(2), 175-213.
Davis, L. (1991). Handbook of Genetic Algorithms. New York, USA: Van Nostrand Reinhold.
Deroussi, L., Gourgand, M., & Tchernev, N. (2008). A simple metaheuristic approach to the simultaneous scheduling of machines and automated guided vehicles. International Journal of Production Research, 46(8), 2143-2164.
Deroussi, L., & Norre, S. (2010). Simultaneous scheduling of machines and vehicles for the flexible job shop problem. Paper presented at the International Conference on Metaheuristics and Nature Inspired Computing, Djerba Island, Tunisia.
Đorđević Milutinović, L., Makajić-Nikolić, D., Antić, S., ŽIvić, M., & Lisec, A. (2021). CONTROL MODEL FOR GROUND CREW SCHEDULING PROBLEM AT SMALL AIRPORTS: CASE OF SERBIA. Transport (16484142), 36(3), 235-245.
Erol, R., Sahin, C., Baykasoglu, A., & Kaplanoglu, V. (2012). A multi-agent based approach to dynamic scheduling of machines and automated guided vehicles in manufacturing systems. Applied Soft Computing, 12(6), 1720-1732.
Farmakis, P. M., & Chassiakos, A. P. (2018). Genetic algorithm optimization for dynamic construction site layout planning. Organization, Technology and Management in Construction, 10(1), 1655–1664.
Fattahi, P., Saidi-Mehrabad, M., & Jolai, F. (2007). Mathematical modeling and heuristic approaches to flexible job shop scheduling problems. [Makespan]. Journal of Intelligent Manufacturing, 18(3), 331-342.
Fontes, D. B. M. M., & Homayouni, S. M. (2019). Joint production and transportation scheduling in flexible manufacturing systems. Journal of Global Optimization, 74(4), 879-908.
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.
Gu, W., Li, Y., Zheng, K., & Yuan, M. (2020). A bio-inspired scheduling approach for machines and automated guided vehicles in flexible manufacturing system using hormone secretion principle. Advances in Mechanical Engineering, 12(2), 1687814020907787.
Homayouni, S. M., & Fontes, D. B. M. M. (2019). Joint scheduling of production and transport with alternative job routing in flexible manufacturing systems. AIP Conference Proceedings, 2070(1), 020045.
Homayouni, S. M., & Fontes, D. B. M. M. (2021). Production and transport scheduling in flexible job shop manufacturing systems. Journal of Global Optimization, 79(2), 463-502.
Homayouni, S. M., Fontes, D. B. M. M., & Gonçalves, J. F. (2020). A multistart biased random key genetic algorithm for the flexible job shop scheduling problem with transportation. International Transactions in Operational Research, n/a(n/a).
Kacem, I., Hammadi, S., & Borne, P. (2002). Pareto-optimality approach for flexible job-shop scheduling problems: hybridization of evolutionary algorithms and fuzzy logic. [Min of makespan, workload of most loaded machine, total workload of machines]. Mathematics and Computers in Simulation, 60(3–5), 245-276.
Karimi, S., Ardalan, Z., Naderi, B., & Mohammadi, M. (2017). Scheduling flexible job-shops with transportation times: Mathematical models and a hybrid imperialist competitive algorithm. Applied Mathematical Modelling, 41, 667-682.
Kumar, M., Janardhana, R., & Rao, C. (2011). Simultaneous scheduling of machines and vehicles in an FMS environment with alternative routing. International Journal of Advanced Manufacturing Technology, 53(1-4), 339-351.
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.
Lyu, X., Song, Y., He, C., Lei, Q., & Guo, W. (2019). Approach to Integrated Scheduling Problems Considering Optimal Number of Automated Guided Vehicles and Conflict-Free Routing in Flexible Manufacturing Systems. IEEE Access, 7, 74909-74924.
Nouri, H. E., Driss, O. B., & Ghédira, K. (2016a). Hybrid metaheuristics for scheduling of machines and transport robots in job shop environment. Applied Intelligence, 45(3), 808-828.
Nouri, H. E., Driss, O. B., & Ghédira, K. (2016b). Simultaneous scheduling of machines and transport robots in flexible job shop environment using hybrid metaheuristics based on clustered holonic multiagent model. Computers & Industrial Engineering, 102, 488-501.
Nusen, P., Boonyung, W., Nusen, S., Panuwatwanich, K., Champrasert, P., & Kaewmoracharoen, M. (2021). Construction Planning and Scheduling of a Renovation Project Using BIM-Based Multi-Objective Genetic Algorithm. Applied Sciences, 11(11), 4716.
Othman, S. N., Mustaffa, N. H., & Sallehuddin, R. (2012, 25-27 Sept. 2012). Supply Chain Spreadsheet Simulation Optimization. Paper presented at the 2012 Fourth International Conference on Computational Intelligence, Modelling and Simulation.
Palisade. (1998). Evolver: The genetic algorithm super solver Version 4. New York, USA: Palisade Corporation.
Politis, S. S., Zhang, Z., Han, Z., Hasenbein, J. J., & Arellano, M. (2021). Stochastic Analysis of Network-Level Bridge Maintenance Needs Using Latin Hypercube Sampling. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 7(1), 04020049.
Reddy, B. S. P., & Rao, C. S. P. (2006). A hybrid multi-objective GA for simultaneous scheduling of machines and AGVs in FMS. International Journal of Advanced Manufacturing Technology, 31(5/6), 602-613.
Sahin, C., Demirtas, M., Erol, R., Baykasoğlu, A., & Kaplanoğlu, V. (2017). A multi-agent based approach to dynamic scheduling with flexible processing capabilities. Journal of Intelligent Manufacturing, 28(8), 1827-1845.
Salama, T. (2019). Multi-objective optimization for repetitive scheduling under uncertainty. Engineering, Construction and Architectural Management, 26(7), 1294-1320.
Shen, L., Dauzère-Pérès, S., & Neufeld, J. S. (2018). Solving the flexible job shop scheduling problem with sequence-dependent setup times. European Journal of Operational Research, 265(2), 503-516.
Souar, Y., & Mouffok, O. (2014). Using Genetic Algorithms in Integer Programming for Decision Support. Valahian Journal of Economic Studies, 5(1), 55-62.
Sperlich, A., Pfeiffer, D., Burgschweiger, J., Campbell, E., Beck, M., Gnirss, R., & Ernst, M. (2018). Energy Efficient Operation of Variable Speed Submersible Pumps: Simulation of a Ground Water Well Field. Water, 10(9), 1255.
Subbaiah, K., Nageswara Rao, M., & Narayana Rao, K. (2009). Scheduling of AGVs and machines in FMS with makespan criteria using sheep flock heredity algorithm. International Journal of Physical Sciences, 4.
Syswerda, G. (1989). Uniform Crossover in Genetic Algorithms. Paper presented at the Proceedings of the 3rd International Conference on Genetic Algorithms.
Türkyılmaz, A., Şenvar, Ö., Ünal, İ., & Bulkan, S. (2020). A research survey: heuristic approaches for solving multi objective flexible job shop problems. Journal of Intelligent Manufacturing, 31(8), 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.
Zhang, G. H., Sun, J. H., Liu, X., Wang, G. D., & Yang, Y. Y. (2019). Solving flexible job shop scheduling problems with transportation time based on improved genetic algorithm. Math Biosci Eng, 16(3), 1334-1347.
Zhang, Q., Manier, H., & Manier, M.-A. (2013). Metaheuristics for Job Shop Scheduling with Transportation. In B. Jarboui, P. Siarry, & J. Teghem (Eds.), Metaheuristics for Production Scheduling (pp. 465-493): John Wiley & Sons, Inc.
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.
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.
Zheng, K., Tang, D., Giret, A., Salido, M. A., & Sang, Z. (2018). A hormone regulation–based approach for distributed and on-line scheduling of machines and automated guided vehicles. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 232(1), 99-113.
Zheng, Y., Xiao, Y., & Seo, Y. (2014). A tabu search algorithm for simultaneous machine/AGV scheduling problem. International Journal of Production Research, 52(19), 5748-5763.