Document Type : Original Article

Authors

Department of Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran.

Abstract

In this study, the problem of simultaneous determination of order acceptance, scheduling and batch delivery considering sequence-dependent setup and capacity constraint has been presented. This problem is a combination of the three problems of order acceptance, scheduling and batch delivery. The most important innovation of this research is the simultaneous optimization of profits and the total weighted earliness and tardiness as two conflicting objectives in the problem of combining order, scheduling and batch delivery. Another innovation of this research is the use of multi-objective Grey Wolf Optimization (GWO) algorithm, which has not been used in studies of this field so far. It has also been shown that the multi-objective Grey Wolf Optimization algorithm is comparable to the exact solution methods. The second part of the numerical results compares the results of the ε-constraint method, NSGA-II and the multi-objective Grey Wolf Optimization algorithm. The results of this section show that by increasing the scale of the problem, the efficiency of the multi- objective Grey Wolf Optimization algorithm is better displayed, and in general, this method has a significant advantage relative to NSGA-II and ε-constraint in terms of DM, SNS and NPS indicators. Also, the solving time of this method is very shorter than that of the ε-constraint. Therefore, from a managerial point of view, a tool called the multi-objective Grey Wolf Optimization algorithm can be used as an efficient tool for supply and production managers, which is able to provide several optimal solutions with different profits, earliness and tardiness.

Keywords

Ayough, A., and Khorshidvand, B., (2019). "Designing a manufacturing cell system by assigning workforce", Journal of Industrial Engineering and Management, Vol. 12, No. 1, pp. 13-26.
Ayough, A., Hosseinzadeh, M., and Motameni, A., (2020). "Job rotation scheduling in the Seru system: shake enforced invasive weed optimization approach", Assembly Automation.
Babaee Tirkolaee, E., Goli, A., Pahlevan, M., and Malekalipour Kordestanizadeh, R., (2019). "A robust bi-objective multi-trip periodic capacitated arc routing problem for urban waste collection using a multi-objective invasive weed optimization", Waste Management & Research, Vol. 37, No. 11, pp. 1089-1101.
Chen, Z.L., (1996). "Scheduling and common due date assignment with earliness-tardiness penalties and batch delivery costs", European Journal of Operational Research, Vol. 93, No. 1, pp. 49-60.
Dametew, A. W., Ketaw, D., and Frank, E., (2019). "Production planning and control strategies used as a gear train for the death and birth of manufacturing industries", Journal of Optimization in Industrial Engineering, Vol. 12, No. 2, pp. 21-32.
Ghasemi, P., and Khalili-Damghani, K., (2021). "A robust simulation-optimization approach for pre-disaster multi-period location–allocation–inventory planning", Mathematics and computers in simulation, Vol. 179, pp. 69-95.
Ghasemi, P., and Talebi Brijani, E., (2014). "An integrated FAHP-PROMETHEE approach for Selecting the best Flexible Manufacturing system", European Online Journal of Natural and Social Sciences, Vol. 3, No. 4, pp-1137.
Ghasemi, P., Khalili-Damghani, K., Hafezalkotob, A., and Raissi, S., (2020). "Stochastic optimization model for distribution and evacuation planning (A case study of Tehran earthquake)", Socio-Economic Planning Sciences, Vol. 71, 100745.
Goli, A., Tirkolaee, E.B., Malmir, B., Bian, G.B., and Sangaiah, A.K., (2019). "A multi-objective invasive weed optimization algorithm for robust aggregate production planning under uncertain seasonal demand", Computing, Vol. 101, No. 6, pp. 499-529.
Iranpoor, M., Ghomi, S.F., and Zandieh, M., (2014). "Order acceptance and due-date quotation in low machine rates", Applied Mathematical Modelling, Vol. 38, No. (7-8), pp. 2063-2072.
Jiang, D., Tan, J., and Li, B., (2017). "Order acceptance and scheduling with batch delivery", Computers & Industrial Engineering, Vol. 107, pp. 100-104.
Kück, M., and Freitag, M., (2021). "Forecasting of customer demands for production planning by local k-nearest neighbor models", International Journal of Production Economics, Vol. 231, 107837.
Lu, L., Ng, C.T., and Zhang, L., (2011). "Optimal algorithms for single-machine scheduling with rejection to minimize the makespan", International Journal of Production Economics, Vol. 130, No. 2, pp. 153-158.
Mgbemena, C.O., Chinwuko, E., and Ifowodo, H.F., (2020). "Production Constraints Modelling: A Tactical Review Approach", Journal of Optimization in Industrial Engineering, Vol. 13, No. 1, pp. 19-27.
Mirjalili, S., Mirjalili, S.M., and Lewis, A., (2014). "Grey wolf optimizer", Advances in engineering software, Vol. 69, pp. 46-61.
Mokhtari, H., (2015). "A nature inspired intelligent water drops evolutionary algorithm for parallel processor scheduling with rejection", Applied Soft Computing, Vol. 26, pp. 166-179.
Okpoti, E.S., and Jeong, I.J., (2021). "A reactive decentralized coordination algorithm for event-driven production planning and control: A cyber-physical production system prototype case study", Journal of Manufacturing Systems, Vol. 58, pp. 143-158.
Ou, J., Zhong, X., and Wang, G., (2015). "An improved heuristic for parallel machine scheduling with rejection", European Journal of Operational Research, Vol. 241, No. 3, pp. 653-661.
Ramyar, M., Mehdizadeh, E., and Hadji Molana, S.M., (2020). "A new bi-objective mathematical model to optimize reliability and cost of aggregate production planning system in a paper and wood company", Journal of Optimization in Industrial Engineering, Vol. 13, No. 1, pp. 81-98.
Satyro, W.C., de Mesquita Spinola, M., de Almeida, C.M., Giannetti, B.F., Sacomano, J.B., Contador, J.C., and Contador, J.L., (2021). "Sustainable industries: Production planning and control as an ally to implement strategy", Journal of Cleaner Production, Vol. 281, 124781.
Tirkolaee, E.B., Goli, A., and Weber, G.W., (2019, May). "Multi-objective aggregate production planning model considering overtime and outsourcing options under fuzzy seasonal demand", In: International Scientific-Technical Conference MANUFACTURING (pp. 81-96). Springer, Cham.
Tirkolaee, E.B., Goli, A., and Weber, G.W., (2020). "Fuzzy mathematical programming and self-adaptive artificial fish swarm algorithm for just-in-time energy-aware flow shop scheduling problem with outsourcing option", IEEE transactions on fuzzy systems, Vol. 28, No. 11, pp. 2772-2783.
Tirkolaee, E.B., Mardani, A., Dashtian, Z., Soltani, M., and Weber, G.W., (2020). "A novel hybrid method using fuzzy decision making and multi-objective programming for sustainable-reliable supplier selection in two-echelon supply chain design", Journal of Cleaner Production, Vol. 250, 119517.
Wang, B., and Wang, H., (2018). "Multiobjective order acceptance and scheduling on unrelated parallel machines with machine eligibility constraints", Mathematical Problems in Engineering.
Yang, B., and Geunes, J., (2007). "A single resource scheduling problem with job-selection flexibility, tardiness costs and controllable processing times", Computers & Industrial Engineering, Vol. 53, No. 3, pp. 420-432.
Yin, Y., Cheng, T.C.E., Hsu, C.J., and Wu, C.C., (2013). "Single-machine batch delivery scheduling with an assignable common due window", Omega, Vol. 41, No. 2, pp. 216-225.
Yin, Y., Ye, D., and Zhang, G., (2014). "Single machine batch scheduling to minimize the sum of total flow time and batch delivery cost with an unavailability interval", Information Sciences, Vol. 274, pp. 310-322.