Integrated production-distribution planning with make-To-order production system considering Stackelberg competition and discount for a Furniture Company

Document Type : Research Paper

Authors

1 School of Industrial Engineering, college of engineering, University of Tehran, Tehran, Iran

2 Department of Industrial Engineering, Faculty of Engineering, College of Farabi, University of Tehran, Qom, Iran

Abstract

Nowadays, in the competitive global market, increasing market share is the main objective of the most manufacturers, however, customization, service speed, customer satisfaction, and environmental problems are vital factors that manufacturers ought to consider to expand their market share.so, the supply chain management can be applied as a proper approach to optimize these factors in whole supply chain to benefit the supply chain members. In this way, the current paper addresses an integrated production and distribution model with combination of Stackelberg competition and Make-to-order production system in different periods. In addition, this model wants to investigate how discounts impact the chain's profits with presence of competition and Make-to-Order production system. This study uses a modified Non-Dominated Sorting Genetic Algorithm II (NSGA-II) approach to solve the medium and large cases model because of the NP-hardness feature. Additionally, the model is applied to Furniture Company to demonstrate its efficacy and validity and results are provided. According to the obtained results, the modified algorithm has better performance in solving model in medium and large-scale cases. The proposed model would be beneficial to increase network efficiency by integrating production-distribution planning.

Keywords

Main Subjects


Aazami, A., & Saidi-Mehrabad, M. (2021). A production and distribution planning of perishable products with a fixed lifetime under vertical competition in the seller-buyer systems: A real-world application. Journal of manufacturing systems, 58, 223-247.
Abraham, A.J., Kumar, K.R., Sridharan, R. & Singh, D. (2015). A genetic algorithm approach for integrated production and distribution problem. Procedia-Social and Behavioral Sciences 189, 184-192.
Adida, E.& DeMiguel, V. (2011). Supply chain competition with multiple manufacturers and retailers. Operational Research 59(1), 156-172.
Badhotiya, G., Kumar, G., Soni, G. & Mittal, M.L. (2019). Fuzzy multi-objective optimization for multi-site integrated production and distribution planning in two echelon supply chain.  International Journal of Advanced Manufacturing Technology. 102,635-645.
Bandyopadhyay, S.& Bhattacharya, R. (2013). Solving multi-objective parallel machine scheduling problem by a modified NSGA-II. Applied Mathematical Modelling 37, 6718-6729.
Bo, V., Bortolini, M., Malaguti, E., Monaci, M., Mora, C. & Paronuzzi, P. (2021). Models and algorithms for integrated production and distribution problems. Comput Ind Eng 154, 107003.
Carr, S. & Duenyas ,L. (2000). Optimal admission control and sequencing in a make-to-stock/make-to-order production system. Oper Res. 48, 709-720.
Chang, K.H. & Lu, Y. (2010). Queueing analysis on a single-station make-to-stock/make-to-order inventory-production system. Appl Math Modell. 34, 978-991.
Chen, G. Q., Wu, X. D., Guo, J., Meng, J., & Li, C. (2019). Global overview for energy use of the world economy: Household-consumption-based accounting based on the world input-output database (WIOD). Energy Economics, 81, 835-847.
Chen, J., Zhang, H. & Sun, Y. (2012). Implementing coordination contracts in a manufacturer Stackelberg dual-channel supply chain. Omega. 40, 571-583.
Chiang, W.C., Russell, R., Xu. X. & Zepeda, D. (2009). A simulation/metaheuristic approach to newspaper production and distribution supply chain problems. Int J Prod Econ.121, 752-767.
Deb, K., Pratap, A., Agarwal, S. & Meyarivan, T.A.M.T. (2002). A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans Evol Comput. 6, 182-197.
Fatemi Ghomi, S. M.T., Karimi, B., Behnamian, J.& Firoozbakht, J. (2021). A multi-objective particle swarm optimization based on pareto archive for integrated production and distribution planning in A Green supply chain. Appl Artif Intell. 35,133-153.
Feng, X., Chu, F., Chu, Ch.& Huang, Y. (2021). Crowdsource-enabled integrated production and transportation scheduling for smart city logistics. Int J Prod Res. 59,2157-2176.
Gao, J., Xiao, Z.& Wei, H. (2021). Competition and coordination in a dual-channel green supply chain with an eco-label policy. Comput Ind Eng. 153, 107057.
Gharaei, A., & Jolai, F. (2021). An ERNSGA‐III algorithm for the production and distribution planning problem in the multiagent supply chain. International Transactions in Operational Research, 28(4), 2139-2168.
Ghasemkhani, A., Tavakkoli-Moghaddam, R., Rahimi, Y., Shahnejat-Bushehri, S. & Tavakkoli-Moghaddam, H. (2021). Integrated production-inventory-routing problem for multi-perishable products under uncertainty by meta-heuristic algorithms. Int J Prod Res. 1-21.
Gholamian, M.R. & Zamani Bajegani, H. (2019). An inventory control model for obsolete items with consideration of all unit quantity discount and price-dependent on order quantity. Modern Research in Decision Making. 4(4), 127-146.
Goodarzian, F. & Hosseini-Nasab, H. (2019). Applying a fuzzy multi-objective model for a production–distribution network design problem by using a novel self-adoptive evolutionary algorithm. Int J Syst Sci: Oper Logist. 8, 1-22.
Gunnarsson, H., Rönnqvist, M. & Carlsson, D. (2007). Integrated production and distribution planning for Södra Cell AB. Journal of Mathematical Modelling and Algorithms. 6, 25-45.
Gupta, D.& Benjaafar, S. (2004). Make-to-order, make-to-stock, or delay product differentiation? A common framework for modeling and analysis. IIE Trans. 36,529-546. 
Heiko, A. & Darkow, I.L. (2016). Energy-constrained and low-carbon scenarios for the transportation and logistics industry. The International Journal of Logistics Management.
Hickman, J., Hassel, D., Joumard, R., Samaras, Z.& Sorenson, S. (1999). Methodology for calculating transport emissions and energy consumption.
Jallad, J., Mekhilef, S., Mokhlis, H., Laghari, J. & Badran, O. (2018). Application of hybrid meta-heuristic Techniques for optimal load shedding planning and operation in an islanded distribution network integrated with distributed generation. Energies. 11, 1134.
Jiang, J. & Rim, S.Ch.(2017). Strategic wip inventory positioning for make-to-order production with stochastic processing times. Math Probl Eng.
Jolai, F., Razmi, J. & Rostami, N. (2011). A fuzzy goal programming and meta heuristic algorithms for solving integrated production: distribution planning problem. Central European Journal of Operations Research. 19(4), 547-569.
Kazemi, H., Mahdavi Mazdeh, M., Rostami, M. & Heydari, M. (2021). The integrated production-distribution scheduling in parallel machine environment by using improved genetic algorithms. J Ind Prod Eng. 38, 157-170.
Khademi, M. & Niazi, F. (2021). Addressing a sustainable production-distribution supply chain network design problem considering carbon emissions policies by a hybrid whale optimization algorithm. Journal of Research in Science, Engineering and Technology. 9, 45-77.
Khalifehzadeh, S., Seifbarghy, M. & Naderi, B. (2017). Solving a fuzzy multi objective model of a production–distribution system using meta-heuristic based approaches. Journal of Intelligent Manufacturing. 28, 95-109.
Khalili, S.M., Jolai, F. & Torabi, S.A. (2017). Integrated production–distribution planning in two-echelon systems: a resilience view. Int J Prod Res. 55, 1040-1064.
Kim, E. & Van Oyen, M.P. (2021). Joint admission, production sequencing, and production rate control for a two-class make-to-order manufacturing system. J Manuf Syst. 59, 413-425.
Li, X., Guo, Sh., Liu, Y., Du, B. & Wang, L. (2017). A production planning model for make-to-order foundry flow shop with capacity constraint. Math Probl Eng. 2017.
Manavizadeh, N., Vafaeenezhad, T.& Farrokhi-Asl, H. (2016). Using Meta-Heuristic Algorithms to Solve an Integrated Production Planning and Preventive Maintenance Model. Appl Math Eng Manage Technol. 4,63-75.
Manteghi, Y., Arkat, J., Mahmoodi, A., & Farvaresh, H. (2021). Competition and cooperation in the sustainable food supply chain with a focus on social issues. Journal of Cleaner Production, 285, 124872.
Mishra, P. & Talati, I.(2018). Quantity discount for integrated supply chain model with back order and controllable deterioration rate. Yugoslav Journal of Operations Research. 28, 355-369.
Moattar Husseini, Z., Karimi, B., Moattar Husseini, S.M. & ,NGhodsipour, S.H. (2015). Multi-objective integrated production distribution planning concerning manufacturing partners. Int J Computer Integr Manuf .28, 1313-1330.
Park*, Y.B. (2005). An integrated approach for production and distribution planning in supply chain management. Int J Prod Res. 43, 1205-1224.
Rad, R., Sadeghi, R. & Nahavandi, N. (2018). A novel multi-objective optimization model for integrated problem of green closed loop supply chain network design and quantity discount. J Cleaner Prod. 196, 1549-1565. 
Rafiei, H., Safaei, F.& Rabbani, M. (2018). Integrated production-distribution planning problem in a competition-based four-echelon supply chain. Comput Ind Eng. 119,85-99.
Rafiei, H, Safaei, F. & Rabbani, M. (2021). An elastic constraint method for a multi-objective production-distribution planning problem with competition. International Journal of Logistics Systems and Management. 39(2).
Rahimi, M., Ghezavati, V.& Asadi, F. (2019). A stochastic risk-averse sustainable supply chain network design problem with quantity discount considering multiple sources of uncertainty. Comput Ind Eng. 130, 430-449.
Sadjadi, S.J, Asadi, H., Sadeghian, R.& Sahebi, H. (2018). Retailer Stackelberg game in a supply chain with pricing and service decisions and simple price discount contract. PLoS One. 
Soman, Ch.A., Van Donk, D.P. & Gaalman, G. (2004). Combined make-to-order and make-to-stock in a food production system. Int J Prod Econ. 90( 2), 223-235.
Stecke ,K.E. & Zhao, X. (2007). Production and transportation integration for a make-to-order manufacturing company with a commit-to-delivery business mode. Manufacturing & Service Operations Management. 2: 206-224.
Taguchi, G. (1986) . Introduction to quality engineering: designing quality into products and processes. No. 658.562 T3.
Tang, S., Wang, W.& Zhou, G. (2020). Remanufacturing in a competitive market: A closed-loop supply chain in a Stackelberg game framework. Expert Syst Appl. 161, 113655.
Thammano, A.& Teekeng, W. (2015). A modified genetic algorithm with fuzzy roulette wheel selection for job-shop scheduling problems. Int J Gen Syst. 44, 499-518.
Van Roy, T.J. (1989). Multi-level production and distribution planning with transportation fleet optimization. Manage Sci. 35, 1443-1453.
Viana, M. S., Junior, M.O.& Contreras, R.C. (2020). A modified genetic algorithm with local search strategies and multi-crossover operator for job shop scheduling problem. Sensors. 20, 5440.
Vidyarthi, N., Elhedhli, S. & Jewkes, E. (2009). Response time reduction in make-to-order and assemble-to-order supply chain design. IIE Trans. 41, 448-466. 
WANG, S. (2017). A Manufacturer Stackelberg Game in Price Competition Supply Chain under a Fuzzy Decision Environment. Int J Appl Math. 47. 1.
Worapradya, K. & Thanakijkasem, P. (2014). Optimizing steel production schedules via a hierarchical genetic algorithm. S. Afr. J. Ind. Eng. 25, 209-221.
Yue, D. & You, F. (2014). Game-theoretic modeling and optimization of multi-echelon supply chain design and operation under Stackelberg game and market equilibrium. Computers & Chemical Engineering.71,347-361.