سامانه پشتیبانی خدمات اطلاعات

  اخبار و اعلانات

 آمار

تعداد نشریات162
تعداد شماره‌ها6,693
تعداد مقالات72,239
تعداد مشاهده مقاله129,232,845
تعداد دریافت فایل اصل مقاله102,066,983
Alidadi Talkhestani, Hamidreza, Haji Mohammad Ali Jahromi, meghdad, keshavarzfard, razieh. (1402). A Location-Inventory Model for Multi-Product Supply Chain with Perishable Products and Price-Dependent Demand. , 57(1), 1-20. doi: 10.22059/aie.2022.338983.1825
Hamidreza Alidadi Talkhestani; meghdad Haji Mohammad Ali Jahromi; razieh keshavarzfard. "A Location-Inventory Model for Multi-Product Supply Chain with Perishable Products and Price-Dependent Demand". , 57, 1, 1402, 1-20. doi: 10.22059/aie.2022.338983.1825
Alidadi Talkhestani, Hamidreza, Haji Mohammad Ali Jahromi, meghdad, keshavarzfard, razieh. (1402). 'A Location-Inventory Model for Multi-Product Supply Chain with Perishable Products and Price-Dependent Demand', , 57(1), pp. 1-20. doi: 10.22059/aie.2022.338983.1825
Alidadi Talkhestani, Hamidreza, Haji Mohammad Ali Jahromi, meghdad, keshavarzfard, razieh. A Location-Inventory Model for Multi-Product Supply Chain with Perishable Products and Price-Dependent Demand. , 1402; 57(1): 1-20. doi: 10.22059/aie.2022.338983.1825

A Location-Inventory Model for Multi-Product Supply Chain with Perishable Products and Price-Dependent Demand

Advances in Industrial Engineering
دوره 57، شماره 1، شهریور 2023، صفحه 1-20    اصل مقاله (465.55 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22059/aie.2022.338983.1825
نویسندگان
Hamidreza Alidadi Talkhestani1؛ meghdad Haji Mohammad Ali Jahromi* 1؛ razieh keshavarzfard2
1Department of Industrial Engineering, North Tehran Branch, Islamic Azad University, Tehran, Iran;
2Department of Industrial Engineering, North Tehran Branch, Islamic Azad University, Tehran, Iran
چکیده
One of the most challenging tasks in the perishable products industry is to control the inventory of products and find the optimum location to store them. This paper tries to respond to these challenges in a way that is close to reality. In this paper, a location-inventory model has been studied for a supply chain with perishable products, considering the dependence of demand to price. The investigated multi-product and multi-period supply chain includes manufacturers, distributors, retailers and customers. Products and centers of this chain are equipped with Radio Frequency Identification (RFID) technology. The location-inventory model, by simultaneously capturing strategic, tactical and operational decisions, can be very effective in increasing the supply chain efficiency. For this purpose, a mixed integer nonlinear programming model is presented. The purpose of the model is to maximize the profitability of the supply chain, which is achieved by the simultaneous decision-making of location, inventory, pricing and demand. Finally, in order to show the efficiency of the proposed model, numerous examples with various parameters are solved and sensitivity analysis is done. The results show that as the dependence of customer demands on price increases, it is inevitable that the supply chain sells the product to customers at a lower price and lower profit, and this causes an extreme decrease in supply chain profit. The lower dependence on the supply chain results in higher profit.
کلیدواژه‌ها
Supply Chain Management؛ Location-Inventory؛ Perishable Products؛ Dependence of Demand on Price
مراجع
  • [1] Stevens, G.C., Integrating the supply chain. international Journal of physical distribution & Materials Management, 1989. 19(8): p. 3-8.
  • [2] Gunasekaran, A., C. Patel, and E. Tirtiroglu, Performance measures and metrics in a supply chain environment. International journal of operations & production Management, 2001. 21(1/2): p. 71-87.
  • [3] Silver, E.A. and D.F. Pyke, R. Peterson. Inventory management and production planning and scheduling, 1998.
  • [4] Cavinato, J.L., A total cost/value model for supply chain competitiveness. Journal of business logistics, 1992. 13(2): p. 285.
  • [5] Diabat, A., J.-P. Richard, and C.W. Codrington, A Lagrangian relaxation approach to simultaneous strategic and tactical planning in supply chain design. Annals of Operations Research, 2013. 203(1): p. 55-80.
  • [6] Chopra, S. and P. Meindl, Supply chain management. Strategy, planning & operation, in Das summa summarum des management. 2007, Springer. p. 265-275.
  • [7] Diabat, A., E. Dehghani, and A. Jabbarzadeh, Incorporating location and inventory decisions into a supply chain design problem with uncertain demands and lead times. Journal of Manufacturing Systems, 2017. 43: p. 139-149.
  • [8] Amiri-Aref, M., W. Klibi, and M.Z. Babai, The multi-sourcing location inventory problem with stochastic demand. European Journal of Operational Research, 2018. 266(1): p. 72-87.
  • [9] Zheng, X., M. Yin, and Y. Zhang, Integrated optimization of location, inventory and routing in supply chain network design. Transportation Research Part B: Methodological, 2019. 121: p. 1-20.
  • [10] Mousavi, S.M., et al., Solving a continuous periodic review inventory-location allocation problem in vendor-buyer supply chain under uncertainty. Computers & Industrial Engineering, 2019. 128: p. 541-552.
  • [11] Rodrigues, F., et al., Comparing techniques for modelling uncertainty in a maritime inventory routing problem. European Journal of Operational Research, 2019. 277(3): p. 831-845.
  • [12] Saragih, N.I., N. Bahagia, and I. Syabri, A heuristic method for location-inventory-routing problem in a three-echelon supply chain system. Computers & Industrial Engineering, 2019. 127: p. 875-886.
  • [13] Gzara, F., E. Nematollahi, and A. Dasci, Linear location-inventory models for service parts logistics network design. Computers & Industrial Engineering, 2014. 69: p. 53-63.
  • [14] Daskin, M.S., C.R. Coullard, and Z.-J.M. Shen, An inventory-location model: Formulation, solution algorithm and computational results. Annals of operations research, 2002. 110(1-4): p. 83-106.
  • [15] Shen, Z.-J.M., C. Coullard, and M.S. Daskin, A joint location-inventory model. Transportation science, 2003. 37(1): p. 40-55.
  • [16] Ouyang, L.-Y., K.-S. Wu, and C.-T. Yang, A study on an inventory model for non-instantaneous deteriorating items with permissible delay in payments. Computers & Industrial Engineering, 2006. 51(4): p. 637-651.
  • [17] Miranda, P.A. and R.A. Garrido, A simultaneous inventory control and facility location model with stochastic capacity constraints. Networks and Spatial Economics, 2006. 6(1): p. 39-53.
  • [18] Atamtürk, A., G. Berenguer, and Z.-J. Shen, A conic integer programming approach to stochastic joint location-inventory problems. Operations Research, 2012. 60(2): p. 366-381.
  • [19] Vidyarthi, N., et al., Integrated production-inventory-distribution system design with risk pooling: model formulation and heuristic solution. Transportation Science, 2007. 41(3): p. 392-408.
  • [20] Park, S., T.-E. Lee, and C.S. Sung, A three-level supply chain network design model with risk-pooling and lead times. Transportation Research Part E: Logistics and Transportation Review, 2010. 46(5): p. 563-581.
  • [21] Shahabi, M., et al., A three level location-inventory problem with correlated demand. Transportation Research Part B: Methodological, 2014. 69: p. 1-18.
  • [22] Amorim, P., H.-O. Günther, and B. Almada-Lobo, Multi-objective integrated production and distribution planning of perishable products. International Journal of Production Economics, 2012. 138(1): p. 89-101.
  • [23] Piewthongngam, K., S. Pathumnakul, and S. Homkhampad, An interactive approach to optimize production–distribution planning for an integrated feed swinecompany. International Journal of Production Economics, 2013. 142(2): p. 290-301.
  • [24] Shahabi, M., et al., Integrated inventory control and facility location decisions in a multi-echelon supply chain network with hubs. Networks and Spatial Economics, 2013. 13(4): p. 497-514.
  • [25] Coelho, L.C. and G. Laporte, Optimal joint replenishment, delivery and inventory management policies for perishable products. Computers & Operations Research, 2014. 47: p. 42-52.
  • [26] Van Elzakker, M., et al., Optimizing the tactical planning in the Fast Moving Consumer Goods industry considering shelf-life restrictions. Computers & Chemical Engineering, 2014. 66: p. 98-109.
  • [27] Berman, O., D. Krass, and M.B. Menezes, Directed assignment vs. customer choice in location inventory models. International Journal of Production Economics, 2016. 179: p. 179-191.
  • [28] Kaya, O. and B. Urek, A mixed integer nonlinear programming model and heuristic solutions for location, inventory and pricing decisions in a closed loop supply chain. Computers & Operations Research, 2016. 65: p. 93-103.
  • [29] Hiassat, A., A. Diabat, and I. Rahwan, A genetic algorithm approach for location-inventory-routing problem with perishable products. Journal of manufacturing systems, 2017. 42: p. 93-103.
  • [30] Soto-Silva, W.E., et al., Optimizing fresh food logistics for processing: Application for a large Chilean apple supply chain. Computers and electronics in agriculture, 2017. 136: p. 42-57.
  • [31] Mohammed, A. and Q. Wang, The fuzzy multi-objective distribution planner for a green meat supply chain. International Journal of Production Economics, 2017. 184: p. 47-58.
  • [32] Savadkoohi, E., M. Mousazadeh, and S.A. Torabi, A possibilistic location-inventory model for multi-period perishable pharmaceutical supply chain network design. Chemical Engineering Research and Design, 2018. 138: p. 490-505.
  • [33] Dai, Z., et al., A location-inventory supply chain network model using two heuristic algorithms for perishable products with fuzzy constraints. Computers & Industrial Engineering, 2018. 119: p. 338-352.
  • [34] Yavari, M. and M. Geraeli, Heuristic method for robust optimization model for green closed-loop supply chain network design of perishable goods. Journal of Cleaner Production, 2019. 226: p. 282-305.
  • [35] Rohmer, S., G. Claassen, and G. Laporte, A two-echelon inventory routing problem for perishable products. Computers & Operations Research, 2019. 107: p. 156-172.
  • [36] Aghsami A, Samimi Y, Aghaei A. An Integrated Markovian Queueing-Inventory Model in a Single Retailer-Single Supplier Problem with Imperfect Quality and Destructive Testing Acceptance Sampling. Advances in Industrial Engineering. 2021 Oct 1;55(4):367-401.
  • [37] Kaya B, Dural D, Sağer M, Akdoğan M, İldeşler AB, Paldrak M, Ekren BY. Optimal Inventory Share Policy Search for e-Grocery Food Supply Network. InDigitizing Production Systems 2022 (pp. 735-746). Springer, Cham.
  • [38] Taleizadeh AA, Aliabadi L, Thaichon P. A sustainable inventory system with price-sensitive demand and carbon emissions under partial trade credit and partial backordering. Operational Research. 2022 Jan 16:1-46.
  • [39] Soleymanfar VR, Makui A, Taleizadeh AA, Tavakkoli-Moghaddam R. Sustainable EOQ and EPQ models for a two-echelon multi-product supply chain with return policy. Environment, Development and Sustainability. 2022 Apr;24(4):5317-43.
  • [40] Arabi M, Gholamian MR. Sustainable Supply Chain Network Design with Price-Based Demand Considering Sound and Dust Pollutions: A Case Study. Advances in Industrial Engineering. Summer 2021, 55(3): 285-306.
  • [41] Zafari F, Shishebori D. Designing a Multi-Objective Three-Stage Location-Routing Model for Humanitarian Logistic Planning under Uncertainty. Advances in Industrial Engineering. Autumn 2019, 53(4): 149-167.
  • [42] Bakhtiaria M, Ebrahimnejadb S, Yavari-Moghaddamb M. A Mathematical Model for Solving Location-Routing Problem with Simultaneous Pickup and Delivery Using a Robust Optimization Approach. Advances in Industrial Engineering, Autumn 2019, 53(4): 185-208.
  • [43] Vidal, C.J. and M. Goetschalckx, A global supply chain model with transfer pricing and transportation cost allocation. European Journal of Operational Research, 2001. 129(1): p. 134-158.
آمار
تعداد مشاهده مقاله: 348
تعداد دریافت فایل اصل مقاله: 634





سامانه مدیریت نشریات علمی. قدرت گرفته از سیناوب