Research article Special Issues

A solution to the transportation hazard problem in a supply chain with an unreliable manufacturer

  • Received: 12 March 2022 Revised: 24 April 2022 Accepted: 27 May 2022 Published: 23 June 2022
  • The current study focuses on a two-echelon supply chain for a reliable retailer, an unreliable manufacturer, and selling price-dependent demand. Due to an unreliable manufacturer and transportation hazards, shortages arise, which negatively impact the reputation of the retailer. Moreover, customers are more conscious of the environment, as a result, most of the industry focuses on the production of green products. To reduce the holding cost of the retailer, a fuel consumption-based single-setup-multi-unequal-increasing-delivery policy was utilized in this current study. With this transportation policy, the number of shipments increases, which directly increases carbon emissions and transportation hazards. To protect the environment, the green level of the product is enhanced through some investments. The demand varies with the price of the product as well as with the level of the greenness of the product. Due to uncertain demand, the rate of the production is treated as controllable. A classical optimization technique and distribution-free approach have been utilized to obtain the optimum solution and the optimized system profit. To prove the applicability, the study is illustrated numerically and graphically via a well-explained analysis of sensitivity. The study proves that single-setup-multi-unequal-increasing delivery policy is $ 0.62 \% $ beneficial compared to single-setup-single-delivery policy and $ 0.35 \% $ better than the single-setup-multi-delivery policy.

    Citation: Soumya Kanti Hota, Santanu Kumar Ghosh, Biswajit Sarkar. A solution to the transportation hazard problem in a supply chain with an unreliable manufacturer[J]. AIMS Environmental Science, 2022, 9(3): 354-380. doi: 10.3934/environsci.2022023

    Related Papers:

  • The current study focuses on a two-echelon supply chain for a reliable retailer, an unreliable manufacturer, and selling price-dependent demand. Due to an unreliable manufacturer and transportation hazards, shortages arise, which negatively impact the reputation of the retailer. Moreover, customers are more conscious of the environment, as a result, most of the industry focuses on the production of green products. To reduce the holding cost of the retailer, a fuel consumption-based single-setup-multi-unequal-increasing-delivery policy was utilized in this current study. With this transportation policy, the number of shipments increases, which directly increases carbon emissions and transportation hazards. To protect the environment, the green level of the product is enhanced through some investments. The demand varies with the price of the product as well as with the level of the greenness of the product. Due to uncertain demand, the rate of the production is treated as controllable. A classical optimization technique and distribution-free approach have been utilized to obtain the optimum solution and the optimized system profit. To prove the applicability, the study is illustrated numerically and graphically via a well-explained analysis of sensitivity. The study proves that single-setup-multi-unequal-increasing delivery policy is $ 0.62 \% $ beneficial compared to single-setup-single-delivery policy and $ 0.35 \% $ better than the single-setup-multi-delivery policy.



    加载中


    [1] Goyal SK (1977) An integrated inventory model for a single supplier-single customer problem. The International Journal of Production Research 15: 107–111. https://doi.org/10.1080/00207547708943107 doi: 10.1080/00207547708943107
    [2] Garai A, Sarkar B (2022) Economically independent reverse logistics of customer-centric closed-loop supply chain for herbal medicines and biofuel. Journal of Cleaner Production 334: 129977. https://doi.org/10.1016/j.jclepro.2021.129977 doi: 10.1016/j.jclepro.2021.129977
    [3] Dey BK, Sarkar B, Sarkar M, et al. (2019) An integrated inventory model involving discrete setup cost reduction, variable safety factor, selling price dependent demand, and investment. RAIRO-Operations Research 53: 39–57. https://doi.org/10.1051/ro/2018009 doi: 10.1051/ro/2018009
    [4] Dey BK, Bhuniya S, Sarkar B (2021) Involvement of controllable lead time and variable demand for a smart manufacturing system under a supply chain management. Expert Systems with Applications 2021: 115464. https://doi.org/10.1016/j.eswa.2021.115464 doi: 10.1016/j.eswa.2021.115464
    [5] Hota SK, Sarkar B, Ghosh SK (2020) Effects of unequal lot size and variable transportation in unreliable supply chain management. Mathematics 8: 357. https://doi.org/10.3390/math8030357 doi: 10.3390/math8030357
    [6] Noh J, Kim JS, Sarkar B (2019) Two-echelon supply chain coordination with advertising-driven demand under Stackelberg game policy. European Journal of Industrial Engineering 13: 213–244. https://doi.org/10.1504/EJIE.2019.098516 doi: 10.1504/EJIE.2019.098516
    [7] Sana SS (2021) A structural mathematical model on two echelon supply chain system. Annals of Operations Research 2021: 1–29. https://doi.org/10.1007/s10479-020-03895-z doi: 10.1007/s10479-020-03895-z
    [8] Sarkar B, Omair M, Kim N (2020) A cooperative advertising collaboration policy in supply chain management under uncertain conditions. Applied Soft Computing 88: 105948. https://doi.org/10.1016/j.asoc.2019.105948 doi: 10.1016/j.asoc.2019.105948
    [9] Sardar SK, Sarkar B. (2020) How Does Advanced Technology Solve Unreliability Under Supply Chain Management Using Game Policy? Mathematics 8: 1191. https://doi.org/10.3390/math8071191 doi: 10.3390/math8071191
    [10] Guchhait R, Pareek S, Sarkar B (2019) How Does a Radio Frequency Identification Optimize the Profit in an Unreliable Supply Chain Management? Mathematics 7: 490. https://doi.org/10.3390/math7060490 doi: 10.3390/math7060490
    [11] Park K, Lee K (2016) Distribution-robust single-period inventory control problem with multiple unreliable suppliers. OR spectrum 38: 949–966. https://doi.org/10.1007/s00291-016-0440-4 doi: 10.1007/s00291-016-0440-4
    [12] Chen Y, Feng Q, Senior Member I, et al. (2021) Modeling and analyzing RFID Generation-2 under unreliable channels. Journal of Network and Computer Applications 178: 102937. https://doi.org/10.1016/j.jnca.2020.102937 doi: 10.1016/j.jnca.2020.102937
    [13] Entezaminia A, Gharbi A, Ouhimmou M (2021) A joint production and carbon trading policy for unreliable manufacturing systems under cap-and-trade regulation. Journal of Cleaner Production 293: 125973. https://doi.org/10.1016/j.jclepro.2021.125973 doi: 10.1016/j.jclepro.2021.125973
    [14] Hoque M (2020) A manufacturer-buyers integrated inventory model with various distributions of lead times of delivering equal-sized batches of a lot. Computers & Industrial Engineering 145: 106516. https://doi.org/10.1016/j.cie.2020.106516 doi: 10.1016/j.cie.2020.106516
    [15] Sarkar B, Saren S, Sinha D, et al. (2015) Effect of unequal lot sizes, variable setup cost, and carbon emission cost in a supply chain model. Mathematical Problems in Engineering 2015. https://doi.org/10.1155/2015/469486 doi: 10.1155/2015/469486
    [16] Tang S, Wang W, Cho S, et al. (2018) Reducing emissions in transportation and inventory management: (R, Q) Policy with considerations of carbon reduction European Journal of Operational Research 269: 327–340. https://doi.org/10.1016/j.ejor.2017.10.010
    [17] Sardar SK, Sarkar B, Kim B (2021) Integrating Machine Learning, Radio Frequency Identification, and Consignment Policy for Reducing Unreliability in Smart Supply Chain Management Processes 9: 247. https://doi.org/10.3390/pr9020247
    [18] Omair M, Noor S, Tayyab M, et al. (2021) The selection of the sustainable suppliers by the development of a decision support framework based on analytical hierarchical process and fuzzy inference system. International Journal of Fuzzy Systems 23: 1986–2003. https://doi.org/10.1007/s40815-021-01073-2 doi: 10.1007/s40815-021-01073-2
    [19] Ullah M, Asghar I, Zahid M, et al. (2021) Ramification of remanufacturing in a sustainable three-echelon closed-loop supply chain management for returnable products. Journal of Cleaner Production 290: 125609. https://doi.org/10.1016/j.jclepro.2020.125609 doi: 10.1016/j.jclepro.2020.125609
    [20] Tayyab M, Sarkar B (2021) An interactive fuzzy programming approach for a sustainable supplier selection under textile supply chain management. Computers & Industrial Engineering 155: 107164. https://doi.org/10.1016/j.cie.2021.107164 doi: 10.1016/j.cie.2021.107164
    [21] Ullah M, Sarkar B (2020) Recovery-channel selection in a hybrid manufacturing-remanufacturing production model with RFID and product quality. International Journal of Production Economics 219: 360–374. https://doi.org/10.1016/j.ijpe.2019.07.017 doi: 10.1016/j.ijpe.2019.07.017
    [22] Guo Z, Fang F, Whinston AB (2006) Supply chain information sharing in a macro prediction market. Decision Support Systems 42: 1944–1958. https://doi.org/10.1016/j.dss.2006.05.003 doi: 10.1016/j.dss.2006.05.003
    [23] Xiao T, Xu T (2013) Coordinating price and service level decisions for a supply chain with deteriorating item under vendor managed inventory. International Journal of Production Economics 145: 743–752. https://doi.org/10.1016/j.ijpe.2013.06.004 doi: 10.1016/j.ijpe.2013.06.004
    [24] Sarkar B (2012) An inventory model with reliability in an imperfect production process. Applied Mathematics and Computation 218: 4881–4891. https://doi.org/10.1016/j.amc.2011.10.053 doi: 10.1016/j.amc.2011.10.053
    [25] Cárdenas-Barrón LE, Sarkar B, Treviño-Garza G (2013) Easy and improved algorithms to joint determination of the replenishment lot size and number of shipments for an EPQ model with rework. Mathematical and Computational Applications 18: 132–138. https://doi.org/10.3390/mca18020132 doi: 10.3390/mca18020132
    [26] Dhahri A, Gharbi A, Ouhimmou M (2022) Integrated production-delivery control policy for an unreliable manufacturing system and multiple retailers. International Journal of Production Economics 245: 108383. https://doi.org/10.1016/j.ijpe.2021.108383 doi: 10.1016/j.ijpe.2021.108383
    [27] Sarkar B, Mridha B, Pareek S (2022) A sustainable smart multi-type biofuel manufacturing with the optimum energy utilization under flexible production. Journal of Cleaner Production 332: 129869. https://doi.org/10.1016/j.jclepro.2021.129869 doi: 10.1016/j.jclepro.2021.129869
    [28] Yadav D, Kumari R, Kumar N, et al. (2021) Reduction of waste and carbon emission through the selection of items with cross-price elasticity of demand to form a sustainable supply chain with preservation technology. Journal of Cleaner Production 297: 126298. https://doi.org/10.1016/j.jclepro.2021.126298 doi: 10.1016/j.jclepro.2021.126298
    [29] Sarkar B, Sarkar M, Ganguly B, et al. (2021) Combined effects of carbon emission and production quality improvement for fixed lifetime products in a sustainable supply chain management. International Journal of Production Economics 231: 107867. https://doi.org/10.1016/j.ijpe.2020.107867 doi: 10.1016/j.ijpe.2020.107867
    [30] Dey BK, Sarkar B, Pareek S (2019) A two-echelon supply chain management with setup time and cost reduction, quality improvement and variable production rate. Mathematics 7: 328. https://doi.org/10.3390/math7040328 doi: 10.3390/math7040328
    [31] Sana SS (2020) Price competition between green and non green products under corporate social responsible firm. Journal of Retailing and Consumer Services 55: 102118. https://doi.org/10.1016/j.jretconser.2020.102118 doi: 10.1016/j.jretconser.2020.102118
    [32] Chen TB, Chai LT (2010) Attitude towards the environment and green products: Consumers' perspective Management science and engineering 4: 27–39. //dx.doi.org/10.3968/j.mse.1913035X20100402.002
    [33] Habib MS, Asghar O, Hussain A, et al. (2021) A robust possibilistic programming approach toward animal fat-based biodiesel supply chain network design under uncertain environment. Journal of Cleaner Production 278: 122403. https://doi.org/10.1016/j.jclepro.2020.122403 doi: 10.1016/j.jclepro.2020.122403
    [34] Sepehri A, Mishra U, Tseng ML, et al. (2021) Joint pricing and inventory model for deteriorating items with maximum lifetime and controllable carbon emissions under permissible delay in payments Mathematics 9: 470. https://doi.org/10.3390/math9050470
    [35] Singh S, Yadav D, Sarkar B, et al. (2021) Impact of energy and carbon emission of a supply chain management with two-level trade-credit policy. Energies 14: 1569. https://doi.org/10.3390/en14061569 doi: 10.3390/en14061569
    [36] Boye JI, Arcand Y (2013) Current trends in green technologies in food production and processing Food Engineering Reviews 5: 1–17. https://doi.org/10.1007/s12393-012-9062-z
    [37] Tseng YJ, Lin SH (2014) Integrated evaluation of green design and green manufacturing processes using a mathematical model. International Journal of Mechanical and Mechatronics Engineering 8: 1205–1210. https://doi.org/10.5281/zenodo.1093574 doi: 10.5281/zenodo.1093574
    [38] Wymer W, Polonsky MJ (2015) The limitations and potentialities of green marketing. Journal of Nonprofit & Public Sector Marketing 27: 239–262. https://doi.org/10.1080/10495142.2015.1053341 doi: 10.1080/10495142.2015.1053341
    [39] Shu T, Liu Q, Chen S, et al. (2018) Pricing decisions of CSR closed-loop supply chains with carbon emission constraints. Sustainability 10: 4430. https://doi.org/10.3390/su10124430 doi: 10.3390/su10124430
    [40] Zhang L, Zhou H (2019) The optimal green product design with cost constraint and sustainable policies for the manufacturer. Mathematical Problems in Engineering 2019: 14. https://doi.org/10.1155/2019/7841097 doi: 10.1155/2019/7841097
    [41] Liu K, Li W, Jia F, et al. (2022) Optimal strategies of green product supply chains based on behaviour-based pricing. Journal of Cleaner Production 335: 130288. https://doi.org/10.1016/j.jclepro.2021.130288 doi: 10.1016/j.jclepro.2021.130288
    [42] Song H, Chu H, Yue H, et al. (2022) Green supply chain coordination with substitutable products under cost sharing contract. Procedia Computer Science 199: 1112–1119. https://doi.org/10.1016/j.procs.2022.01.141 doi: 10.1016/j.procs.2022.01.141
    [43] Mahapatra AS, Soni NH, Mahapatra MS, et al. (2021) A continuous review production-inventory system with a variable preparation time in a fuzzy random environment. Mathematics 9: 747. https://doi.org/10.3390/math9070747 doi: 10.3390/math9070747
    [44] Scarf H (1958) A min-max solution of an inventory problem. Studies in the mathematical theory of inventory and production, Santa Monica: Rand Corporation.
    [45] Sepehri A, Mishra U, Sarkar B (2021) A sustainable production-inventory model with imperfect quality under preservation technology and quality improvement investment. Journal of Cleaner Production 310 : 127332. https://doi.org/10.1016/j.jclepro.2021.127332 doi: 10.1016/j.jclepro.2021.127332
    [46] Bhuniya S, Pareek S, Sarkar B (2021) A supply chain model with service level constraints and strategies under uncertainty. Alexandria Engineering Journal 60: 6035–6052. https://doi.org/10.1016/j.aej.2021.03.039 doi: 10.1016/j.aej.2021.03.039
    [47] Kshetri N (1977) Blockchain and sustainable supply chain management in developing countries. International Journal of Information Management 60: 102376. https://doi.org/10.1016/j.ijinfomgt.2021.102376 doi: 10.1016/j.ijinfomgt.2021.102376
    [48] Centobelli P, Cerchione R, Del Vecchio P, Oropallo E, Secundo G (2021) Blockchain technology design in accounting: Game changer to tackle fraud or technological fairy tale? Accounting, Auditing & Accountability Journal. https://doi.org/10.1108/AAAJ-10-2020-4994 doi: 10.1108/AAAJ-10-2020-4994
    [49] Shen C, Pena-Mora F (2018) Blockchain for cities—a systematic literature review. Ieee Access 6 : 76787–76819.: https://doi.org/10.1109/ACCESS.2018.2880744 doi: 10.1109/ACCESS.2018.2880744}
  • Reader Comments
  • © 2022 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(1510) PDF downloads(82) Cited by(11)

Article outline

Figures and Tables

Figures(7)  /  Tables(6)

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog