A carbon sensitive transport-based deteriorating supply chain model under type-2 fuzzy bi-matrix game

References

• Barman, H., Parvin, M., Roy, S. K., & Weber, G. W. (2021). Back-order inventory model with inflation in a cloudy fuzzy environment. Journal of Industrial and Management Optimization, 17(4), 1913–1941. doi:10.3934/jimo.2020052
   Web of Science ®Google Scholar
• Bhattacharya, P., Bhattacharya, K., De, S. K., Nayak, P. K., & Joardar, S. (2022). A fuzzy strategic game solution for a green supply chain model. Applied Intelligence, 52(15), 18061–18080. doi:10.1007/s10489-022-03447-x
   Web of Science ®Google Scholar
• Bhattacharya, K., & De, S. K. (2022). A pollution sensitive fuzzy EPQ model with endogenous reliability and product deterioration based on lock fuzzy game theoretic approach. Soft Computing. doi:10.1007/s00500-022-07485-y
   Web of Science ®Google Scholar
• Bouchery, Y., Ghaffari, A., Jemai, Z., & Tan, T. (2017). Impact of coordination on cost and carbon emission for a two-echelon serial economic order quantity problem. European Journal of Operational Research, 260(2), 520–533. doi:10.1016/j.ejor.2016.12.018
   Web of Science ®Google Scholar
• Castillo, O., & Melin, P. (2008). Intelligent systems with interval type-2 fuzzy logic. International Journal of Innovative Computing Information Control, 4(4), 771–783.
   Web of Science ®Google Scholar
• Costa, N., & Lourenco, J. (2024). Desirability-based post-hoc selection of pareto solutions. International Journal of Management Science & Engineering Management, 1–10. doi:10.1080/17509653.2023.2296876
   Google Scholar
• Daryanto, Y., Wee, H. M., & Widyadana, G. A. (2019). Low carbon supply chain coordination for imperfect quality deterioration items. Mathematics, 7(3), 469–477. doi:10.3390/math7030234
   Web of Science ®Google Scholar
• Dashtakian-Nasrabad, S., Esmaeili-Qeshlaqi, M., Alipour-Vaezi, M., Jolai, F., & Aghsami, A. (2024). A bi-objective optimization mathematical model integrated with bulk arrival Markovian queueing system and machine learning in publishing industries. International Journal of Management Science & Engineering Management, 1–18. doi:10.1080/17509653.2024.2326066
   Google Scholar
• Das, C. B., & Roy, S. K. (2010). Fuzzy based ga for entropy Bimatrix goal game. International Journal of Uncertainty, Fuzziness & Knowledge-Based Systems, 18(6), 779–799. doi:10.1142/S0218488510006799
   Web of Science ®Google Scholar
• De, S. K. (2018). Triangular dense fuzzy lock sets. Soft Computing, 22(21), 7243–7254. doi:10.1007/s00500-017-2726-0
   Web of Science ®Google Scholar
• De, S. K., & Beg, I. (2016). Triangular dense fuzzy sets and new defuzzication methods. Journal of Intelligent and Fuzzy System, 31(1), 469–477. doi:10.3233/IFS-162160
   Web of Science ®Google Scholar
• De, S. K., Bhattacharya, K., Bhattacharya, P., Nayak, P. K., & Joardar, S. (2022). Solution of a pollution sensitive supply chain model for novel strategic fuzzy game via Bernoulli Trial. Computers & Operations Research, 144(8), 105846. doi:10.1016/j.cor.2022.105846
   Google Scholar
• De, S. K., Kundu, P. K., & Goswami, A. (2003). An economic production quantity inventory modelling involving fuzzy demand rate and fuzzy deterioration rate. Journal of Applied Mathematics and Computing, 12(1–2), 251–260. doi:10.1007/BF02936197
   Google Scholar
• De, S. K., & Mahata, G. C. (2016). Decision of a fuzzy inventory with fuzzy backorder model under cloudy fuzzy demand rate. International Journal of Applied and Computational Mathematics. doi:10.1007/5.4089-016-0285-4
   Google Scholar
• De, S. K., & Mahata, G. C. (2019a). A cloudy fuzzy economic order quantity model for imperfect quality items with allowable proportionate discounts. Journal of Industrial Engineering International, 15(4), 571–583. doi:10.1007/s40092-019-0310-1
   Google Scholar
• De, S. K., & Mahata, G. C. (2019b). An EPQ model for three-layer supply chain with partial backordering and disruption: Triangular dense fuzzy lock set approach. Sādhanā, 44(8). doi:10.1007/s12046-019-1160-7
   Web of Science ®Google Scholar
• De, S. K., & Mahata, G. C. (2019c). A production inventory supply chain model with partial backordering and disruption under triangular linguistic dense fuzzy lock set approach. Soft Computing, 24(7), 5053–5069. doi:10.1007/s00500-019-04254-2
   Web of Science ®Google Scholar
• De, S. K., & Mahata, G. C. (2021). Solution of an imperfect‐quality EOQ model with backorder under fuzzy lock leadership game approach. International Journal of Intelligent Systems, 36(1), 421–446. doi:10.1002/int.22305
   Web of Science ®Google Scholar
• De, S. K., Mahata, G. C., & Maity, S. (2021). Carbon emission sensitive deteriorating inventory model with trade credit under volumetric fuzzy systems. International Journal of Intelligent Systems, 36(12), 7563–7590. doi:10.1002/int.22599
   Web of Science ®Google Scholar
• De, S. K., Roy, B., & Bhattacharya, K. (2021). Solving an EPQ model with doubt fuzzy set: A robust intelligent decision-making approach. Knowledge-Based Systems, 235, 107666. doi:10.1016/j.knosys.2021.107666
   Web of Science ®Google Scholar
• Gao, J. (2013). Uncertain bimatrix game with applications. Fuzzy Optimization and Decision Making, 12(1), 65–78. doi:10.1007/s10700-012-9145-6
   Web of Science ®Google Scholar
• Huanga, Y. S., Fang, C. C., & Lin, Y. A. (2020). Inventory management in supply chains with consideration of logistics, green investment and different carbon emission policies. Computer and Industrial Engineering, 139, 106–207. doi:10.1016/j.cie.2019.106207
   Web of Science ®Google Scholar
• Jauhari, W. A. (2022). Sustainable inventory management for a closed-loop supply chain with energy usage, imperfect production, and green investment. Cleaner Logistics and Supply Chain, 4, 100055. doi:10.1016/j.clscn.2022.100055
   Google Scholar
• Jauhari, W. A., Pamuji, A. S., & Rosyidi, C. N. (2014). Cooperative inventory model for vendor-buyer system with unequal-sized shipment, defective items and carbon emission costs. International Journal of Logistics Systems & Management, 19(2), 163–186. doi:10.1504/IJLSM.2014.064657
   Google Scholar
• Jauhari, W. A., Pujawan, I., & Suef, M. (2023). Sustainable inventory management with hybrid production system and investment to reduce defects. Annals of Operations Research, 324(1–2), 543–572. doi:10.1007/s10479-022-04666-8
   Web of Science ®Google Scholar
• Jauhari, W. A., Pujawan, I. N., Suef, M., & Govindan, K. (2022). Low carbon inventory model for vendor‒buyer system with hybrid production and adjustable production rate under stochastic demand. Applied Mathematical Modelling, 108, 840–868. doi:10.1016/j.apm.2022.04.012
   Web of Science ®Google Scholar
• Jauhari, W. A., Ramadhany, S. C. N., Rosyidi, C. N., Mishra, U., & Hishamuddin, H. (2023). Pricing and green inventory decisions for a supply chain system with green investment and carbon tax regulation. Journal of Cleaner Production, 425, 138897. doi:10.1016/j.jclepro.2023.138897
   Web of Science ®Google Scholar
• Jauhari, W. A., & Wangsa, I. D. (2022). A manufacturer-retailer inventory model with remanufacturing, stochastic demand, and green investments. Process Integration & Optimization for Sustainability, 6(2), 253–273. doi:10.1007/s41660-021-00208-0
   Google Scholar
• Karmakar, S., De, S. K., Datta, T., & Goswami, A. (2020). An integrated production policy with defective items and stock-out based substitution under triangular dense fuzzy lock set environment. RAIRO - Operations Research, 55, S2727–S2746. doi:10.1051/ro/2020102
   Web of Science ®Google Scholar
• Karmakar, S., De, S. K., & Goswami, A. (2018). A pollution sensitive remanufacturing model with waste items: Triangular dense fuzzy lock set approach. Journal of Cleaner Production, 187, 789–803. doi:10.1016/j.jclepro.2018.03.161
   Web of Science ®Google Scholar
• Kicsiny, R., & Varga, Z. (2023). New algorithm for checking pareto optimality in bimatrix games. Annals of Operations Research, 320(1), 235–259. doi:10.1007/s10479-022-04912-z
   Web of Science ®Google Scholar
• Larbani, M. (2009). Solving bimatrix games with fuzzy payoffs by introducing nature as a third player. Fuzzy Sets and Systems, 160(5), 657–666. doi:10.1016/j.fss.2008.06.010
   Web of Science ®Google Scholar
• Lathamaheswari, M., Nagarajan, D., Kavikumar, J., & Broumi, S. (2020). Triangular interval type-2 fuzzy soft set and its application. Complex & Intelligent Systems, 6(3), 531–544. doi:10.1007/s40747-020-00151-6
   Web of Science ®Google Scholar
• Lathamaheswari, M., Nagarajan, D., Kavikumar, K., & Phang, C. (2018). A review on type-2 fuzzy controller on control system. Journal of Advanced Research in Dynamical and Control Systems, 10(11), 430–435.
   Google Scholar
• Lee, S., & Kim, D. (2014). An optimal policy for a single vendor single buyer integrated production distribution model with both deteriorating and defective items. International Journal of Production Economics, 147, 161–170. doi:10.1016/j.ijpe.2013.09.011
   Web of Science ®Google Scholar
• Li, D. F. (2012). A fast approach to compute fuzzy values of matrix games with payoffs of triangular fuzzy numbers. European Journal of Operational Research, 223(2), 421–429. doi:10.1016/j.ejor.2012.06.020
   Web of Science ®Google Scholar
• Mahata, P., De, S. K., & Mahata, G. C. (2021). Optimal ordering and screening policy for perishable items with imperfect quality. International Journal of Mathematics and Its Applications, 9(1), 51–61.
   Google Scholar
• Maity, S., De, S. K., & Mondal, S. P. (2019). A study of an EOQ model under lock fuzzy environment. Mathematics, 7(1), 75. doi:10.3390/math7010075
   Web of Science ®Google Scholar
• Mendel, J. M. (2009). Type-2 fuzzy sets and systems: How to learn about them. IEEE SMC eNewslett, 27, 1–8.
   Google Scholar
• Mendel, J. M., John, R. I., & Liu, F. (2006). Interval type-2 fuzzy logic systems made simple. IEEE Transactions on Fuzzy Systems, 14(6), 808–821. doi:10.1109/TFUZZ.2006.879986
   Web of Science ®Google Scholar
• Micheli Guido, J. L., & Mantella, F. (2018). Modelling an environmentally-extended inventory routing problem with demand uncertainty and a heterogeneous fleet under carbon control policies. International Journal of Production Economics, 204, 316–327. doi:10.1016/j.ijpe.2018.08.018
   Web of Science ®Google Scholar
• Nagarajan, D., Lathamaheswari, M., Broumi, S., & Kavikumar, J. (2019). A new perspective on traffic control management using triangular interval type-2 fuzzy sets and interval neutrosophic sets. Operations Research Perspectives, 6, 100099. doi:10.1016/j.orp.2019.100099
   Web of Science ®Google Scholar
• Nannar, S., Sindhuchao, S., Chaiyaphan, C., & Ransikarbum, K. (2024). Optimization of the sustainable food supply chain with integrative data envelopment analysis approach. International Journal of Management Science & Engineering Management, 1–16. doi:10.1080/17509653.2024.2317479
   Google Scholar
• Qin, J., & Liu, X. (2014). Frank aggregation operators for triangular interval type-2 fuzzy set and its application in multiple attribute group decision making. Journal of Applied Mathematics, 2014, 1–24. doi:10.1155/2014/923213
   Google Scholar
• Renna, P. (2023). Controllable processing times with limited resources and energy consumption in flow shops: An assessment by simulation. International Journal of Management Science & Engineering Management, 1–12. doi:10.1080/17509653.2023.2285774
   Google Scholar
• Roy, S. K. (2007). Fuzzy programming approach to two-person multicriteria bimatrix games. The Journal of Fuzzy Mathematics, 15(1), 141–153.
   Google Scholar
• Roy, S. K., & Maiti, S. K. (2020). Reduction methods of type-2 fuzzy variables and application to stackelberg game. Applied Intelligence, 50(5), 1398–1415. doi:10.1007/s10489-019-01578-2
   Web of Science ®Google Scholar
• Roy, S. K., & Mondal, S. K. (2016). An approach to solve fuzzy interval valued matrix game. International Journal of Operational Research, 23(6). doi:10.1504/IJOR2016.076880
   Google Scholar
• Shaerpour, M., Azani, M., Aghsami, A., & Rabbani, M. (2023). A new fuzzy bi-objective mixed-integer linear programming for designing a medical waste management network in the coronavirus epidemic: A case study. International Journal of Management Science and Engineering Management, 1–16. doi:10.1080/17509653.2023.2253775
   Web of Science ®Google Scholar
• Shi, X., Dong, C., Zhang, C., & Zhang, X. (2019). Who should invest in clean technologies in a supply chain with competition? Journal of Cleaner Production, 215, 689–700. doi:10.1016/j.jclepro.2019.01.072
   Web of Science ®Google Scholar
• Singla, N., Kaur, P., & Gupta, U. C. (2023). A new approach to solve intuitionistic fuzzy bi-matrix games involving multiple opinions. Iranian Journal of Fuzzy Systems, 20(1), 185–197.
   Web of Science ®Google Scholar
• Sola, H. B., Fernandez, J., Hagras, H., Herrera, F., Pagola, M., & Barrenechea, E. (2015). Interval type-2 fuzzy sets are generalization of interval valued fuzzy sets: Toward a wider view on their relationship. IEEE Transactions on Fuzzy Systems, 23(5), 1876–1882. doi:10.1109/TFUZZ.2014.2362149
   Web of Science ®Google Scholar
• Taleizadeh, A. A. (2014). An economic order quantity model for deteriorating items in a purchasing system with multiple prepayments. Applied Mathematical Modelling, 38(23), 5357–5366. doi:10.1016/j.apm.2014.02.014
   Web of Science ®Google Scholar
• Taleizadeh, A. A., Khanbaglo, M. P. S., & Barron, L. E. C. (2016). An EOQ inventory model with partial backordering and reparation of imperfect products. International Journal of Production Economics, 182, 418–434. doi:10.1016/j.ijpe.2016.09.013
   Web of Science ®Google Scholar
• Testa, F., Iraldo, F., & Frey, M. (2011). The effect of environmental regulation on firms competitive performance: The case of the building & construction sector in some EU regions. Journal of Environmental Management, 92(9), 2136–2144. doi:10.1016/j.jenvman.2011.03.039
   PubMed Web of Science ®Google Scholar
• Tiwari, S., Daryanto, Y., & Wee, H. M. (2018). Sustainable inventory management with deteriorating and imperfect quality items considering carbon emission. Journal of Cleaner Production, 192, 281–292. doi:10.1016/j.jclepro.2018.04.261
   Web of Science ®Google Scholar
• Wahab, M. I. M., Mamun, S. M. H., & Ongkunarak, P. (2011). EOQ models for a coordinated two-level international supply chain considering imperfect items and environmental impact. International Journal of Production Economics, 134(1), 151–158. doi:10.1016/j.ijpe.2011.06.008
   Web of Science ®Google Scholar
• Wangsa, I. D. (2017). Greenhouse gas penalty and incentive policies for a joint economic lot size model with industrial and transport emissions. International Journal of Industrial Engineering Computation, 8(1), 453–480. doi:10.5267/j.ijiec.2017.3.003
   Google Scholar
• Wangsa, I. D., Tiwari, S., Wee, H. M., & Reong, S. (2020). A sustainable vendor-buyer inventory system considering transportation, loading and unloading activities. Journal of Cleaner Production, 271, 122120. doi:10.1016/j.jclepro.2020.122120
   Web of Science ®Google Scholar
• Xu, Z., Elomri, A., Pokharel, S., & Mutlu, F. (2019). The design of green supply chains under carbon policies: A literature review of quantitative models. Sustainability, 11(11), 3094. doi:10.3390/su11113094
   Web of Science ®Google Scholar
• Yang, P. C., & Wee, H. M. (2000). Economic ordering policy of deteriorated item for vendor and buyer: An integrated approach. Production Planning & Control, 11(5), 474–480. doi:10.1080/09537280050051979
   Web of Science ®Google Scholar
• Zadeh, L. A. (1965). Fuzzy sets. Information Control, 8(3), 338–354. doi:10.1016/S0019-9958(65)90241-X
   Google Scholar
• Zarandi, M. H. F., Rezaee, B., Turksen, I. B., & Neshat, E. (2009). A type-2 rule-based expert system model for stock price analysis. Expert Systems with Applications, 36(1), 139–154. doi:10.1016/j.eswa.2007.09.034
   Web of Science ®Google Scholar
• Zhang, H., Li, L., Zhou, P., Hou, J., & Qio, Y. (2014). Subsidy modes waste cooking oil and biofuel: Policy effectiveness and sustainable supply chains in China. Energy Policy, 65(C), 270–274. doi:10.1016/j.enpol.2013.10.009
   Google Scholar