Optimization of a two-echelon supply chain with random demand and random defect rate under strict carbon cap policy

被引:2
作者
Ghosh, Arindam [1 ]
机构
[1] IFHE Deemed Univ, Dept Operat & IT, ICFAI Business Sch IBS, Hyderabad, India
关键词
Supply chain; Defective items; Strict carbon cap policy; Mixed-integer non-linear programming; UNCERTAIN DEMAND; CO2; EMISSIONS; MANAGEMENT; PERFORMANCE; IMPERFECT; FRAMEWORK; COORDINATION; BENCHMARKING; MODELS; IMPACT;
D O I
10.1108/BIJ-10-2020-0537
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Purpose The yield of defective items and emissions of greenhouse gases in supply chains are areas of concern. Organizations try to reduce the yield defective items and emissions. In this paper, a constrained optimization model is developed with consideration of the yield of defective items and strict carbon cap policy simultaneously and then optimized. Further, sensitivity analyses have been carried out to draw different managerial insights. Precisely, we have tried to address the following research questions: (1) how to optimize the cost for a two-echelon supply chain considering yield of defective items and strict carbon cap policy, (2) how the total expected cost and total expected emissions act with changing parameters. Design/methodology/approach The mathematical modeling approach has been adopted to develop a model and further optimized it with optimization software. Costs and emissions from different areas of a supply chain have been derived and then the total cost and total emissions have been formulated mathematically. One constrained mixed-integer nonlinear programming (MINLP) problem has been formulated and solved considering emissions-related, velocity and production related-constraints. Further, different sensitivity analyses have been derived to draw some managerial insights. Findings In this paper, many decision variables have been calculated with a set of basic values of other parameters. It has been found that both cost and emissions can be controlled by controlling different parameters. It has been also found that some parameters have very little or no influence either on cost or emissions. In most cases, originations may exhaust the given limit of carbon cap to optimize their costs. Originality/value In spite of my sincere efforts, no paper has been found that has considered the yield of defective items and strict carbon cap policy simultaneously. In this paper, it is assumed that both demand and defect rates are random in nature. The model, presented in this paper may give insights to develop different supply chain models with consideration of both defective items and strict carbon cap policy. Sensitivity analyses, drawn in this paper may give deep insights to managers and carbon regulatory bodies.
引用
收藏
页码:793 / 816
页数:24
相关论文
共 41 条
[1]   Controlling setup cost in (Q, r, L) inventory model with defective items [J].
Annadurai, K. ;
Uthayakumar, R. .
APPLIED MATHEMATICAL MODELLING, 2010, 34 (06) :1418-1427
[2]  
[Anonymous], 2018, The Paris Agreement
[3]   Carbon Footprint and the Management of Supply Chains: Insights From Simple Models [J].
Benjaafar, Saif ;
Li, Yanzhi ;
Daskin, Mark .
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2013, 10 (01) :99-116
[4]  
Bogaschewsky R., 1995, Naturliche umwelt und produktion
[5]   Modeling green supply chain coordination: current research and future prospects [J].
Chauhan, Chetna ;
Singh, Amol .
BENCHMARKING-AN INTERNATIONAL JOURNAL, 2018, 25 (09) :3767-3788
[6]   The carbon-constrained EOQ [J].
Chen, Xi ;
Benjaafar, Saif ;
Elomri, Adel .
OPERATIONS RESEARCH LETTERS, 2013, 41 (02) :172-179
[7]   Optimal vendor investment for reducing defect rate in a vendor-buyer integrated system with imperfect production process [J].
Dey, O. ;
Gini, B. C. .
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2014, 155 :222-228
[8]   Estimating the Marginal Abatement Cost Curve of CO2 Emissions in China: Provincial Panel Data Analysis [J].
Du, Limin ;
Hanley, Aoife ;
Wei, Chu .
ENERGY ECONOMICS, 2015, 48 :217-229
[9]   Loss-averse preferences in a two-echelon supply chain with yield risk and demand uncertainty [J].
Du, Shaofu ;
Zhu, Yujiao ;
Nie, Tengfei ;
Yu, Haisuo .
OPERATIONAL RESEARCH, 2018, 18 (02) :361-388
[10]  
Dubey R, 2017, BENCHMARKING, V24, P184, DOI 10.1108/BIJ-01-2016-0011