顾客有限“碳行为”偏好对选址-路径-库存联合优化的影响

doi:10.16381/j.cnki.issn1003-207x.2016.07.013

中国管理科学 ›› 2016, Vol. 24 ›› Issue (7): 110-119.doi: 10.16381/j.cnki.issn1003-207x.2016.07.013

顾客有限“碳行为”偏好对选址-路径-库存联合优化的影响

唐金环, 戢守峰, 姜力文, 朱宝琳

东北大学工商管理学院, 辽宁沈阳 110819

收稿日期:2013-12-04 修回日期:2014-12-23 出版日期:2016-07-20 发布日期:2016-07-27
通讯作者: 戢守峰(1958-),男(汉族),辽宁沈阳人,东北大学工商管理学院教授,博士生导师,研究方向:物流系统建模与优化、物流与供应链管理,E-mail:sfji@mail.neu.edu.cn E-mail:sfji@mail.neu.edu.cn
基金资助:
国家自然科学基金资助项目（70872019，71572031）；辽宁省教育厅人文社科基地项目（ZJ2013014）

The Effect of Consumers Bounded “Carbon Behavior” Preference on Location-Routing-Inventory Optimization

TANG Jin-huan, JI Shou-feng, JIANG Li-wen, ZHU Bao-lin

School of Business Administration, Northeastern University, Shenyang 110819, China

Received:2013-12-04 Revised:2014-12-23 Online:2016-07-20 Published:2016-07-27

摘要/Abstract

摘要： 针对考虑顾客有限“碳行为”偏好的选址-路径-库存联合优化问题，引入环保度系数作为碳排放量的特征向量，在低碳产品加价率存在的情况下，刻画了顾客有限“碳行为”偏好和市场逆需求系数对低碳产品需求量的影响，构建了选址-路径-库存系统中考虑有“碳行为”偏好的联合优化模型，并分析了顾客行为偏好对企业收益的影响。使用基于NNC的多目标求解方法，对考虑成本和碳排放的双目标问题进行处理并得到一组Pareto解集，数值实验证明了产品环保度、顾客有限“碳行为”偏好对企业运作方案和收益水平的影响。

关键词: 有限"碳行为"偏好, 选址-路径-库存联合优化, 加价率, 环保度, Pareto解集

Abstract: The optimization of supply chain network considering both cost and emissions is a hot topic now. However, the traditional researches mostly focus on the trade-off among economic cost, customer service and others. In this paper, a supply chain network model considering the cost and emissions of location, routing and inventory is designed. Also, the consumer environmental behaviors (CEBs) are incorporated. CEBs not only affect consumers' willingness to pay premium prices for low carbon emission products, but also the overall demand for low carbon emission products. Specifically, it's assumed that the price premium for eco-friendly product is p_x=pθ_x². Where p is the price of the normal product, p_x is the price of the eco-friendly products, and θ_x is the green level coefficient of products. The demand function describes as d_x = d+τθ_x-λp_x. Where d_x is the demand of the eco-friendly products, d is the initial demand without considering CEBs or a premium for greener products, τ is the consumers' environmental preference for low carbon products, λ is the market inverse demand coefficient. The contributions of this research can be listed as follows. First, a multi-objective model is constructed, which provides a trade-off between costs and carbon emissions. The NNC method is used to solve the model, and then a Pareto optimal set can be obtained. After that, the revenue function based on the Pareto solutions is proposed. In the computational experiments, the model is tested by the data from the Northeast Chemical Sales Company of CNPC. The obtained Pareto optimal curve provides a portfolio of configurations for decision makers. Then, the same technique can be used to obtain the revenue curves from different carbon emissions. Hence, the unique optimal revenue levels and the relevant decisions can be acquired. Finally, the sensitivity of the case study was analyzed. We are interested in the effects of CEBs on the demand and revenue in a three-level supply chain. The results show that more positive CEBs result in greater demand and higher revenue. Also, it's observed that the pricing of low carbon operations is critical. Therefore, enterprises should make marketing efforts to strengthen consumers' environmental preferences. Companies should support their claims to consumers and ensure the degree of CEBs before implementing their carbon emission reduction policies.

Key words: bounded "carbon behaviors", preference, location-routing-inventory integration problem, degree of environment, price premium, Pareto solutions

中图分类号:

C931

唐金环, 戢守峰, 姜力文, 朱宝琳. 顾客有限“碳行为”偏好对选址-路径-库存联合优化的影响[J]. 中国管理科学, 2016, 24(7): 110-119.

TANG Jin-huan, JI Shou-feng, JIANG Li-wen, ZHU Bao-lin. The Effect of Consumers Bounded “Carbon Behavior” Preference on Location-Routing-Inventory Optimization[J]. Chinese Journal of Management Science, 2016, 24(7): 110-119.

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顾客有限“碳行为”偏好对选址-路径-库存联合优化的影响

The Effect of Consumers Bounded “Carbon Behavior” Preference on Location-Routing-Inventory Optimization

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