供应链
生产(经济)
可持续发展
工作(物理)
债券
环境经济学
计算机科学
持续性
环境污染
清洁生产
业务
经济
城市固体废物
财务
环境科学
微观经济学
环境保护
废物管理
营销
机械工程
生态学
政治学
法学
生物
工程类
作者
Hanieh Heydari,Ata Allah Taleizadeh,Fariborz Jolai
标识
DOI:10.1016/j.engappai.2022.105583
摘要
One of the crises of human beings today is the lack of natural resources and the increase in the production of industrial waste due to overproduction. Also, the gradual warming of the earth has become one of the most important topics of discussion today. However, the trend of increasing unnecessary production, the volume of waste, and consequently environmental pollution and damage to plants and animals is very significant. One solution to prevent this trend is to use a sustainable supply chain and encourage producers to participate in green projects. But the other important thing is that attention to the environment should not deprive decision-makers of increasing profits and returns. Therefore, it is necessary to decide on the selling price of products according to issues such as inflation, transportation costs, production costs, and other items. After entering the production field, producers may need an initial budget to continue their work. This initial budget can be repaid with green bonds. Accordingly, a sustainable supply chain is introduced in this research, and then a two-stage model is presented. In the first stage, the model calculates the optimal priced of items for the manufacturer and retailer. In the second stage, it finances the introduced sustainable supply chain using green bonds. The Benders decomposition and Meta Heuristic algorithms are used to solve the problem and several numerical examples and test problems are provided to show the applicability of the model. This study develops a new integrated model for pricing and financing a sustainable supply chain with the aim of reducing the costs of the manufacturer and due to the lack of an initial budget. The introduced model uses discounts to persuade the customers to buy again and recycle the products.
科研通智能强力驱动
Strongly Powered by AbleSci AI