The Design of a Sustainable Location-Routing-Inventory Model Considering Consumer Environmental Behavior
| Autor: | Jinhuan Tang, Liwen Jiang, Shoufeng Ji |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
Supply chain
Geography Planning and Development lcsh:TJ807-830 0211 other engineering and technologies lcsh:Renewable energy sources 02 engineering and technology 010501 environmental sciences Management Monitoring Policy and Law 01 natural sciences Willingness to pay Economics consumer environmental behaviors location-routing-inventory Sensitivity (control systems) Marketing lcsh:Environmental sciences 0105 earth and related environmental sciences Network model lcsh:GE1-350 021103 operations research Renewable Energy Sustainability and the Environment lcsh:Environmental effects of industries and plants Pareto principle Particle swarm optimization Environmental economics MOPSO lcsh:TD194-195 sustainable supply chain network Greenhouse gas Routing (electronic design automation) |
| Zdroj: | Sustainability, Vol 8, Iss 3, p 211 (2016) Sustainability; Volume 8; Issue 3; Pages: 211 |
| ISSN: | 2071-1050 |
| Popis: | Our aim is to design a sustainable supply chain (SSC) network, which takes into consideration consumer environmental behaviors (CEBs). CEBs not only affect consumers’ demand for products with low carbon emissions, they also affect their willingness to pay premium prices for products with low carbon emissions. We incorporate CEBs into the SSC network model involving location, routing and inventory. Firstly, a multi-objective optimization model comprised of both the costs and the carbon emissions of a joint location-routing-inventory model is proposed and solved, using a multi-objective particle swarm optimization (MOPSO) algorithm. Then, a revenue function including CEBs is presented on the basis of a Pareto set of the trade-off between costs and carbon emissions. A computational experiment and sensitivity analysis are conducted, employing data from the China National Petroleum Corporation (CNPC). The results clearly indicate that our research can be applied to actual supply chain operations. In addition, some practical managerial insights for enterprises are offered. |
| Databáze: | OpenAIRE |
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