| Title |
A mathematical programming based decision support system for waste to resource market trading |
| ID_Doc |
27041 |
| Authors |
Mah, AXY; Ng, TS; Wang, B; Tiong, YW; Lee, JTE; Wang, CH |
| Title |
A mathematical programming based decision support system for waste to resource market trading |
| Year |
2024 |
| Published |
|
| DOI |
10.1016/j.jclepro.2024.140569 |
| Abstract |
In a linear economy, consumers typically dispose end-of-life products which are eventually incinerated or landfilled. Digital platforms could unlock rich waste reutilization opportunities and economic benefits by connecting the waste producers with potential waste buyers in online marketplaces. While previous studies mostly focus on input-output matching, this study proposes a decision support system that can be incorporated to an online marketplace to optimize the waste trading based on economic considerations. Moreover, the decision support system could facilitate higher level decisions such as capacity planning and incentive design. Based on a case study on Singapore's organic waste streams, the waste trading platform presents economic benefits for agents that sell their waste. Additionally, enforcing waste reutilization targets would require relevant policy support in terms of incentives or levies, where the levies can be implemented as co-payment rate for the agents. For instance, results showed that when the food waste reutilization target is set as 6 t/d, increasing the copayment rate from 0 to 20% allows the waste trading network to be self-sustaining without external funding. Finally, sensitivity analyses show that collecting more waste records in the database helps in optimizing the investment decisions, preferably when the number of records exceeds 64. |
| Author Keywords |
Circular economy; Industrial symbiosis; Mathematical optimization; Waste to resource; Digital platform; Stochastic programming |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:001162337300001 |
| WoS Category |
Green & Sustainable Science & Technology; Engineering, Environmental; Environmental Sciences |
| Research Area |
Science & Technology - Other Topics; Engineering; Environmental Sciences & Ecology |
| PDF |
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