解决垃圾桶位置问题与不确定的废物产生率:一个双目标强大的优化方法
1Department of Engineering, INMABB, Universidad Nacional del Sur (UNS)-CONICET, Bahía Blanca, Argentina.
概括
本研究引入了一个强大的优化模型,用于设计城市固体废物 (MSW) 收集网络. 该模型有效地将成本和收集频率降至最低,尽管存在废物产生不确定性,但提高了城市可持续性.
科学领域:
- 运营研究 运营研究
- 环境工程 环境工程
- 城市规划 城市规划
背景情况:
- 高效的城市固体废物 (MSW) 系统对于城市的可持续性和宜居性至关重要.
- 规划MSW系统面临挑战,原因是关键参数的不确定性,如废物产生率.
- 一个MSW系统中的初始接触点,收集点,需要精心设计网络.
研究的目的:
- 开发一个强大的优化模型来设计城市固体废物 (MSW) 收集点网络.
- 同时最大限度地降低网络成本和废物收集频率.
- 为改善MSW系统规划,解决废物产生率的不确定性.
主要方法:
- 为MSW收集点网络设计开发了一个强大的优化模型.
- 该模型包含一个双目标功能,以平衡网络成本和收集频率.
- 解决方案与确定性模型进行了比较,使用现实的场景和不同的废物产生率.
主要成果:
- 强大的优化模型在各种场景中提供了与决定性方法相比具有竞争力的解决方案.
- 该模型成功地将收集点网络成本和所需的收集频率降到最低.
- 开发的模型允许探索成本最小化和收集频率之间的权衡.
结论:
- 强大的优化对于在不确定性下设计MSW收集网络是有效的.
- 该模型增强了可持续和宜居的城市环境的规划.
- 决策者可以利用这个模型来优化MSW收集基础设施和运营.
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