Komilis D P
Laboratory of Solid and Hazardous Waste Management, Department of Environmental Engineering, School of Engineering, Democritus University of Thrace, Xanthi 671 00, Greece.
Waste Manag. 2008 Nov;28(11):2355-65. doi: 10.1016/j.wasman.2007.11.004. Epub 2008 Jan 14.
Two conceptual mixed integer linear optimization models were developed to optimize the haul and transfer of municipal solid waste (MSW) prior to landfilling. One model is based on minimizing time (h/d), whilst the second model is based on minimizing total cost (euro/d). Both models aim to calculate the optimum pathway to haul MSW from source nodes (waste production nodes, such as urban centers or municipalities) to sink nodes (landfills) via intermediate nodes (waste transfer stations). The models are applicable provided that the locations of the source, intermediate and sink nodes are fixed. The basic input data are distances among nodes, average vehicle speeds, haul cost coefficients (in euro/ton km), equipment and facilities' operating and investment cost, labor cost and tipping fees. The time based optimization model is easier to develop, since it is based on readily available data (distances among nodes). It can be used in cases in which no transfer stations are included in the system. The cost optimization model is more reliable compared to the time model provided that accurate cost data are available. The cost optimization model can be a useful tool to optimally allocate waste transfer stations in a region and can aid a community to investigate the threshold distance to a landfill above which the construction of a transfer station becomes financially beneficial. A sensitivity analysis reveals that queue times at the landfill or at the waste transfer station are key input variables. In addition, the waste transfer station ownership and the initial cost data affect the optimum path. A case study at the Municipality of Athens is used to illustrate the presented models.
开发了两个概念性混合整数线性优化模型,以优化城市固体废物(MSW)在填埋前的运输和转运。一个模型基于最小化时间(小时/天),而第二个模型基于最小化总成本(欧元/天)。两个模型的目的都是计算将城市固体废物从源节点(废物产生节点,如城市中心或市镇)通过中间节点(废物转运站)运输到汇节点(填埋场)的最佳路径。只要源节点、中间节点和汇节点的位置固定,这些模型就适用。基本输入数据包括节点之间的距离、平均车速、运输成本系数(欧元/吨公里)、设备和设施的运营及投资成本、劳动力成本和倾倒费。基于时间的优化模型更容易开发,因为它基于现成的数据(节点之间的距离)。它可用于系统中不包括转运站的情况。如果有准确的成本数据,成本优化模型比时间模型更可靠。成本优化模型可以是在一个地区优化分配废物转运站的有用工具,并且可以帮助社区研究到填埋场的阈值距离,超过该距离建设转运站在经济上变得有利可图。敏感性分析表明,在填埋场或废物转运站的排队时间是关键输入变量。此外,废物转运站的所有权和初始成本数据会影响最佳路径。雅典市的一个案例研究用于说明所提出的模型。