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A bi-level programming approach to joint network design and pricing problem in the municipal solid waste management system: A case study

机译:城市固体废物管理系统联合网络设计与定价问题的双级规划方法:案例研究

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摘要

The fast growth of urbanization and population has held to the increase of waste in cities and caused significant problems in urban management systems. In this study, the design of municipal solid waste management network as well as determination of outsourcing policies is studied from the viewpoint of an organization (e.g. municipality) which collects different types of wastes from all over the city and pays a certain amount of money in exchange. In case of outsourdng, auction will be held and the companies who their business is recycling and composting can participate in by bidding. This process results in the selection of a company or an insourcing alternative. The problem is modelled as a bi-level programming model, which in the first level, municipality decides as the leader on outsourcing, and if outsourcing is agreed upon, a company is selected. In the second level, bidders compete as followers in the auction for receiving more waste from the municipality and offer prices. An exact novel solution method is applied to convert the proposed bi-level programming model into a single-level one that can be solved by commercial solvers. To validate the proposed solution method the relevant results are compared with those obtained by Karush-Kuhn-Tucker (KKT) approach by using data extracted from a real case study. Numerical results show that the proposed method is able to decrease the complexity of the concerned problem and considerable saving in computational time.
机译:城市化和人口的快速增长使城市的废物增加,并对城市管理系统引起了重大问题。在本研究中,从组织(例如市政)的观点来看,研究了市政固体废物管理网络的设计以及外包政策的确定,该组织(例如市政)从城市各地收集不同类型的废物并支付一定数量的钱交换。如果是Outsourdng,将举行拍卖,并将其业务回收和堆肥的公司可以通过竞标参加。此过程导致公司或批准替代品的选择。该问题被建模为双级编程模型,在第一级,市政当局决定作为外包的领导者,如果达成外包,则选择了一家公司。在二级,投标人竞争追随者在拍卖中获得从市政市场获得更多浪费并提供价格。应用精确的新型解决方案方法以将所提出的双级编程模型转换为可以通过商业求解器解决的单级。为了验证所提出的解决方案方法,将相关结果与通过使用从真实案例研究中提取的数据提取的karush-kuhn-tucker(kkt)方法获得的相关结果。数值结果表明,该方法能够降低有关问题的复杂性,并在计算时间中显着节省。

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