工业工程 ›› 2019, Vol. 22 ›› Issue (5): 82-93.doi: 10.3969/j.issn.1007-7375.2019.05.011

• 专题论述 • 上一篇    下一篇

不确定环境下建筑废弃物设施选址的多目标鲁棒优化问题

许妙1, 袁红平2   

  1. 1. 西南交通大学 经济管理学院, 四川 成都 610031;
    2. 广州大学 工商管理学院, 广东 广州 510006
  • 收稿日期:2018-12-08 出版日期:2019-10-31 发布日期:2019-10-29
  • 作者简介:许妙(1996-),女,四川省人,硕士研究生,主要研究方向为建筑废弃物管理
  • 基金资助:
    国家自然科学基金资助项目(71573216);四川省科技计划资助项目(2017ZR0150);四川循环经济研究中心重点资助项目(XHJJ-1807)

A Multi-objective Robust Optimization Model for Site-selection of Construction Waste Facilities under Uncertainty

XU Miao1, YUAN Hongping2   

  1. 1. School of Economics and Management, Southwest Jiaotong University, Chengdu 610031, China;
    2. School of Management, Guangzhou University, Guangzhou 510006, China
  • Received:2018-12-08 Online:2019-10-31 Published:2019-10-29

摘要: 如何在充分考虑外部环境不确定性(比如:废弃物产生量、资源化率、成本等)下综合控制成本、GHG排放与视觉污染等的最小化是实现建筑废弃物设施合理选址及废弃物分配的关键。首先引入传统确定性模型,在经济、环境、社会各视角下同时最小化成本、GHG排放以及视觉污染;然后考虑各不确定性参数在一有界闭空间内变化,构建了鲁棒相对模型;最后以北京市为算例确定最优的废弃物设施选址与分配。结果表明,随着参数不确定性水平的增大,总目标函数值呈逐步上升趋势;相较于确定性模型,构建的鲁棒模型所获得的解更加稳定,证明了鲁棒模型的有效性。

关键词: 建筑废弃物, 废弃物设施, 鲁棒优化, 选址, 分配

Abstract: How to minimize cost, GHG emission, and visual pollution under a set of external environmental uncertainties (such as the amount of waste generation, resource utilization rate, cost, etc.) is essential for the reasonable location and allocation of construction waste facilities (CWFs). Firstly, from economical, environmental and social perspectives, a traditional deterministic model is introduced to minimize cost, GHG emission and visual pollution when locating CWFs. Then, a robust counterpart is constructed based on the traditional deterministic model, and each of these uncertain parameters is assumed to vary in a specified closed bounded box. Finally, the existing CWFs in Beijing are chosen as the candidate points to determine the optimal location and allocation of CWFs in Beijing. The result shows that the total objective value grows up gradually with the increase of the uncertainty level of the parameters. Compared with the deterministic model, the solution obtained by the robust model is more stable and reliable, proving the effectiveness of the proposed model.

Key words: construction waste, waste facilities, robust optimization, location, allocation

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