Exploring alternative solid waste management strategies for achieving policy goals

The authors previously analysed a real-world solid waste management (SWM) system using the solid waste optimization life-cycle framework (SWOLF) to identify optimal SWM strategies that meet modelled objectives (<i>e.g.</i> cost, environmental impacts, landfill diversion). While mathematically optimal strategies can support SWM decision making, they may not be readily implementable because of unmodelled objectives (<i>e.g.</i> practical limitations, social preferences, political and management considerations). A mathematical programming technique extending SWOLF is used to systematically identify, for several scenarios, different ‘optimal’ SWM strategies that are maximally different from each other in terms of waste flows, while meeting modelled objectives and constraints. The performance with respect to unmodelled issues was analysed to demonstrate the flexibility in potential strategies. Practitioner feedback highlighted implementation challenges due to existing practices; however, insights gained from this exercise led to more plausible and acceptable strategies by incrementally modifying the initial SWM alternatives generated.

作者团队此前已借助固体废物优化生命周期框架（solid waste optimization life-cycle framework, SWOLF），针对真实世界的固体废物管理（solid waste management, SWM）系统开展分析，旨在识别符合建模目标的最优固体废物管理策略，涵盖成本、环境影响、填埋分流等维度。尽管数学层面的最优策略可为固体废物管理决策提供有力支撑，但由于存在未被纳入建模范畴的目标（如实际操作限制、社会偏好、政治与管理考量等），此类策略往往难以直接落地实施。本研究采用一种拓展了SWOLF框架的数学规划方法，针对多类场景系统识别出多套不同的“最优”固体废物管理策略——这些策略在废物流动维度上彼此差异最大化，同时严格满足预设的建模目标与约束条件。研究团队针对未建模问题的策略表现开展分析，以此展现潜在方案的灵活性空间。从业者反馈指出，现有运营模式带来了诸多实施难题；不过，通过逐步修正初始生成的固体废物管理备选方案，本次研究所得的分析结果催生了更具可行性与社会认可度的优化策略。