Food waste is a problem for which solutions are recognised but not readily put into practice. What should be the primary objective, reducing or eliminating surplus food production, requires great change within social, cultural and economic structures. The secondary approach of redistributing surplus food to areas of deficit (in terms of socio-economic groups and/or geographic regions) involves a significant logistical burden, and suffers the same issues as with the elimination of waste. The least desirable, but perhaps most practicable approach, is the use of food waste as a feedstock for Anaerobic Digestion (AD). The strategic adoption of AD can therefore be seen as an important step towards mitigating food waste, but the implementation of efficient AD systems on a large (county/region) scale involves significant complexity. The optimal number, size and location of AD plants, and whether they are centralised versus decentralised, may be determined by considering factors such as supply and proximity to feedstock, transport links, emission hazards and social impact. Reaching balanced and objective decisions when faced with such disparate criteria is inevitably very difficult. To address this problem we prototype and evaluate a decision support tool for county-scale AD planning. Our approach is a hybridised Agent Based Model (ABM) with a Multi Objective Optimisation. We capture the spatio-temporal dependencies that exist in the water, energy and food systems associated with energy derived from food waste using Agent Based Modelling (ABM). The use of Interactive Multi Criteria Analysis as visual analytics offers a means to communicate the co-benefits and trade-offs that may emerge, as well as prioritise the AD strategies, based on the weighting of criteria. Specifically, the method supports exploration of the social, environmental and economic impact of different AD strategies and decisions, linked to current issues, namely AD scale and adoption. The results highlight a trade-off between transport costs and social acceptability for the AD centralised versus decentralised strategies. When low carbon options are weighted higher then slow, steady and aggressive decentralised strategies are the best strategic adoption of AD. Conversely, when Energy production is considered with a greater weighting, then aggressive scaling up in a centralised approach is best with slow and steady approaches being further from the ideal. The framework has demonstrated that it permits a space for dialogue and transparent prioritization of AD strategies based on WEF nexus impacts.

餐厨垃圾是一个公认的解决方案，但不易付诸实践。减少或消除剩余粮食生产的主要目标应该是社会，文化和经济结构发生重大变化。将剩余食物重新分配到赤字地区的第二种方法（就社会经济群体和/或地理区域而言）涉及大量的后勤负担，并且遭受与消除废物相同的问题。最不希望但也可能最可行的方法是将食物残渣用作厌氧消化（AD）的原料。因此，战略性地采用反倾销可以被认为是减轻食物浪费的重要一步，但是在大范围（县/地区）实施有效的反倾销系统会带来极大的复杂性。最佳数量 反渗透工厂的规模和位置，以及它们是集中式还是分散式，可以通过考虑以下因素来确定，例如原料的供应和接近程度，运输联系，排放危害和社会影响。当面对如此不同的标准时，要达成平衡而客观的决定是非常困难的。为了解决这个问题，我们为县级AD规划设计了原型并评估了决策支持工具。我们的方法是具有多目标优化的混合基于主体的模型（ABM）。我们使用基于代理的模型（ABM）捕获了与食物垃圾产生的能量相关的水，能源和食物系统中存在的时空依赖性。使用交互式多标准分析作为可视化分析提供了一种手段，可以交流可能出现的共同利益和取舍，以及根据标准权重确定广告投放策略的优先级。具体而言，该方法支持探索与当前问题（即广告规模和采用）相关的不同广告策略和决策对社会，环境和经济的影响。结果突出表明，AD集中式策略与分散式策略在运输成本和社会接受度之间进行了权衡。当低碳选择权的权重更高时，缓慢，稳定和积极的权力下放策略将是AD的最佳策略。相反，当能源生产被认为具有更大的权重时，在集中式方法中积极地扩大规模是最好的，而缓慢而稳定的方法离理想状态还远。