CONTEXT

Agricultural crop and livestock production systems are complex, essential to human well-being, and fraught with sustainability challenges. In light of intrinsic variability in agricultural production systems and the high number of decision variables, decision support for optimization of sustainability outcomes should be supported by rigorous operations research.

OBJECTIVE

Several operations research (OR) methods such as evolutionary algorithms, multi-objective optimization, and data envelopment analysis (DEA) have been applied to optimization in agricultural contexts, taking into account different objective functions and decision variables, and life cycle-based evaluation of environmental outcomes in agriculture have become widespread. The current review evaluates the methods used for optimization of agricultural and livestock systems for life cycle-based environmental sustainability goals.

METHODS

A Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) systematic review method and three complementary search strategies were used to identify relevant articles. Strengths, weaknesses, and performance issues for each method are considered and compared.

RESULTS AND CONCLUSIONS

Farm benchmarking, output prediction and resource use management are the three most commonly considered decision types in crop-livestock production systems. To guide selection and implementation of appropriate OR methods, a framework (decision tree) is proposed.

SIGNIFICANCE

The proposed decision tree provides an indication of necessary method-specific methodological choices. Methodological choices with respect to each method are discussed.

中文翻译：

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农畜生产系统环境评价的运筹学

语境

农业作物和畜牧生产系统复杂，对人类福祉至关重要，并且充满了可持续性挑战。鉴于农业生产系统的内在可变性和大量决策变量，优化可持续性结果的决策支持应得到严格的运筹学研究的支持。

客观的

进化算法、多目标优化和数据包络分析 (DEA) 等几种运筹学 (OR) 方法已应用于农业环境中的优化，考虑到不同的目标函数和决策变量，以及基于生命周期的评估农业中的环境成果已变得普遍。当前的审查评估了用于优化农业和畜牧系统以实现基于生命周期的环境可持续性目标的方法。

方法

系统评价和元分析的首选报告项目 (PRISMA) 系统评价方法和三种互补的搜索策略用于识别相关文章。考虑并比较每种方法的优点、缺点和性能问题。

结果和结论

农场基准、产量预测和资源使用管理是作物-畜牧生产系统中最常考虑的三种决策类型。为了指导选择和实施适当的 OR 方法，提出了一个框架（决策树）。

意义

建议的决策树提供了必要的特定于方法的方法选择的指示。讨论了每种方法的方法选择。