The use of renewable energies has become very attractive, because it protects the environment and boosts regional development. In this paper, a sustainable two-phase sequential approach is proposed for the design of bioenergy SCs under uncertainties. The first phase, integrating geographical information, social aspects, and multi-criteria decision-making techniques, helps find appropriate locations for the bio-refineries. High rates of unemployment, and high vulnerability to the variation in the markets in an economic crisis are considered as social concerns. Integrating these factors filters the areas for the second phase. The first phase reduces complexity in the computation of the problem, and helps set up sustainable development in the supply chain. In the second phase, to cope with the uncertainties in the bioenergy supply network, a robust model is introduced. It reduces the sensitivity to inaccurate input data, and the obtained solutions stay optimal when the parameters change slightly. In order to validate this two-phase sequential approach, a case study is investigated. The results of tests show that integrating the concepts of uncertainties and sustainability with geographical information of the area in a two-phase sequential approach outperforms the traditional models, and leads to the creation of 262 jobs. The jobs have a high impact on the surrounding area.

可再生能源的使用已经变得非常有吸引力，因为它可以保护环境并促进地区发展。本文提出了一种可持续的两阶段顺序方法，用于不确定性条件下的生物能源供应链设计。第一阶段整合了地理信息，社会方面和多准则决策技术，有助于为生物炼油厂找到合适的位置。高失业率和经济危机中对市场变化的高度脆弱性被认为是社会关注的问题。综合这些因素，可以过滤第二阶段的面积。第一阶段降低了问题计算的复杂性，并有助于建立供应链中的可持续发展。在第二阶段，为了应对生物能源供应网络中的不确定性，引入了鲁棒模型。它降低了对不准确输入数据的敏感度，并且当参数略有变化时，所获得的解决方案仍保持最佳状态。为了验证此两阶段顺序方法，研究了一个案例研究。测试结果表明，在两个阶段的顺序方法中，将不确定性和可持续性的概念与该地区的地理信息相结合的效果要优于传统模型，从而创造了262个工作岗位。这些工作对周围地区有很大影响。测试结果表明，在两个阶段的顺序方法中，将不确定性和可持续性的概念与该地区的地理信息相结合的效果要优于传统模型，从而创造了262个工作岗位。这些工作对周围地区有很大影响。测试结果表明，在两个阶段的顺序方法中，将不确定性和可持续性的概念与该地区的地理信息相结合的效果要优于传统模型，从而创造了262个工作岗位。这些工作对周围地区有很大影响。