As a critical component of sustainable development, a transportation system should be designed such that it has a positive impact on the economic, environmental, and social sustainability of the served region. In response, this study introduces the concept of passenger dissatisfaction with additional walking and waiting as an indicator of social sustainability and uses the concept while optimizing the transit network for economic, environmental, and social perfectives. Due to a lack of knowledge about the actual value of different passenger dissatisfaction levels and uncertainty in demand, a multi-objective robust possibilistic programming approach (RPP^⁎) is proposed and solved by using an interactive fuzzy programming approach. Different from other robust possibilistic approaches, RPP^⁎ optimizes not only the mean of the objective function and chance constraint violations but also the risk value inherited by uncertain parameters through considering the absolute deviation of the objective function. Both the advantage of RPP^⁎ versus the deterministic model and its superiority against several robust possibilistic approaches are demonstrated in the numerical studies. Furthermore, the outcomes of the numerical study demonstrate that the transportation network should be designed in a decentralized way as the risk coefficients, i.e., risk-taking attitude, increase.

作为可持续发展的重要组成部分，运输系统的设计应使其对服务区域的经济、环境和社会可持续性产生积极影响。作为回应，本研究引入了乘客对额外步行和等待的不满的概念，作为社会可持续性的一个指标，并在优化交通网络以实现经济、环境和社会完美的同时使用该概念。由于缺乏对不同乘客不满水平的实际价值和需求不确定性的了解，提出了一种多目标鲁棒可能性规划方法（RPP ^⁎），并通过使用交互式模糊规划方法进行求解。与其他稳健的可能性方法不同，RPP ^⁎通过考虑目标函数的绝对偏差，不仅优化了目标函数的均值和机会约束违规，还优化了不确定参数继承的风险值。数值研究证明了 RPP ^⁎相对于确定性模型的优势及其相对于几种强大的可能性方法的优势。此外，数值研究的结果表明，随着风险系数（即冒险态度）的增加，交通网络应该以分散的方式设计。