Currently, a huge amount of cargo is transported via containers by liner shipping companies. Under stochastic demand, repacking operations and carbon reduction, which may lead to an increase in effectiveness and environmental improvement, have been rarely considered in previous literature. In this paper, we investigate a container transshipment route scheduling problem with repacking operations under stochastic demand and environmental protection. The problem is a combinatorial optimization problem. Lacking historical data, a chance-constrained programming model is proposed to minimize the total operating and environment-related costs. We choose two distribution-free approaches, i.e., approximation based in Markov’s Inequality and Mixed Integer Second-Order Conic Program to approximate the chance constraints. As the loses induced by unfulfilled demand are not taken into account in the above model, a scenario-based model is developed considering the loses. Risk-neutral model may provide solutions that perform poorly while considering uncertainty. To incorporate decision makers’ perspectives, therefore, we also propose a risk-averse model adopting a risk aversion measure called Conditional Value-at-Risk to meet different preferences. Finally, we conduct computational experiments based on real data to compare the performances of the modeling methods and illustrate the impacts by testing different risk levels and confidence levels.

目前，班轮运输公司通过集装箱运输大量货物。在随机需求下，以前的文献很少考虑重新包装操作和减少碳排放，这可能导致效率提高和环境改善。在本文中，我们研究了在随机需求和环境保护下具有重新包装操作的集装箱转运路线调度问题。该问题是组合优化问题。缺乏历史数据，提出了机会受限的编程模型，以最大程度地降低总运营成本和与环境相关的成本。我们选择两种无分布方法，即基于马尔可夫不等式的近似和混合整数二阶圆锥程序，以近似机会约束。由于在上述模型中未考虑由未满足需求引起的损失，因此考虑损失的情况下开发了基于场景的模型。在考虑不确定性的同时，风险中性模型可能会提供效果不佳的解决方案。因此，为了纳入决策者的观点，我们还提出了一种规避风险的模型，该模型采用称为条件风险值的风险规避措施来满足不同的偏好。最后，我们根据实际数据进行计算实验，以比较建模方法的性能，并通过测试不同的风险水平和置信度水平来说明影响。因此，为了纳入决策者的观点，我们还提出了一种规避风险的模型，该模型采用称为条件风险值的风险规避措施来满足不同的偏好。最后，我们根据实际数据进行计算实验，以比较建模方法的性能，并通过测试不同的风险水平和置信度水平来说明影响。因此，为了纳入决策者的观点，我们还提出了一种规避风险的模型，该模型采用称为条件风险值的风险规避措施来满足不同的偏好。最后，我们根据实际数据进行计算实验，以比较建模方法的性能，并通过测试不同的风险水平和置信度水平来说明影响。