ABSTRACT In this paper, a fuzzy-stochastic optimization model is developed for an intermodal fleet management system of a large international transportation company. The proposed model integrates various strategic, tactical and operational level decisions simultaneously. Since real-life fleet planning problems may involve different types of uncertainty jointly such as randomness and fuzziness, a hybrid chance-constrained programming and fuzzy interactive resolution-based approach is employed. Therefore, stochastic import/export freight demand and fuzzy transit times, truck/trailer availabilities, the transport capacity of Ro-Ro vessels, bounds on block train services, etc. can also be taken into account concurrently. In addition to minimize overall transportation costs, optimization of total transit times and CO2 emission values are also incorporated in order to provide sustainable fleet plans by maximizing customer satisfaction and environmental considerations. Computational results show that effective and efficient fleet plans can be produced by making use of the proposed optimization model.

中文翻译：

---

某国际运输公司联运车队管理问题的模糊随机优化模型

摘要在本文中，为一家大型国际运输公司的多式联运车队管理系统开发了模糊随机优化模型。所提出的模型同时集成了各种战略、战术和操作层面的决策。由于现实生活中的车队规划问题可能涉及不同类型的不确定性，例如随机性和模糊性，因此采用了混合机会约束编程和基于模糊交互式分辨率的方法。因此，随机的进出口货运需求和模糊的运输时间、卡车/拖车的可用性、滚装船的运输能力、班列服务的界限等也可以同时考虑。除了最大限度地降低整体运输成本，还整合了总运输时间和二氧化碳排放值的优化，以通过最大限度地提高客户满意度和环境考虑来提供可持续的车队计划。计算结果表明，利用所提出的优化模型可以产生有效和高效的车队计划。