We are observing more often extreme climate incidents because of global warming. There is a dire requirement for governments, enterprises, the overall population, and academics to take facilitated activities so as to handle the difficulties forced by environmental change. The most important strategic issue is to design an effective and environmentally concerned logistics system as transportation is one of the fundamental reasons for carbon emanations. Having this goal and mentioned highly important contributions in the field, this article introduces an unprecedented integrated mathematical model for a green solid transportation system with dwell time to execute the carbon tax, cap, and offset regulation. Due to market fluctuations, the supply and demand parameters are not always of crisp nature. Hence, a twofold (type-2 intuitionistic) uncertainty is incorporated in this article to provide a realistic transportation system. A new ranking defuzzification technique is presented for conversion into a deterministic form. After that, a fuzzy technique and a nonfuzzy technique are used to get the Pareto-optimal solution of the proposed problem. The performances of our findings are discussed with industrial-based application examples. Moreover, a comparative study is explored among the other relevant existing techniques. Managerial insights, conclusions, and avenues of future scopes are offered at the end of this article.

中文翻译：

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类型 2 模糊逻辑在碳税、上限和抵消政策下具有停留时间的多目标绿色固体交通位置问题中的应用：模糊与非模糊技术

由于全球变暖，我们观察到更多的极端气候事件。迫切需要政府、企业、全体人民和学术界开展便利活动，以应对环境变化带来的困难。最重要的战略问题是设计一个有效且环保的物流系统，因为运输是碳排放的根本原因之一。有了这个目标并提到了该领域的重要贡献，本文介绍了一种前所未有的集成数学模型，用于绿色固体交通系统，具有执行碳税、上限和抵消监管的停留时间。由于市场波动，供需参数并不总是清晰的。因此，本文包含双重（2 类直觉）不确定性，以提供现实的交通系统。提出了一种新的排序去模糊化技术，用于转换为确定性形式。之后，使用模糊技术和非模糊技术来获得所提出问题的帕累托最优解。我们的研究结果的性能通过基于工业的应用示例进行了讨论。此外，还探讨了其他相关现有技术之间的比较研究。本文末尾提供了管理见解、结论和未来范围的途径。使用模糊技术和非模糊技术来获得所提出问题的帕累托最优解。我们的研究结果的性能通过基于工业的应用示例进行了讨论。此外，还探讨了其他相关现有技术之间的比较研究。本文末尾提供了管理见解、结论和未来范围的途径。使用模糊技术和非模糊技术来获得所提出问题的帕累托最优解。我们的研究结果的性能通过基于工业的应用示例进行了讨论。此外，还探讨了其他相关现有技术之间的比较研究。本文末尾提供了管理见解、结论和未来范围的途径。