论文标题
气候和经济的动态综合模型的多目标最佳控制：行动进化
Multi-objective Optimal Control of Dynamic Integrated Model of Climate and Economy: Evolution in Action
论文作者
论文摘要
研究气候变化经济学的广泛使用模型之一是气候和经济（DICE）的动态综合模型，该模型是由William Nordhaus教授开发的，William Nordhaus是2018年诺贝尔经济科学纪念奖的获奖者之一。最初是在骰子动力学上定义了单一目标的最佳控制问题，该问题旨在最大化社会福利。在本文中，在骰子模型上定义的双目标最佳控制问题，其目标是最大化社会福利并最大程度地减少大气的温度偏差。使用非主导分类遗传算法II（NSGA-II）解决的多目标最佳控制问题也将其与该问题的单目标版本上的先前作品进行了比较。由此产生的帕累托阵线重新发现了先前的结果，并概括为广泛的非优势解决方案，以最大程度地减少全球温度偏差，同时优化经济福利。先前使用的单一目标方法无法创造出如此多种可能性，因此，其提供的解决方案在视觉和可触及性能方面受到限制。除此之外，除非我们在全球条件上具有重大的技术进步或积极的变化，否则导致的帕累托最佳套件表明，温度偏差不能低于一定的下限。
One of the widely used models for studying economics of climate change is the Dynamic Integrated model of Climate and Economy (DICE), which has been developed by Professor William Nordhaus, one of the laureates of the 2018 Nobel Memorial Prize in Economic Sciences. Originally a single-objective optimal control problem has been defined on DICE dynamics, which is aimed to maximize the social welfare. In this paper, a bi-objective optimal control problem defined on DICE model, objectives of which are maximizing social welfare and minimizing the temperature deviation of atmosphere. This multi-objective optimal control problem solved using Non-Dominated Sorting Genetic Algorithm II (NSGA-II) also it is compared to previous works on single-objective version of the problem. The resulting Pareto front rediscovers the previous results and generalizes to a wide range of non-dominant solutions to minimize the global temperature deviation while optimizing the economic welfare. The previously used single-objective approach is unable to create such a variety of possibilities, hence, its offered solution is limited in vision and reachable performance. Beside this, resulting Pareto-optimal set reveals the fact that temperature deviation cannot go below a certain lower limit, unless we have significant technology advancement or positive change in global conditions.
