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A step-wise genetic-algorithm-based approach for improving the sustainability of any country and for determining the characteristics of the ideally sustainable country

机译:基于逐步遗传算法的方法,可改善任何国家的可持续性并确定理想的可持续性国家的特征

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A step-wise genetic algorithm (GA)-based approach is put forward for (a) guiding any interested country on how to optimally improve its environmental sustainability (ES), and (b) determining the characteristics of the (theoretically) maximally sustainable country. The Environmental Sustainability Index (ESI) 2005 is used to this end, with the GA genes, chromosomes, and fitness values corresponding to the ESI 2005 indicators, sets of indicator values, and scores, respectively. Following GA operation, any interested country can increase - and, ideally, maximise - its ES via the following procedure: a chromosome with similar gene values to the ESI indicator values of the interested country, but demonstrating higher fitness (ESI score), is appropriately selected from any GA generation such that the changes that are necessary in order for the country's ESI indicator values to match those of the selected chromosome to be not only implementable, but furthermore capable of producing the maximal improvement in terms of ES. By repeating this procedure on each updated version of the interested country, the country's indicator values and ESI score are progressively modified towards maximal ES. Alternative optimisation approaches, such as pattern search (PS) and simulated annealing (SA), are also capable of reaching maximal ES, yet - due to their single-state basis of operation - do not permit the concurrent investigation of alternative paths towards maximal ES, and - furthermore - do not guarantee the identification of the appropriate indicator(s) to be modified. An interesting finding that is common to GA, PS, and SA operation is that the fitness values of the best chromosomes/states invariably exceed not only the ESI score of the top-ranking ESI 2005 country (75.1 of Finland), but - furthermore - the “perfect” ESI 2005 score of 100 by around 10, thus putting into question the construction details of the ESI 2005.1
机译:提出了一种基于遗传算法的方法,用于(a)指导任何感兴趣的国家如何最佳地改善其环境可持续性(ES),以及(b)确定(理论上)最大可持续性国家的特征。为此,使用了环境可持续性指数(ESI)2005,GA基因,染色体和适应度值分别对应于ESI 2005指标,指标值集和得分。在进行通用航空操作之后,任何感兴趣的国家都可以通过以下过程来增加-并在最大程度上最大化其ES:具有与感兴趣国家的ESI指标值相似的基因值,但具有较高适应性(ESI评分)的染色体选自任何GA世代,以便使该国的ESI指标值与所选染色体的ESI指标值相匹配所必需的更改不仅可以实施,而且能够在ES方面产生最大的改善。通过在感兴趣国家的每个更新版本上重复此过程,该国家的指标值和ESI分数将逐步朝着最大ES方向修改。诸如模式搜索(PS)和模拟退火(SA)之类的替代优化方法也能够达到最大ES,但是由于其单状态操作基础,因此不允许同时研究替代途径来实现最大ES ,此外-不保证标识要修改的适当指标。 GA,PS和SA操作共有的一个有趣发现是,最佳染色体/状态的适应度值始终不仅超过排名最高的ESI 2005国家(芬兰为75.1)的ESI得分,而且- ESI 2005的“完美”评分为100,满分为10,因此对ESI 2005.1的构造细节提出了质疑

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