Abstract
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
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