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Optimization of tourism impacts within protected areas by means of genetic algorithms

机译：利用遗传算法优化保护区内旅游业影响

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The search for a balance between nature conservation and tourism development within protected areas is becoming an increasingly multifaceted problem worldwide, as outlined by an increasing number of authors and highlighted at several international events. Since it is unlikely that all management objectives will reach their optimum values simultaneously, an optimization approach is required to meet multiple, conflicting goals and to obtain an overall trade-off in terms of the conceived objectives. In this paper we propose a new model for optimizing the allocation of tourist infrastructures (refuges and camping sites), and apply it to a protected area in the European Alps, where tourism has grown considerably in recent years. To reach this goal, a complex model based on genetic algorithms was required (instead of a common multicriteria analysis) to obtain a complex interplay in the form of a dynamical simulation where candidate solutions are interactively evaluated. In accordance with local actors, we selected 18 quantifiable criteria encompassing all relevant tourist activities within the study area. These were translated into geographic information system (GIS) layers, submitted to a genetic optimization procedure and compared the performances of the optimized tourist allocations with those of existing infrastructures and with worst case scenarios. Resulting tourist allocations perform very well, while existing tourist sites behaved halfway between the fittest and the least fit genetic solutions, since they prioritized logistic and safety criteria rather than ecological ones. The proposed model is a very flexible and effective tool, easily exportable to any protected area, with implications for researchers and policymakers who aim to provide an effective balance between nature and human impact.
机译：在全球范围内寻求自然保护和旅游业发展之间的平衡的问题正日益成为一个多方面的问题，越来越多的作者对此进行了概述，并在若干国际事件中对此进行了强调。由于不可能所有管理目标都同时达到其最佳值，因此需要一种优化方法来满足多个相互矛盾的目标，并就所设想的目标进行总体权衡。在本文中，我们提出了一种用于优化旅游基础设施（避难所和露营地）分配的新模型，并将其应用于欧洲阿尔卑斯山的保护区，近年来该地区的旅游业增长迅猛。为了实现此目标，需要一种基于遗传算法的复杂模型（而不是通用的多准则分析），以动态仿真的形式获得复杂的相互作用，其中交互式评估候选解决方案。根据当地参与者，我们选择了18个可量化标准，涵盖了研究区域内所有相关的旅游活动。将这些转换为地理信息系统（GIS）层，提交给遗传优化程序，并将优化的游客分配的性能与现有基础设施的性能以及最坏情况下的性能进行比较。最终的游客分配表现非常好，而现有的游客站点的表现介于最适合和最不适合的遗传解决方案之间，因为它们优先考虑物流和安全标准，而不是生态标准。提议的模型是一种非常灵活和有效的工具，可以很容易地导出到任何保护区，这对旨在在自然与人类影响之间实现有效平衡的研究人员和政策制定者具有意义。

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