基于不确定性的水资源配置双层模型及其实证研究

针对水资源管理系统的不确定性和复杂性,引入区间参数表达系统中的不确定信息,建立了反映水资源管理者和使用者之间层次关系的区间双层规划模型,并以北京市丰台区水资源管理系统为例进行实证研究.同时,基于交互式算法和模糊满意度算法,用Lingo软件编程求解,确定了丰台区水资源的优化配置方案.规划结果表明:丰台区水资源管理系统的供需水量基本达到平衡,75%的供水量来源于本地地表水和南水北调水源;规划期内的系统经济效益预期达到2.22×10~9~5.16×10~9元,COD排放量将达到1.47×10~4~1.89×10~4t.区间结果提高了优化方案的灵活性,系统满意度体现了上层决策者与下层决策者的交互.其次,通过设计4种COD最大允许排放情景,说明了不同的COD排放约束将对规划结果产生重要影响.最后,通过3种模型的对比分析可以为丰台区水资源配置提供不同发展情景下的优化方案.     

基于生态系统服务价值的东北农牧交错区土地利用格局优化与评价

为完善土地规划评估指标、挖掘东北农牧交错区生态建设潜力,在明晰2001—2018年东北农牧交错区生态系统服务价值（ESV）时空特征的基础上,分别以供给服务、调节服务和支持服务三种生态功能为优先发展目标,结合CLUE-S模型提出了三种土地利用格局规划方案。结果显示：（1）2001—2018年研究区ESV总量增长9.69%,其中调节、支持和供给服务功能年均占比分别为67.25%、21.88%和6.74%;（2）三种规划方案对区域ESV提升明显,其中支持服务优先情景下ESV总量提升5.84%,高于供给服务（2.66%）和调节服务（5.19%）优先情景;（3）不同土地利用类型的环境适应性不同,研究区西北部、西南部和东部部分地区更适宜造林和退耕,ESV总量和支持服务价值的提升潜力较大,而北部和东南部地区更适宜开垦农田,供给和调节服务价值提升潜力较大。不同生态系统服务间的权衡与协同是保障区域生态与经济稳定可持续发展的关键。充分考虑政策与环境适应性等因素,对东北农牧交错区土地利用格局进行优化,将为当地规划提供理论基础和实践参考。     

A dynamic programming implemented resource competition game theoretic model

Resource competition is commonly occurred in animal populations and studied intensively by researchers. Previous studies have applied game theoretic model by finding Nash equilibrium to investigate this phenomenon. However computation of the Nash equilibrium requires an understanding of the payoff matrix that allocates the rewards received by players when they adopt each of the strategies in the game. In our study we present a dynamic programming implemented framework to compute 2 × 2 intraspecific finite resource allocation game's payoff matrix explicitly. We assume that two distinct types of individuals, aggressive and non-aggressive, are in the population. Then we divide the entire animal development period into three different stages: initialization, quasilinear growth and termination. Each stage for each type of players is specified with their own development coefficient, which determines how resource consumption could convert into strength as reward. Each player has equal and finite resource at the beginning of their development and fights against other players in the population to maximize its own potential reward. Based on these assumptions it is reasonable to use backward induction dynamic programming to compute payoff matrix. We present numerical examples for three different types of aggressive individuals and compute the payoff matrices correspondingly. Then we use the derived payoff matrices to determine the Nash equilibrium and Evolutionary Stable Strategy. Our research provide a framework for future quantitative studies on animal resource competition problems and could be expanded to n-players interspecific stochastic asymmetric resource allocation problem by changing some settings of dynamic programming formulation.     

Setting Realistic Recovery Targets for Two Interacting Endangered Species,Sea Otter and Northern Abalone

Failure to account for interactions between endangered species may lead to unexpected population dynamics, inefficient management strategies, waste of scarce resources, and, at worst, increased extinction risk. The importance of species interactions is undisputed, yet recovery targets generally do not account for such interactions. This shortcoming is a consequence of species‐centered legislation, but also of uncertainty surrounding the dynamics of species interactions and the complexity of modeling such interactions. The northern sea otter (Enhydra lutris kenyoni) and one of its preferred prey, northern abalone (Haliotis kamtschatkana), are endangered species for which recovery strategies have been developed without consideration of their strong predator–prey interactions. Using simulation‐based optimization procedures from artificial intelligence, namely reinforcement learning and stochastic dynamic programming, we combined sea otter and northern abalone population models with functional‐response models and examined how different management actions affect population dynamics and the likelihood of achieving recovery targets for each species through time. Recovery targets for these interacting species were difficult to achieve simultaneously in the absence of management. Although sea otters were predicted to recover, achieving abalone recovery targets failed even when threats to abalone such as predation and poaching were reduced. A management strategy entailing a 50% reduction in the poaching of northern abalone was a minimum requirement to reach short‐term recovery goals for northern abalone when sea otters were present. Removing sea otters had a marginally positive effect on the abalone population but only when we assumed a functional response with strong predation pressure. Our optimization method could be applied more generally to any interacting threatened or invasive species for which there are multiple conservation objectives. Definición de Metas de Recuperación Realistas para Dos Especies en Peligro Interactuantes, Enhydra lutris y Haliotis kamtschatkana     

Wildlife corridors as a connected subgraph problem

Wildlife corridors connect areas of biological significance to mitigate the negative ecological impacts of habitat fragmentation. In this article we formalize the optimal corridor design as a connected subgraph problem, which maximizes the amount of suitable habitat in a fully connected parcel network linking core habitat areas, subject to a constraint on the funds available for land acquisition. To solve this challenging computational problem, we propose a hybrid approach that combines graph algorithms with Mixed Integer Programming-based optimization. We apply this technique to the design of corridors for grizzly bears in the U.S. Northern Rockies, illustrating the underlying computational complexities by varying the granularity of the parcels available for acquisition. The approach that is introduced is general and can be applied to other species or other similar problems, such as those occurring in social networks.     

多应急点多需求点物资调度的灰色多目标规划

为了研究在信息不确定情况下,应急物资需求量和应急时间为区间数的物资调度问题,基于灰色系统理论构建多目标规划模型,结合实例并采用灰色区间数求解方法,计算物资调度方案。结果表明:应急物资调度与区间参数取值无关,相关调度模型与算法对应急初期的实际物资调度具有参考意义;运用灰色区间数描述调度中的不确定因素,有助于提高实际物资调度过程中的准确性。