Sustainable pattern analysis of a publicly owned Material Recovery Facility in a fast-growing urban setting under uncertainty

Sustainable development goals are achievable through the installation of Material Recovery Facilities (MRFs) in certain solid waste management systems, especially those in rapidly expanding multi-district urban areas. MRFs are a cost-effective alternative when curbside recycling does not demonstrate long-term success. Previous capacity planning uses mixed integer programming optimization for the urban center of the city of San Antonio, Texas to establish that a publicly owned material recovery facility is preferable to a privatized facility. As a companion study, this analysis demonstrates that a MRF alleviates economic, political, and social pressures facing solid waste management under uncertainty. It explores the impact of uncertainty in decision alternatives in an urban environmental system. From this unique angle, waste generation, incidence of recyclables in the waste stream, routing distances, recycling participation, and other planning components are taken as intervals to expand upon previous deterministic integer-programming models. The information incorporated into the optimization objectives includes economic impacts for recycling income and cost components in waste management. The constraint set consists of mass balance, capacity limitation, recycling limitation, scale economy, conditionality, and relevant screening restrictions. Due to the fragmented data set, a grey integer programming modeling approach quantifies the consequences of inexact information as it propagates through the final solutions in the optimization process. The grey algorithm screens optimal shipping patterns and an ideal MRF location and capacity. Two case settings compare MRF selection policies where optimal solutions exemplify the value of grey programming in the context of integrated solid waste management.     

Multi-objective Programming and Social Welfare Analysis of Rural–urban Land Conversion Decision-making

Abstract

Rural–urban land conversion is an inevitable phenomenon in urbanization and industrialization. And the decision-making issue about this conversion is multi-objective because the social decision maker (the whole of central government and local authority) has to integrate the requirements of different interest groups (rural collective economic organizations, peasants, urban land users and the ones affected indirectly) and harmonize the sub-objects (economic, social and ecological outcomes) of this land allocation process. This paper established a multi-objective programming model for rural–urban land conversion decision-making and made some social welfare analysis correspondingly. Result shows that the general object of rural–urban land conversion decision-making is to reach the optimal level of social welfare in a certain state of resources allocation, while the preference of social decision makers and the value judgment of interest groups are two crucial factors which determine the realization of the rural–urban land conversion decision-making objects.     

滑坡预测的改进前馈网络方法研究

作者提出了滑坡位移预测的一种改进前馈网络方法——目的规划法,与通常的前馈网络方法相比,该方法改进了网络的准则函数,降低了网络的灵敏度,改善了网络的泛化性能,提高了滑坡位移的预测精度。同时它是一种面向数据的方法,适合于不同地区不同条件下滑坡的预测。清江隔河岩库区滑坡和卧龙寺滑坡的实例研究表明了该方法的可行性及有效性。     

结构分析中模拟与仿真技术研究

由于像洪水、水灾、地震这样一类自然灾害的原型重复试验几乎是不可能的,因此计算机仿真技术在这一领域的应用具有重要的意义。本文探索了土木工程中模拟与仿真的概念、特征及实现途径,阐述了关于仿真智能化、可视化的技术细节及仿真的基本思路;结合面向对象程序设计（OOP）概念,提出了结构分析程序设计的原则及标准。在此基础上,编写了基于Windows的结构有限元分析软件SmartSEA.     

基于灾害风险评估的山地城市固定避难场所布局优化研究——以东川区为例

研究以各区域灾害风险评估系数作为权重系数,对山地小城市各区域避难场所进行优化布局。首先,通过风险值=危险性*脆弱性/抗灾救灾能力机理表达式构建灾害风险评估指标体系,并以模糊综合评价法得出灾害风险评估数值,在此基础上通过多目标选址优化模型来构建山地城市避难场所的优化模型,其中灾害风险评估系数作为影响布局的权重因素纳入其中。最后,以东川区为研究对象,对其固定避难场所进行优化布局研究,结果表明:东川区城区固定避灾场所数量可在接近最优解的情况下达到效果最优。     

Suitability of short or long conservation contracts under ecological and socio-economic uncertainty

Acquisition of land rights has become a primary tool used to protect terrestrial biodiversity. Fixed length contracts are often used when trying to secure conservation benefits on private land in agri-environment schemes and payment for environmental services schemes, but the duration of the conservation contracts used in different programmes varies. To date, very little research has been undertaken to determine the situations in which contracts of differing lengths are optimal or when conservation agencies or groups should use a portfolio of different contract lengths rather than relying on a single type. Using stochastic dynamic programming and related heuristic methods, we investigate how the choice between short or long conservation contracts is affected by uncertainty regarding the future availability of sites and their ecological condition. We also examine the benefits offered by using a portfolio of different contract lengths. Conservation agencies must pay private landowners a premium to secure longer agreements and because of this, shorter contracts are advantageous if sites are likely to remain available for conservation in the future. Long contracts are preferred when future site availability becomes more unlikely. In contrast to uncertainty over site availability, uncertainty over future ecological conditions has little effect on contract selection and only markedly influences the choice between short and long contracts when there is heterogeneity across sites in expected conservation outcomes and future availability of sites is also uncertain. Finally, when future site availability is unlikely, the use of a portfolio of short and long contracts would offer greater conservation gains than using either type in isolation, even though this option is not yet one that is commonly found in conservation practice.     

基于CLUE-S和灰色线性规划的嘉兴北部土地利用优化配置研究

构建基于CLUE-S与灰色线性规划混合模型的土地利用优化配置方法,在导入区域政策、社会经济、生态目标和土地利用现状等条件下,进行土地利用数量结构与空间布局的统一优化,并以嘉兴北部地区为例进行实证研究,共设置现状趋势情景、规划目标情景和规划可持续情景这3种模拟情景.规划可持续情景侧重社会经济环境效益,故对建设用地快速增长和农用地持续减少起到明显调控作用,可实现生态敏感区环境和粮食安全的双重保护,是理想的土地利用优化方案.CLUE-S模型与灰色线性规划的耦合能够兼顾现状条件和区域发展目标,模拟土地利用的数量和空间变化,是解决土地资源优化配置问题的有效方法.     

Disequilibrium and Indivisibility of Pollution Control Equipment Under a Permit-Trading System: A Case Study of Kao-Hsiung and Ping-Tung Counties in Taiwan

A mixed-integer programming model that minimizes the social abatement cost is used to investigate whether a market equilibrium condition could be reached in a newly proposed permit-trading market for nitrogen oxide control in Taiwan. Unlike in previous studies, unit pollution abatement cost is determined endogenously by incorporating technology adoption as a binary decision variable. The results show that when technologies are lumpy and irreversible, disequilibrium might occur due to firms’ inability to manage their emission levels after installing equipment with fixed size and control capacity.

A Model for Landscape Planning Under Complex Spatial Conditions

We present a new mathematical programming framework that is adaptable to a variety of spatially explicit landscape problems in environmental investment, conservation, and land-use planning, transport planning, and agriculture. As part of capturing spatial interdependencies, the framework considers decision variables at two levels, finely spaced grid cells and landholdings. We applied the framework to an environmental investment problem using objective functions representing biodiversity and carbon sequestration. We also tested the model to optimize the path of a road through part of the landscape. Using the Nambucca case study in eastern Australia, we applied a hybrid greedy randomised adaptive search procedure (GRASP) to find solutions to the model.     

Optimal Selection of Priority Development Areas Considering Tradeoffs Between Hydrology and Development Configuration

Mixed-integer linear programs are proposed for siting development and conservation areas in watersheds, addressing economic objectives (development perimeter and proximity) and ecological objectives. Links between watershed hydrology and ecology need not be well defined. Parameters for the linear programs are obtained from linearization of the SWAT hydrologic model.