Formulating and Solving Nonlinear Integrated Ecological-Economic Models Using GAMS

In order to analyze, understand and prescribe natural resourcemanagement strategies, the decision making framework should ideallycapture the dynamics of inter-dependency between the economic andecological systems in an integrated manner. However, by including twocomplex systems within a single integrated framework makes many of thepresent analytical tools redundant. Computational models on the otherhand are ideally suited to meet this challenge. The size and complexityof models solved through numerical techniques have increasedexponentially over the last decade. This is especially true fornon-linear optimization models. However, although the science of solvingnon-linear models has improved significantly, the solving of thesemodels is still an art. In this paper, we look at the criticalparameters that a modeler needs to be aware of when developingintegrated economic-ecology models and some `tricks' to solve them withthe minimum of effort through the use of the optimization software GAMS(General Algebraic Modeling System).     

人口经济动力学与CGE模型仿真

用通用数学建模系统软件GAMS建立了一个可以用于中长期预测和政策模拟的可计算一般均衡(CGE)模型系统.本系统由人口增长模型、生产模型和消费与储蓄模型组成.利用各个模型间的综合平衡关系和模型的动态反馈结构,将人口增长模型的输出作为外生变量,工资替代率和退休年龄作为控制变量,研究了按照中国人口老龄化的速度和依然运行传统的社会保障体系将会给国民经济和人民生活水平带来的影响,并探索了现有养老金系统改革可能达到的经济与社会效益.     

GAMS supported optimization and predictability study of a multi-objective adsorption process with conflicting regions of optimal operating conditions

In process systems engineering, it is critical to design an effective and optimized process in a short period with minimum experimental trials. However, improvement of some process variables may deteriorate some other criteria due to conflicting regions of factor interests for optimal solution in multi-objective optimization (MOO) processes. Here, the global optimization of an adsorption case study with conflicting optimal solutions based on multi-objective Response Surface Methodology (RSM) design is facilitated with the implementation of BARON solver based on General Algebraic Modeling System (GAMS) with identical factor variables, levels, and model equations. RSM suggested fifteen different optimum settings of which the validation is quite expensive and onerous, whereas GAMS suggested a single optimum setting which makes it more economically viable especially for large scale systems. In addition, the GAMS-based optimization provided more accurate and reliable results when experimentally validated as compared to the RSM-based solution.     

水资源优化配置的可视化决策支持系统分析平台

针对水资源优化配置的复杂性以及多目标性,从水资源、社会、经济和生态环境协调发展出发,基于已经开发并在实践推广应用的水资源多过程模拟和优化配置的复杂整体决策支持分析系统,建立水资源优化配置的可视化决策支持系统分析平台对流域水资源进行优化配置。通过淮河流域水资源与经济社会协调发展的水资源优化配置案例分析与演示,详细阐述该系统操作和分析过程。该系统有助于提高水资源优化管理与合理配置的效率,为水资源管理决策提供一种有效便利的分析平台和工具。     

Profit optimization for chemical process plant based on a probabilistic approach by incorporating material flow uncertainties

This paper reports how the economic performance of a chemical process plant is affected by material flow uncertainties from the plant inlet and outlet. Two chance-constrained optimization models were proposed. The models were tested using case studies of an existing gas processing plant. Profit optimization for the case studies was made with respect to the reliability of holding the process constraints at a certain confidence level [0.5, 1]. The optimal profit change for uncertainty from the plant inlet within the confidence interval [0.96, 1] was 86%. On the other hand, the optimal profit change for uncertainty from the plant outlet was only 2% for the same confidence level interval considered. This suggests that the uncertainty from the plant inlet has a major impact on the overall economic performance of the plant. Sensitivity analysis showed how uncertain parameters from both plant sides can affect the overall profit significantly.     

MCP算法与计算实现:一个示例

混合互补问题(MCP)可以用来描述多种类型的经济模型。本文介绍了MCP的一般形式,及由一般形式推导出的几种常用MCP表达形式。在此基础上,针对一个运输问题,分别采用线性规划与MCP方法求解。特别地,给出了求解该运输问题两种算法的GAMS代码,供读者借鉴。     

GAMS系统在土坡极限荷载计算中的应用

对最新运筹学实用软件系统GAMS作了简单介绍 ,描述了GAMS系统中模型的建立及求解过程。在一土坡极限荷载的算例中 ,运用三维有限元塑性极限分析下限法建立相应的数学规划模型 ,通过GAMS软件非线性优化求解。     

含机组组合的短期水火储联合最优经济调度

为研究抽水蓄能给水火联合调度系统带来的影响,提出了新的含机组组合的水火储联合最优经济调度模型,采用GAMS中含分支定界法的求解器对模型进行求解,仿真验证了所述模型的有效性和可行性。结果表明:所建模型可充分利用水力资源发电,缓解火电的调峰压力;并根据抽水储能的抽水发电特性实现了对火电机组的削峰填谷的作用,在改善火电运行条件的同时,平滑火电出力,减少污染气体的排放,提高整个电力系统运行的稳定性、经济性和环保性。同时,为进一步研究储能对电力系统的影响具有一定的借鉴作用。     

Multi-objective optimization of the stack of a thermoacoustic engine using GAMS

This work illustrates the use of a multi-objective optimization approach to model and optimize the performance of a simple thermoacoustic engine. System parameters and constraints that capture the underlying thermoacoustic dynamics have been used to define the model. Work output, viscous loss, conductive heat loss, convective heat loss and radiative heat loss have been used to measure the performance of the engine. The optimization task is formulated as a five-criterion mixed-integer non-linear programming problem. Since we optimize multiple objectives simultaneously, each objective component has been given a weighting factor to provide appropriate user-defined emphasis. A practical example is given to illustrate the approach. We have determined a design statement of a stack describing how the design would change if emphasis is given to one objective in particular. We also considered optimization of multiple objectives components simultaneously and identify global optimal solutions describing the stack geometry using the augmented ɛ-constraint method. This approach has been implemented in GAMS (General Algebraic Modelling System).     

A Cross Entropy-based heuristic for the capacitated multi-source Weber problem with facility fixed cost

This paper investigates a capacitated planar location–allocation problem with facility fixed cost. A zone-based fixed cost which consists of production and installation costs is considered. A nonlinear and mixed integer formulation is first presented. A powerful three stage Cross Entropy meta-heuristic with novel density functions is proposed. In the first stage a covering location problem providing a multivariate normal density function for the associated stochastic problem is solved. The allocation values considering a multinomial density function are obtained in the second stage. In the third stage, single facility continuous location problems are solved. Several instances of various sizes are used to assess the performance of the proposed meta-heuristic. Our approach performs well when compared with the optimizer GAMS which is used to provide the optimal solution for small size instances and lower/upper bounds for some of the larger ones.