A novel MINLP-based representation of the original complex model for predicting gasoline emissions

The Environmental Protection Agency (EPA) introduced Reformulated Gasoline (RFG) requirements as a measure to reduce emissions from gasoline-powered vehicles in certain geographic areas. As part of this effort, the EPA developed empirical models for predicting emissions as a function of gasoline properties and established statutory baseline emissions from a representative set of gasolines. All reformulated gasoline requires certification via this model, known as the Complex Model, and all refiners and importers calculate emissions performance reductions from the statutory baseline gasoline. The current representation of the Complex Model is extremely difficult to implement within refinery operations models or to use in combination with models for designer gasoline. RFG and boutique fuels are key driving forces in the North American refining industry.The RFG models introduce increasingly complex constraints with the major limitation that they are implicitly defined through a series of complicated disjunctions assembled by the EPA in the form of spreadsheets. This implicit and cumbersome representation of the emissions predictive models renders rigorous optimization and sensitivity analysis very difficult to address directly. In this paper, we discuss how the federal government requirements for reformulated gasoline can be restated as a set of mixed-integer nonlinear programming (MINLP) constraints with the aid of disjunctive programming techniques. We illustrate the use of this model with two simple example fuel blending problems.     

New Tractable Classes From Old

The constraint satisfaction problem is known to be NP-hard in general, but a number of restrictions of the problem have been identified over the years which ensure tractability. This paper introduces two simple methods of combining two or more tractable classes over disjoint domains, in order to synthesise larger, more expressive tractable classes. We demonstrate that the classes so obtained are genuinely novel, and have not been previously identified. In addition, we use algebraic techniques to extend the tractable classes which we identify, and to show that the algorithms for solving these extended classes can be less than obvious.     

基于炼油过程生产特性的优化调度模型

针对炼油过程的平稳性和长期性等生产特性,研究了其优化调度问题。给出了平稳性和长期性的定义,并对生产特性进行了模型化描述。提出了生产的平稳度、长期度性能指标,以实现生产特性的量化表达和评价。在此基础上建立了炼油过程的广义析取规划优化调度模型。以某炼油过程生产调度为例,对比有无体现生产特性的优化调度仿真结果表明:基于炼油过程生产特性的优化调度模型能够提高生产特性性能,得到的调度方案更为可行和实用。     

Optimization-based cosmetic formulation: Integration of mechanistic model,surrogate model,and heuristics

Multiple functional and hard-to-quantify sensorial product attributes that can be satisfied by a large number of cosmetic ingredients are required in the design of cosmetics. To overcome this problem, a new optimization-based approach for expediting cosmetic formulation is presented. It exploits the use of a hierarchy of models in an iterative manner to refine the search for creating the highest-quality cosmetic product. First, a systematic procedure is proposed for optimization problem formulation, where the cosmetic formulation problem is defined, design variables are specified, and a set of models for sensorial perception and desired product properties are identified. Then, a solution strategy that involves iterative model adoption and two numerical techniques (i.e., generalized disjunctive programming reformulation and model substitution) is applied to improve the efficiency of solving the optimization problem and to find better solutions. The applicability of the proposed procedure and solution strategy is illustrated with a perfume formulation example.     

基于多种群蚁群算法的柔性作业车间调度研究

针对柔性作业车间调度的特点,设计了柔性作业车间调度析取图模型,结合蚁群分工组织的工作方式,给出了基于竞争规则的多种群蚁群算法求解方法。算法中不同种群的蚂蚁被放置在析取图中不同的工序节点上,通过核心种群的引导,充分发挥蚁群协作竞争的并行高效特点,满足柔性作业车间调度的要求。仿真实验表明该算法求解柔性作业车间调度具有可行性和有效性。     

应用析取克里格方法估计区域地下水埋深分布

本文比较了几种常用的估计土壤空间变异的计算方法，介绍了析取克里格的理论和计算方法，给出计算区域地下水埋深分布的实例，并对普通克里格和析取克里格的计算方差作了比较。     

双枝模糊逻辑(II)

在双枝模糊集基础上,通过对单枝模糊逻辑的合理扩展,建立了双枝模糊逻辑的框架。从双枝模糊命题入手,给出双枝模糊逻辑的性质和双枝模糊逻辑公式,以及双枝模糊逻辑的析取范式与合取范式。这些结果为研究双枝模糊推理和双枝模糊控制奠定了基础。     

命题逻辑中推理理论的数字形式

本文对简单合取式的主析取范式及简单析取式的主合取范式作了数字形式上的表示,在一定程度上简化了自然推理系统P.     

命题公式主范式的二进制求法

命题公式主范式在数理逻辑中有重要作用,其方法论也颇具价值。针对解决求主析取范式的传统方法比较繁琐的情况,通过对极小项下标特征的讨论,利用二进制给出了由命题公式的析取范式确定主析范式中的二进制求法,从而简化了由繁杂的命题公式推演或真值表计算求主析取范式的计算过程,给出了求命题公式主析取范式的简便求法——表格法。该法稍做变动后,对求主合析取范式同样适用。