石油供应链计划层优化与不确定性风险管理模型

提出了一种基于有限场景的两阶段随机混合整数线性规划(MILP)模型,来优化不确定条件下多周期、多层级的石油工业供应链的计划层管理。模型以碳排放税的形式将减少CO2排放的环境目标融入到经济目标之中。供应链的各级节点均以黑箱的形式存在,使模型得以简化,在时间尺度相对较长的计划层获得优化结果,为供应链的计划与管理提供指导方案。并且分析了算例最优期望收益的风险性,在此基础上引入风险管理约束,得到了带有风险管理约束的供应链计划层优化模型。该模型的结果与原模型相比,期望收益附近的收益风险性降低。     

基于风险管理的石化工业供应链网络设计

提出了一种带有风险约束的石化工业供应链设计方法,能够应对需求不确定性带来的影响。供应链网络设计问题包括仓储和分销中心的布局结构及容量安排,以及各级之间的物流连接关系。首先建立了不确定条件下的供应链设计模型,并在此基础上加入了风险约束,最后将多目标优化问题转化为单目标优化问题,建立了确定性的两阶段随机规划模型。以某个化工集团供应链设计为例,分析了风险管理在建立供应链中的重要性。     

不确定条件下石化企业供应链计划优化

针对石化企业供应链计划层的不确定性,提出了一种多周期、多产品的计划优化模型。基于离散时间建模方法,利用模糊可能性方法将不确定性问题转化为确定性问题,建立了混合整数线性规划模型。同时采用模型预测控制思想,利用模型的动态属性为决策者提供了不同满意度下的决策序列。以某炼油企业供应链为实例,证明了本方法的有效性。     

基于启发式知识和自适用遗传算法的复合材料铺层优化设计

一般针对复合材料层合板铺层优化设计的研究多侧重于算法的研究,没有考虑到铺层知识对铺层的约束.本文建立了基于启发式知识和自适应遗传算法的复合材料层合板铺层优化模型,采用带置信度的IF-THEN模糊表达方式表达层合板铺层启发式知识,以蔡-希尔(Tsai-Hill)强度准则建立自适用遗传算法的适应度函数,在原有约束的基础上增加了铺层启发式知识约束.算例应用上述模型求解层合板的最佳铺层顺序,并将该结果和没有应用铺层知识约束的优化结果进行比较,证明了该模型的优越性和实用性.     

化工企业供应链长期规划与投资决策体系

提出了化工企业供应链长期规划与投资决策的基本策略.首先,基于企业运营的3类战略目标（企业利益目标、社会利益目标和顾客利益目标）,采用层次分析法建立投资决策全面评价体系.然后,根据投资决策全面评价体系,建立供应链长期规划与解瓶颈的多目标优化模型,并提出了系统可操作性指标的量化方案.最后,结合投资决策全面评价的权重体系,采用目标规划,对该多目标优化模型求解,作出优化的投资决策.以某炼油厂的扩产规划为例,进行了供应链长期规划与投资决策的实例研究.     

基于条件场景的不确定性石化供应链优化方法

针对产品需求及其价格存在不确定性的石化供应链计划层最优化问题,本文建立了一种基于条件场景的石化供应链最优化方法。用多个离散场景近似随机变量概率的连续分布,根据随机变量的概率分布特征,对场景发生的概率进行参数估计,进而建立了基于场景的两阶段混合整数线性规划(MILP)模型。利用基于场景的优化结果随离散网格数增加而逐渐趋近连续的随机优化结果这一规律,给出了获得最佳离散网格数的方法,实现了计算时间成本与计算精度之间的平衡。在此基础上引入条件概率方法,利用两个随机变量间的相关性,建立了以产品价格及其需求量为不确定性的石化供应链优化方法。结果表明,与传统未考虑随机变量间相关性的一般场景划分方法相比,本文基于条件场景的随机优化方法可以更快地获得最佳场景数目,进而有效降低了计算量。     

基于收益共享契约的基础油供应链建模方法

针对以炼油企业为主导的基础油供应链中所涉及到的多对一原料采购与定价问题,利用Stackelberg博弈问题求解方法,建立了分散决策模式下实际现有模型与收益共享契约模型,并引入粒子群优化算法,对模型进行参数估计,分析各参数对于供应链各成员利润的影响,同时得到一个广泛适用的采购定价模型。仿真结果表明,采用收益共享契约机制协调了供应链成员间利润分配,提高了原料供应商、炼油企业及供应链总体利润。     

浅析国营大中型企业建立内控管理体系的必要性

内部控制的动力源于风险防范,并构成风险管理的必要环节,企业管理的重要内容之一就是建立风险评估系统,认识和分析企业整体目标及各活动层目标,以及影响这些目标实现的内在和外在因素发生的概率及可能后果,并采取相应的控制措施。因此,风险防范既是企业管理的必要部分,也是内部控制体系建立的内在动力。内部控制体系的建立是与风险管理要求相并存,正因为存在各种各样的风险,企业才有必要建立良好的内部控制管理体系,配合风险管理,实现企业目标。国营大中型企业经济业务复杂、运转环节多,生产经营的风险性大,建立内控管理体系是强化管理、规…     

化工过程预测控制的在线优化实现机制

多层结构的预测控制已逐渐成为工业过程控制领域的主流控制方案。在此控制架构基础上,根据操作工或工艺优化所给定期望值的不同,将稳态优化问题具体化为两种基本情况,并对此提出基于复合目标函数的优化问题,可针对不同过程要求退化为线性、二次或二者兼有的优化问题形式。为保证最优目标的可行性并在一定程度上避免关键变量饱和,对不可行的期望值适当调整。将所得最优目标增量化处理后送入模型预测控制动态控制层,确保了上下层之间变量传递的一致性。包含约束的全混槽反应器系统仿真实例表明,流程的优化实现层可针对不同的过程要求有效给出最优目标以便动态控制,说明了该优化流程的可行性。     

多目标优化在化工领域中的应用进展

环境友好的化工过程不仅需要关注与生产过程收益密切相关的原材料费用、设备费与操作费等,还要综合考虑生产过程的安全性与废弃物的环境危害等指标。多目标优化是在综合考虑各个目标的情况下,根据问题的需要,寻求一组合适的优化方案即Pareto解集。文章主要从动力学、生产过程、产品供应链等方面综述了近几年多目标优化在不同化工生产过程中的应用。     

Robust design and operations of hydrocarbon biofuel supply chain integrating with existing petroleum refineries considering unit cost objective

This paper addresses the optimal design and planning of the advanced hydrocarbon biofuel supply chain with the unit cost objective. Benefited from the drop-in properties of advanced hydrocarbon biofuels, the supply chain takes advantage of the existing petroleum infrastructure, which may lead to significant capital and transportation savings. A mixed-integer linear programming model is proposed to simultaneously consider the supply chain design, integration strategy selection, and production planning. A robust optimization approach which tradeoffs the performance and conservatism is adopted to deal with the demand and supply uncertainty. Moreover, the unit cost objective makes the final products more cost-competitive. The resulting mixed-integer linear fractional programming model is solved by tailored optimization algorithm. County level cases in Illinois are analyzed and compared to show the advantage of the proposed optimization framework. The results show that the preconversion to petroleum-upgrading pathway is more economical when applying the unit cost objective.     

Design under uncertainty of hydrocarbon biorefinery supply chains: Multiobjective stochastic programming models,decomposition algorithm,and a Comparison between CVaR and downside risk

A bicriterion, multiperiod, stochastic mixed‐integer linear programming model to address the optimal design of hydrocarbon biorefinery supply chains under supply and demand uncertainties is presented. The model accounts for multiple conversion technologies, feedstock seasonality and fluctuation, geographical diversity, biomass degradation, demand variation, government incentives, and risk management. The objective is simultaneous minimization of the expected annualized cost and the financial risk. The latter criterion is measured by conditional value‐at‐risk and downside risk. The model simultaneously determines the optimal network design, technology selection, capital investment, production planning, and logistics management decisions. Multicut L‐shaped method is implemented to circumvent the computational burden of solving large scale problems. The proposed modeling framework and algorithm are illustrated through four case studies of hydrocarbon biorefinery supply chain for the State of Illinois. Comparisons between the deterministic and stochastic solutions, the different risk metrics, and two decomposition methods are discussed. The computational results show the effectiveness of the proposed strategy for optimal design of hydrocarbon biorefinery supply chain under the presence of uncertainties. © 2012 American Institute of Chemical Engineers AIChE J, 2012     

多期生物燃料供应链网络建模与多目标优化

建立了一个基于多目标优化以及生命周期评价（LCA）的多期生物燃料供应链模型。该模型的3个目标函数分别为总折现利润、平均单位能量生物燃料的温室气体排放和化石能源投入（economic,energy,environmental,3E）。为了将生物质生产的季节性以及库存等问题引入模型中,需要对每年进行多期划分。考虑到需要进一步引入供应链的扩张,模型的时间跨度设定为3年。此外,该模型还考虑了生物质产地、工厂,生物燃料市场的选址以及各节点间的物流流量等问题。通过将非线性的后两个目标函数利用ε-constraint法转化为线性约束条件,该模型最终被转化为混合整数线性规划（MILP）问题并得以求解。对解得的非劣解在三维坐标系上线性插值可得非劣解所在曲面,它揭示了3E目标之间的权衡取舍关系。还使用了一个基于中国国情的数据的案例对该模型进行检验。     

Optimal planning for the reuse of municipal solid waste considering economic,environmental, and safety objectives

A mathematical programming model is presente for the optimal planning of the reuse of municipal solid waste (MSW) to maximize the economic benefit while simultaneously considering sustainability and safety criteria. The proposed methodology considers several phases of the supply chain including waste separation, distribution to processing facilities, processing to obtain useful products, and distribution of products to consumers. Additionally, the safety criteria are based on the potential fatalities associated with waste management. The proposed optimization model is formulated as a multiobjective optimization problem, which considers three different objectives including the maximization of the net annual profit, the maximization of the amount of reused MSW, and the minimization of the social risk associated with the supply chain. The proposed model is applied to a case study in the central‐west region of Mexico. The results show the tradeoff between the social risk and the economic and environmental criteria. © 2015 American Institute of Chemical Engineers AIChE J, 61: 1881–1899, 2015     

Nationwide energy supply chain analysis for hybrid feedstock processes with significant CO2 emissions reduction

Integrating diverse energy sources to produce cost‐competitive fuels requires efficient resource management. An optimization framework is proposed for a nationwide energy supply chain network using hybrid coal, biomass, and natural gas to liquids (CBGTL) facilities, which are individually optimized with simultaneous heat, power, and water integration using 162 distinct combinations of feedstock types, capacities, and carbon conversion levels. The model integrates the upstream and downstream operations of the facilities, incorporating the delivery of feedstocks, fuel products, electricity supply, water, and CO₂ sequestration, with their geographical distributions. Quantitative economic trade‐offs are established between supply chain configurations that (a) replace petroleum‐based fuels by 100%, 75%, and 50% and (b) utilize the current energy infrastructures. Results suggest that cost‐competitive fuels for the US transportation sector can be produced using domestically available coal, natural gas, and sustainably harvested biomass via an optimal network of CBGTL plants with significant GHG emissions reduction from petroleum‐based processes. © 2012 American Institute of Chemical Engineers AIChE J, 2012     

A LCA Based Biofuel Supply Chain Analysis Framework

This paper presents a life cycle assessment （LCA） based biofuel supply chain （SC） analysis framework which enables the study of economic, energy and environmental （3E） performances by using multi-objective opti-mization. The economic objective is measured by the total annual profit, the energy objective is measured by the average fossil energy （FE） inputs per MJ biofuel and the environmental objective is measured by greenhouse gas （GHG） emissions per MJ biofuel. A multi-objective linear fractional programming （MOLFP） model with multi-conversion pathways is formulated based on the framework and is solved by using theε-constraint method. The MOLFP prob-lem is turned into a mixed integer linear programming （MILP） problem by setting up the total annual profit as the optimization objective and the average FE inputs per MJ biofuel and GHG emissions per MJ biofuel as constraints. In the case study, this model is used to design an experimental biofuel supply chain in China. A set of the weekly Pareto optimal solutions is obtained. Each non-inferior solution indicates the optimal locations and the amount of biomass produced, locations and capacities of conversion factories, locations and amount of biofuel being supplied in final markets and the flow of mass through the supply chain network （SCN）. As the model reveals trade-offs among 3E criteria, we think the framework can be a good support tool of decision for the design of biofuel SC.     

Risk management for a global supply chain planning under uncertainty: Models and algorithms

In this article, we consider the risk management for mid‐term planning of a global multi‐product chemical supply chain under demand and freight rate uncertainty. A two‐stage stochastic linear programming approach is proposed within a multi‐period planning model that takes into account the production and inventory levels, transportation modes, times of shipments, and customer service levels. To investigate the potential improvement by using stochastic programming, we describe a simulation framework that relies on a rolling horizon approach. The studies suggest that at least 5% savings in the total real cost can be achieved compared with the deterministic case. In addition, an algorithm based on the multi‐cut L‐shaped method is proposed to effectively solve the resulting large scale industrial size problems. We also introduce risk management models by incorporating risk measures into the stochastic programming model, and multi‐objective optimization schemes are implemented to establish the tradeoffs between cost and risk. To demonstrate the effectiveness of the proposed stochastic models and decomposition algorithms, a case study of a realistic global chemical supply chain problem is presented. © 2009 American Institute of Chemical Engineers AIChE J, 2009     

Balancing responsiveness and economics in process supply chain design with multi‐echelon stochastic inventory

This article is concerned with the optimal design of multi‐echelon process supply chains (PSCs) under economic and responsive criteria with considerations of inventory management and demand uncertainty. The multi‐echelon inventory systems are modeled with the guaranteed service approach to handle the uncertain demands at each echelon. The maximum guaranteed service time of the last echelon of the PSC is proposed as a measure of a PSC's responsiveness. The problem is formulated as a bi‐criterion mixed‐integer nonlinear program (MINLP) with the objectives of minimizing the annualized cost (economic objective) and minimizing the maximum guaranteed service times of the markets (responsiveness objective). The model simultaneously predicts the optimal network structure, transportation amounts, and inventory levels under different specifications of the PSC responsiveness. An example on acetic acid supply chain is presented to illustrate the application of the proposed model and to comprehensively compare different measures of PSC responsiveness. © 2010 American Institute of Chemical Engineers AIChE J, 2011     

Supply chain risk identification using a HAZOP‐based approach

Risk management has become imperative for today's complex supply chains. Most approaches reported in the literature have been ad‐hoc and specific to certain risks; a general and comprehensive approach is lacking. To address this, we present a structured methodology for risk identification. Supply chain networks are in many ways similar to chemical plants, therefore well‐established methods and concepts from chemical process risk management can be adapted to supply chains. Drawing from this analogy, we propose to represent supply chain structure and operations using flow and work‐flow diagrams, equivalent to process flow diagrams (PFDs) and operating procedures. Following the HAZard and OPerability (HAZOP) analysis method common in process safety, risk identification can be performed by systematically generating deviations in different supply chain parameters and identifying their possible causes, consequences, safeguards, and mitigating actions. The application and benefits of the proposed approach are demonstrated using a refinery supply chain case study. © 2009 American Institute of Chemical Engineers AIChE J, 2009