Fair profit allocation in supply chain optimization with transfer price and revenue sharing: MINLP model and algorithm for cellulosic biofuel supply chains

A mixed‐integer nonlinear programming (MINLP) formulation to simultaneously optimize operational decisions as well as profit allocation mechanisms in supply chain optimization, namely material transfer prices and revenue share policies among the supply chain participants is proposed. The case of cellulosic bioethanol supply chains is specifically considered and the game‐theory Nash bargaining solution approach is employed to achieve fair allocation of profit among the collection facilities, biorefineries, and distribution centers. The structural advantages of certain supply chain participants can be taken into account by specifying different values of the negotiation‐power indicators in the generalized Nash‐type objective function. A solution strategy based on a logarithm transformation and a branch‐and‐refine algorithm for efficient global optimization of the resulting nonconvex MINLP problem is proposed. To demonstrate the application of the proposed framework, an illustrative example and a state‐wide county‐level case study on the optimization of a potential cellulosic bioethanol supply chain in Illinois are presented. © 2014 American Institute of Chemical Engineers AIChE J, 60: 3211–3229, 2014     

Integrated gasoline blending and order delivery operations: Part I. short‐term scheduling and global optimization for single and multi‐period operations

Gasoline is one of the most valuable products in an oil refinery and can account for as much as 60–70% of total profit. Optimal integrated scheduling of gasoline blending and order delivery operations can significantly increase profit by avoiding ship demurrage, improving customer satisfaction, minimizing quality give‐aways, reducing costly transitions and slop generation, exploiting low‐quality cuts, and reducing inventory costs. In this article, we first introduce a new unit‐specific event‐based continuous‐time formulation for the integrated treatment of recipes, blending, and scheduling of gasoline blending and order delivery operations. Many operational features are included such as nonidentical parallel blenders, constant blending rate, minimum blend length and amount, blender transition times, multipurpose product tanks, changeovers, and piecewise constant profiles for blend component qualities and feed rates. To address the nonconvexities arising from forcing constant blending rates during a run, we propose a hybrid global optimization approach incorporating a schedule adjustment procedure, iteratively via a mixed‐integer programming and nonlinear programming scheme, and a rigorous deterministic global optimization approach. The computational results demonstrate that our proposed formulation does improve the mixed‐integer linear programming relaxation of Li and Karimi, Ind. Eng. Chem. Res., 2011, 50, 9156–9174. All examples are solved to be 1%‐global optimality with modest computational effort. © 2016 American Institute of Chemical Engineers AIChE J, 62: 2043–2070, 2016     

A new approach for global optimization of a class of MINLP problems with applications to water management and pooling problems

One of the biggest challenges in solving optimization engineering problems is rooted in the nonlinearities and nonconvexities, which arise from bilinear terms corresponding to component material balances and/or concave functions used to estimate capital cost of equipments. The procedure proposed uses an MILP lower bound constructed using partitioning of certain variables, similar to the one used by other approaches. The core of the method is to bound contract a set of variables that are not necessarily the ones being partitioned. The procedure for bound contraction consists of a novel interval elimination procedure that has several variants. Once bound contraction is exhausted the method increases the number of intervals or resorts to a branch and bound strategy where bound contraction takes place at each node. The procedure is illustrated with examples of water management and pooling problems. © 2011 American Institute of Chemical Engineers AIChE J, 58: 2320–2335, 2012     

铁选矿厂水系统优化设计探讨

铁选矿厂属于高水耗行业,对水系统进行优化设计,不仅可以提高水资源重复利用率、降低水耗成本,而且可以减轻对环境的污染。介绍了选矿各生产单元的用水水质要求,根据用水水质对给水系统进行了划分,并探讨了选矿厂节水措施。     

某煤制烯烃项目给排水系统分析与优化

针对某已建煤制烯烃项目给排水系统的设计及运行情况进行调研分析,分析结果显示该项目给水系统设计基本符合"分级供水、分质供水"的原则,排水系统设计基本符合"清污分流、污污分流"的原则。同时针对存在的"少量高压生产水用户提高了整个生产给水系统压力"及"工艺装置内部分高浓度污水混入低浓度污水和污染雨水系统,对污水处理场运行产生冲击"等问题,提出了"少量高压生产水单独设置加压泵"和"装置内部分高浓度污水进一步分流和预处理"等优化建议。     

Novel bound contraction procedure for global optimization of bilinear MINLP problems with applications to water management problems

We propose a new method to obtain the global optimum of MINLP problems containing bilinearities. Our special method that contracts the bounds of one variable at a time allows reducing the gap between a linear lower bound and an upper bound obtained solving the original problem. Unlike some methods based on variable partitioning, our bound contraction procedure does not introduce new integers or intervals. We illustrate the method by applying it to water management problems.     

Multiobjective optimization of product and process networks: General modeling framework,efficient global optimization algorithm,and case studies on bioconversion

A comprehensive optimization model that can determine the most cost‐effective and environmentally sustainable production pathways in an integrated processing network is needed, especially in the bioconversion space. We develop the most comprehensive bioconversion network to date with 193 technologies and 129 materials/compounds for fuels production. We consider the tradeoff between scaling capital and operating expenditures (CAPEX and OPEX) as well as life cycle environmental impacts. Additionally, we develop a general network‐based modeling framework with nonconvex terms for CAPEX. To globally optimize the nonlinear program with high computational efficiency, we develop a specialized branch‐and‐refine algorithm based on successive piecewise linear approximations. Two case studies are considered. The optimal pathways have profits from ?$12.9 to $99.2M/yr, and emit 791 ton CO₂‐eq/yr to 31,571 ton CO₂‐eq/yr. Utilized technologies vary from corn‐based fermentation to pyrolysis. The proposed algorithm reduces computational time by up to three orders of magnitude compared to general‐purpose global optimizers. © 2014 American Institute of Chemical Engineers AIChE J, 61: 530–554, 2015     

Continuous‐time modeling and global optimization approach for scheduling of crude oil operations

Scheduling of crude oil operations is a critical and complicated component of overall refinery operations, because crude oil costs account for about 80% of the refinery turnover. Moreover, blending with less expensive crudes can significantly increase profit margins. The mathematical modeling of blending different crudes in storage tanks results in many bilinear terms, which transforms the problem into a challenging, nonconvex, and mixed‐integer nonlinear programming (MINLP) optimization model. Two primary contributions have been made. First, the authors developed a novel unit‐specific event‐based continuous‐time MINLP formulation for this problem. Then they incorporated realistic operational features such as single buoy mooring (SBM), multiple jetties, multiparcel vessels, single‐parcel vessels, crude blending, brine settling, crude segregation, and multiple tanks feeding one crude distillation unit at one time and vice versa. In addition, 15 important volume‐based or weight‐based crude property indices are also considered. Second, they exploited recent advances in piecewise‐linear underestimation of bilinear terms within a branch‐and‐bound algorithm to globally optimize the MINLP problem. It is shown that the continuous‐time model results in substantially fewer bilinear terms. Several examples taken from the work of Li et al. are used to illustrate that (1) better solutions are obtained and (2) ε‐global optimality can be attained using the proposed branch‐and‐bound global optimization algorithm with piecewise‐linear underestimations of the bilinear terms. © 2011 American Institute of Chemical Engineers AIChE J, 2012     

Deciphering and handling uncertainty in shale gas supply chain design and optimization: Novel modeling framework and computationally efficient solution algorithm

The optimal design and operations of shale gas supply chains under uncertainty of estimated ultimate recovery (EUR) is addressed. A two‐stage stochastic mixed‐integer linear fractional programming (SMILFP) model is developed to optimize the levelized cost of energy generated from shale gas. In this model, both design and planning decisions are considered with respect to shale well drilling, shale gas production, processing, multiple end‐uses, and transportation. To reduce the model size and number of scenarios, we apply a sample average approximation method to generate scenarios based on the real‐world EUR data. In addition, a novel solution algorithm integrating the parametric approach and the L‐shaped method is proposed for solving the resulting SMILFP problem within a reasonable computational time. The proposed model and algorithm are illustrated through a case study based on the Marcellus shale play, and a deterministic model is considered for comparison. © 2015 American Institute of Chemical Engineers AIChE J, 61: 3739–3755, 2015     

Scheduling of crude oil operations under demand uncertainty: A robust optimization framework coupled with global optimization

Scheduling of crude oil operations is an important component of overall refinery operations, because crude oil costs account for about 80% of the refinery turnover. The mathematical modeling of blending different crudes in storage tanks results in many bilinear terms, which transform the problem into a challenging, nonconvex, mixed‐integer nonlinear programming (MINLP) optimization model. In practice, uncertainties are unavoidable and include demand fluctuations, ship arrival delays, equipment malfunction, and tank unavailability. In the presence of these uncertainties, an optimal schedule generated using nominal parameter values may often be suboptimal or even become infeasible. In this article, the robust optimization framework proposed by Lin et al. and Janak et al. is extended to develop a deterministic robust counterpart optimization model for demand uncertainty. The recently proposed branch and bound global optimization algorithm with piecewise‐linear underestimation of bilinear terms by Li et al. is also extended to solve the nonconvex MINLP deterministic robust counterpart optimization model and generate robust schedules. Two examples are used to illustrate the capability of the proposed robust optimization approach, and the extended branch and bound global optimization algorithm for demand uncertainty. The computational results demonstrate that the obtained schedules are robust in the presence of demand uncertainty. © 2011 American Institute of Chemical Engineers AIChE J, 58: 2373–2396, 2012     

发电厂锅炉给水系统改造方案设计

针对某发电厂锅炉给水系统存在的再生周期很短，再生剂比耗大，自用水率高等问题，提出了强化自备水厂水处理工艺，同时加设预处理和反渗透装置的技改方案。通过技术经济比较可知，该改造方案技术上合理，经济上可行。     

居住小区管网系统二次给水污染的研究

对西安市部分住宅楼二次供水系统进行分析,对比了4种不同供水方式及不同管材和水力停留时间对用户水质的影响。结果表明,以水箱供水的影响较大,气压给水二次污染较小;室内供水系统中钢塑复合管优于镀锌管;停留时间以不超过6h为宜。针对小区管网系统二次污染状况,提出管网系统二次污染的防治改造对策。     

Optimal supply chain design and operations under multi‐scale uncertainties: Nested stochastic robust optimization modeling framework and solution algorithm

Although strategic and operational uncertainties differ in their significance of impact, a “one‐size‐fits‐all” approach has been typically used to tackle all types of uncertainty in the optimal design and operations of supply chains. In this work, we propose a stochastic robust optimization model that handles multi‐scale uncertainties in a holistic framework, aiming to optimize the expected economic performance while ensuring the robustness of operations. Stochastic programming and robust optimization approaches are integrated in a nested manner to reflect the decision maker's different levels of conservativeness toward strategic and operational uncertainties. The resulting multi‐level mixed‐integer linear programming model is solved by a decomposition‐based column‐and‐constraint generation algorithm. To illustrate the application, a county‐level case study on optimal design and operations of a spatially‐explicit biofuel supply chain in Illinois is presented, which demonstrates the advantages and flexibility of the proposed modeling framework and efficiency of the solution algorithm. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3041–3055, 2016     

OBAJANA#4总承包项目给排水系统分析

全面介绍了尼日利亚OBAJANA 6 000 t/d熟料生产线总承包项目给排水系统的设计特点;重点对项目水源问题、水处理工艺选择、给排水系统划分等进行了方案分析;并对给排水各单体和各个系统的特点及系统的优缺点进行了逐一分析.     

Global optimization of multicomponent distillation configurations: 1. Need for a reliable global optimization algorithm

Nonazeotropic multicomponent mixtures are often separated into products by distillation configurations containing multiple distillation columns. One method of calculating the minimum vapor duty of a configuration is to sequentially calculate the minimum vapor duty of each mixture as it is split into two streams within a given column starting from the feed column. The other method simultaneously manipulates all the splits to yield the overall minimum vapor duty of the entire configuration. Of these two methods, the sequential minimization is attractive as it can be analytically solved. However, through extensive computations, we find that the sequential minimization method is not a valid substitute for the simultaneous minimization method. As the number of components in the feed increases, the fraction of the basic configurations for which sequential method yields a reasonable estimate decreases rapidly, thereby emphasizing the need for a more robust and reliable global optimization algorithm. © 2012 American Institute of Chemical Engineers AIChE J, 59: 971–981, 2013     

Planning and scheduling of flexible process networks under uncertainty with stochastic inventory: MINLP models and algorithm

The tactical planning and scheduling of chemical process networks consisting of both dedicated and flexible processes under demand and supply uncertainty is addressed. To integrate the stochastic inventory control decisions with the production planning and scheduling, a mixed‐integer nonlinear programming (MINLP) model is proposed that captures the stochastic nature of the demand variations and supply delays using the guaranteed‐service approach. The model takes into account multiple tradeoffs and simultaneously determines the optimal selection of production schemes, purchase amounts of raw materials, sales of final products, production levels of processes, detailed cyclic production schedules for flexible processes, and working inventory and safety stock levels of all chemicals involved in the process network. To globally optimize the resulting nonconvex MINLP problems with modest computational times, the model properties are exploited and a tailored branch‐and‐refine algorithm based on the successive piecewise linear approximation is proposed. To handle the degeneracy of alternative optima in assignment configurations of production scheduling, three symmetry breaking cuts are further developed to accelerate the solution process. The application of the model and the performance of the proposed algorithm are illustrated through three examples with up to 25 chemicals and 16 processes including at most 8 production schemes for each flexible process. © 2012 American Institute of Chemical Engineers AIChE J, 59: 1511–1532, 2013     

Optimal design and operations of supply chain networks for water management in shale gas production: MILFP model and algorithms for the water‐energy nexus

The optimal design and operations of water supply chain networks for shale gas production is addressed. A mixed‐integer linear fractional programming (MILFP) model is developed with the objective to maximize profit per unit freshwater consumption, such that both economic performance and water‐use efficiency are optimized. The model simultaneously accounts for the design and operational decisions for freshwater source selection, multiple transportation modes, and water management options. Water management options include disposal, commercial centralized wastewater treatment, and onsite treatment (filtration, lime softening, thermal distillation). To globally optimize the resulting MILFP problem efficiently, three tailored solution algorithms are presented: a parametric approach, a reformulation‐linearization method, and a novel Branch‐and‐Bound and Charnes–Cooper transformation method. The proposed models and algorithms are illustrated through two case studies based on Marcellus shale play, in which onsite treatment shows its superiority in improving freshwater conservancy, maintaining a stable water flow, and reducing transportation burden. © 2014 American Institute of Chemical Engineers AIChE J, 61: 1184–1208, 2015     

交通生命线系统震后应急调度模型及方法

震后交通应急调度是地震救灾工作中的一个重要环节。对震后交通生命线系统的功能进行分析,将震后道路里程、车辆速度、行程延误、交通负荷度以及路网连通可靠度等因素遴选为震后交通生命线系统的交通阻抗效用指标,提出将这些效用指标转化为一种广义交通阻抗即运输时间的理论方法,考虑到震后应急物资调度是基于时间链的动态过程,假设调度至受灾点的物资是被连续消耗的,进而建立震后多需求点多服务点应急调度的双层决策优化数学模型,给出双层规划问题的动态优化算法,得到最优的应急调度连续可行方案。通过一个仿真算例进行了验证。     

供水管网调度系统信息化建设研究

对供水管网集成化的数据采集与监控系统,水力模型和优化调度3个系统的基本功能进行了分析论述,在此基础上,提出了供水管网调度系统信息化建设的整体解决方案,编制了供水调度系统管理软件,软件由数据模块、决策模块、输出模块组成,实现了供水管网的调度系统的自动化控制。该软件已成功地应用于上海、南京等地的城市供水管网系统。     

交流变频调速器在恒压变量供水控制系统中的应用

介绍利用PLC和交流变频器 (VVVF)实现恒压供水的工作原理 ,论述了用 1台变频器控制 3台异步电机的工作过程 ,使系统达到自动跟踪 ,稳定恒压 ,变量供水