Integration of real options into short-term mine planning and production scheduling

Commodity prices have fallen sharply due to the global financial crisis. This has adversely affected the viability of some mining projects, including leading to the possibility of bankruptcy for some companies. These price falls reflect uncertainties and risks associated with mining projects. In recent years, much work has been published related to the application of real options pricing theory to value life-of-mine plans in response to long term financial uncertainty and risk. However, there are uncertainties and risks associated with medium/short-term mining operations. Real options theory can also be applied to tactical decisions involving uncertainties and risks. This paper will investigate the application of real options in the mining industry and present a methodology developed at University of Queensland, Australia, for integrating real options into medium/short-term mine planning and production scheduling. A case study will demonstrate the validity and usefulness of the methodology and techniques developed.

Improving performance of open-pit mine production scheduling problem under grade uncertainty by hybrid algorithms

One of the surface mining methods is open-pit mining,by which a pit is dug to extract ore or waste downwards from the earth’s surface.In the mining industry,one of the most significant difficulties is long-term production scheduling(LTPS)of the open-pit mines.Deterministic and uncertainty-based approaches are identified as the main strategies,which have been widely used to cope with this problem.Within the last few years,many researchers have highly considered a new computational type,which is less costly,i.e.,meta-heuristic methods,so as to solve the mine design and production scheduling problem.Although the optimality of the final solution cannot be guaranteed,they are able to produce sufficiently good solutions with relatively less computational costs.In the present paper,two hybrid models between augmented Lagrangian relaxation(ALR)and a particle swarm optimization(PSO)and ALR and bat algorithm(BA)are suggested so that the LTPS problem is solved under the condition of grade uncertainty.It is suggested to carry out the ALR method on the LTPS problem to improve its performance and accelerate the convergence.Moreover,the Lagrangian coefficients are updated by using PSO and BA.The presented models have been compared with the outcomes of the ALR-genetic algorithm,the ALR-traditional sub-gradient method,and the conventional method without using the Lagrangian approach.The results indicated that the ALR is considered a more efficient approach which can solve a large-scale problem and make a valid solution.Hence,it is more effectual than the conventional method.Furthermore,the time and cost of computation are diminished by the proposed hybrid strategies.The CPU time using the ALR-BA method is about 7.4%higher than the ALR-PSO approach.

Optimization based scheduling for a class of production systems with integral constraints

Operation scheduling for a class of production systems with"instantly consumed"products is very important.It is challenging to satisfy the real time system demand and to consider the realizability of the production schedules.This paper formulates a new model for optimization based production scheduling problems with integral constraints.Based on the detailed analysis of the production rate constraints,it is proved that this type of optimization problems is equivalent to a smooth nonlinear programming problem.The reachable upper and lower bounds of the production amount in every period can be expressed as functions of two variables,i.e.,the production rate at the start and end of that period.It is also proved that the gradients of these functions are monotonic,and their convexity or concavity is guaranteed.When the production cost function is convex,this type of optimization problems is equivalent to a convex programming problem.With the above analysis,a two-stage solution method is developed to solve the production scheduling problems with integral constraints,and in many applications the global optimal solution can be obtained efficiently.With the new model and solution method,the difficulties caused by the constraints on production rate can be overcome and the optimal schedule can be obtained with the real time system demand satisfied.Numerical testing for scheduling of electric power production systems is performed and the testing results are discussed.It is demonstrated that the new model and solution method are effective.

A linear programming model for long-term mine planning in the presence of grade uncertainty and a stockpile

The complexity of an open pit production scheduling problem is increased by grade uncertainty. A method is presented to calculate the cost of uncertainty in a production schedule based on deviations from the target production. A mixed integer linear programming algorithm is formulated to find the min- ing sequence of blocks from a predefined pit shell and their respective destinations, with two objectives： to maximize the net present value of the operation and to minimize the cost of uncertainty. An efficient clustering technique reduces the number of var/ables to make the problem tractable. Also, the parameters that control the importance of uncertainty in the optimization problem are studied. The minimum annual mining capacity in presence of grade uncertainty is assessed. The method is illustrated with an oil sand deposit in northern Alberta.

Approximate Approach to Deal with the Uncertainty in Integra ted Production Scheduling and Maintenance Planning

This paper deals with the integration problem between production scheduling and maintenance planning in a single machine,where the impact of failure uncertainty is considered.The objective is to minimize the weighted sum of quality robustness and solution robustness,which is determined by the jobs1 sequence,preventive maintenances,position and buffer time in the schedule.Then,a three-stage algorithm is devised to solve the problem,where the gradient descent algorithm based on an effective surrogate measure is developed in the second st age.The numerical experiments show that the deviation of the approximate approach is very small,as compared with the exact solution obtained by CPLEX.The balance between quality robustness and solution robustness and the distribution of buffer time in different scenarios are shown in a case study.It validates the necessity and effectiveness of the consideration of robustness in the industrial practice.

考虑太阳能辅助碳捕集技术的综合能源生产单元随机低碳调度策略

为解决综合能源生产单元(integrated energy production unit,IEPU)中燃煤机组碳捕集过程的高能耗问题,同时应对新能源不确定性对运行调度带来的挑战,该文提出一种考虑太阳能辅助碳捕集技术的IEPU随机低碳调度策略,旨在实现IEPU的多能协同与低碳运行。首先,对含太阳能辅助碳捕集热电联产单元(combined heat and power based on solar-assisted carbon capture,CHP-SACC)的能量流动与运行机理进行分析,并构建其运行模型;其次,考虑风电不确定性带来的影响,提出一种基于条件最小二乘生成对抗网络(conditional-least squares generative adversarial networks,C-LSGANs)的可再生能源场景生成方法来提高场景的生成质量;然后,考虑异质能流耦合约束、多元设备运行约束以及能量平衡约束等,以最大化系统运行收益期望为目标构建IEPU随机低碳调度模型;最后,在算例仿真中设置不同的运行策略验证所提低碳转型方案的有效性,并分析了能源价格、设备容量等因素对系统运行收益的影响。

都江堰灌区水生态产品价值实现历史演进与对策建议

灌区是水生态产品的直接提供者之一,全面支撑水生态产品价值实现是灌区高质量发展的使命和任务。通过回顾和总结都江堰灌区水生态产品价值实现的历史演进特点,分析了目前存在的问题,建议从系统规划、水权水价改革、加强科技创新和数字孪生灌区建设等方面不断拓展水生态产品价值实现的广度和深度,充分融合千年古堰造福于民的价值追求,实现水生态产品价值的“帕累托最优”。

混合三维分布估计算法求解分布式加工装配和车辆配送集成调度问题

本文针对一类广泛存在的分布式加工装配和车辆配送集成调度问题(Integrated Scheduling Problem of Distributed Production Assembly and Vehicle Delivery,ISP_DPAVD),以最小化运输和延迟惩罚总成本为优化目标,提出一种混合三维分布估计算法(Hybrid three-Dimensional Estimation of Distribution Algorithm,H3DEDA)进行求解.ISP_DPAVD包含两个耦合的子问题,即加工装配阶段子问题(子问题1)和车辆配送阶段子问题(子问题2).由于每个子问题1的解(部分解1)均会确定1个具体的子问题2,故ISP_DPAVD的解空间非常庞大.根据这一特点,在H3DEDA中,先设计结合邻域变换的启发式规则来快速获取子问题2的优良解,以实现子问题间的部分解耦并明显缩减搜索空间,再设计三维EDA引导的全局搜索和变邻域驱动的局部搜索来获取ISP_DPAVD的高质量解.通过在不同规模测试问题上的仿真实验和算法比较,验证了H3DEDA求解ISP_DPAVD的有效性.

基于低碳需求响应的含煤制氢与碳捕集电厂的综合能源系统优化调度

为了提高综合能源系统的低碳性与经济性,提出了煤制氢与碳捕集电厂联合运行模式下考虑低碳需求响应机制的综合能源系统优化调度。对煤制氢与富氧燃烧类型碳捕集电厂进行建模,并引入储碳罐、电转气装置以提高捕碳灵活性,降低制氧、制氢成本;将低碳需求响应机制引入综合能源系统调度模型中,并分析其减排能力;以运行成本最小为目标函数建立了综合能源系统的低碳经济调度模型。通过算例对所提策略进行验证,结果表明该策略能够提高风电消纳水平,降低整体系统的碳排放量,提升系统经济性。

A maintenance driven scheduling cockpit for integrated production and maintenance operation schedule

The production and maintenance functions have objectives that are often in contrast and it is essential for management to ensure that their activities are carried out synergistically,to ensure the maximum efficiency of the production plant as well as the minimization of management costs.The current evolution of ICT technologies and maintenance strategies in the industrial field is making possible a greater integration between production and maintenance.This work addresses this challenge by combining theknowledge of the data collected from physical assets for predictive maintenance management with the possibility of dynamic simulate the future behaviour of the manufacturing system through a digital twin for optimal management of maintenance interventions.The paper,indeed,presents a supporting digital cockpit for production and maintenance integrated scheduling.Thetool proposes an innovative approach to manage health data from machines being in any production system and provides support to compare the information about their remaining useful life(RUL)with the respective production schedule.The maintenancedriven schedulingcockpit(MDSC)offers,indeed,a supporting decision tool for the maintenance strategy to be implemented that can help production and maintenance managers in the optimal scheduling of preventive maintenance interventions based on RUL estimation.The simulation is performed by varying the production schedule with the maintenance tasks involvement;opportune decisions are taken evaluating the total costs related to the simulated strategy and the impact on the production schedule.

北京地铁智慧车辆段方案研究

地铁车辆段是地铁列车的停放、日常保养、检修基地,同时还具备车辆救援、办公综合、材料供应等重要功能。当地铁列车结束运营或出现特殊状况时,都会返回车辆段进行“体检”或“治疗”,为安全运营做充分准备。随着北京地铁的高速发展,为应对不断增长的列车数量和客流量,车辆段的运维检修、调度运行、生产管控压力持续增大。本文在分析传统地铁车辆段运营现状的基础上,介绍了地铁智慧车辆段的定义与业务功能。结合北京地铁智慧车辆段建设需求,以车辆运维和设备维护为核心,开展北京地铁智慧车辆段方案的顶层需求分析,研究面向生产调度、检修维护和综合管控的车辆段智慧化提升技术,在保证车辆段安全稳定运营的前提下,提出了涵盖调度运行智能化、运维检修信息化、综合管控数字化的智慧车辆段方案,既能降低运维成本能提高运维管理效率,建立可推广、可复制的车辆段建设管理模式,可促进运维水平持续提升,助力“智慧城轨”建设再上新台阶。

碳交易机制下绿氢蓝氢协调优化对综合能源系统的影响评估

能源结构低碳转型下,针对绿氢蓝氢协同利用下综合效益不明确的问题,提出一种绿氢蓝氢对综合能源系统影响综合评估方法。首先基于电制绿氢、气制蓝氢、掺氢燃机和储氢罐等设备构建绿氢蓝氢综合能源系统结构,进而在碳交易机制下,建立以碳交易成本、风电运行及弃风惩罚成本、购能成本和蓝氢提纯成本之和最小为优化目标的低碳经济调度模型;其次基于调度结果,从经济性、设备寿命损耗和节能环保性3个方面充分挖掘评价指标,构建综合评估指标体系,并利用基于AHP-熵-独立性权法的综合赋权法计算指标权重以增强赋权结果的合理性,进而计算出综合评价值。算例结果验证了所提综合评价方法的合理性,同时也表明绿氢蓝氢协同使综合能源系统具有较高的综合效益。

数字孪生三峡建设与展望

作为水利部数字孪生工程建设的先行先试对象之一,数字孪生三峡建设取得了显著成效。通过水利信息化基础设施、数字孪生平台及智能业务应用体系整合与建设,建立了物理实体工程与数字孪生工程及其影响河段虚实交互映像,有效提升了长江流域调度和三峡工程综合管理能力。文章阐述了数字孪生三峡的建设目标、总体框架、建设内容及初步成果,分析了数字孪生三峡先行先试建设的特色与亮点,并结合新阶段水利高质量发展的要求,对数字孪生三峡下一步建设提出了展望。

综合能源生产单元参与日前电-气耦合市场分布鲁棒自调度方法

在构建新型电力系统、实现双碳战略目标的背景下,综合能源生产单元(integrated energy production unit,IEPU)可作为传统燃煤发电机组的一种绿色改造方案。以IEPU为研究对象,提出一种数据驱动的IEPU参与日前电-气耦合市场的分布鲁棒自调度方法。首先建立光伏发电的区间不确定性集;其次根据日前电力市场和天然气市场的历史价格数据构建分布鲁棒模糊集;之后以利润最大化为目标建立IEPU参与日前电-气耦合市场分布鲁棒自调度模型;然后基于对偶理论将模型转化为易求解的混合整数线性规划问题;最后案例分析表明与偏保守的鲁棒优化方法相比,采用分布鲁棒优化方法处理价格不确定性可以有效平衡自调度方案的鲁棒性和经济性。

复杂电子装备的批产自动化测试产线构建与应用

文章介绍了复杂电子装备批产集成调试的现状以及存在的问题,针对这些问题提出了构建复杂电子装备批产自动化测试产线的思路。分别从批产管理模式升级、测试工位自动化改造、物料信息化管控、测试数据自动采集等方面展开规划,构建了复杂电子装备的批产自动化测试产线,实现了测试工位集成互联、资源快速调度、数据集中管控、计划管理精细化,该产线在制造企业内应用,推动了批产任务优质高效完成,实现装备年产能翻番。

基于关键链的再制造系统不确定性生产调度方法

针对再制造系统生产调度的不确定性问题,提出一种基于关键链的再制造系统不确定性生产调度方法。基于单代号网络图(Activity-on-node,AON)对再制造系统调度问题进行参数描述,并建立再制造系统生产调度模型,对目标函数和约束条件进行描述。基于关键链理论对模型进行求解,将再制造生产调度问题看作是不确定性的资源受限型项目调度,以平均作业时间求得基准调度;将基准调度作为AON网络图中的资源约束,综合考虑AON网络图中的工序约束和资源约束得出再制造生产调度的关键链;再通过压缩作业时间、设置缓冲区以解决再制造工艺时间的不确定性问题,获得最终的调度方案。将该方法应用到某再制造车间的生产调度实践中,并用Crystal Ball软件对调度结果进行仿真。

钢铁生产动态调度理论研究与工程应用综述

本文以钢铁企业生产为背景 ,为了更进一步研究有效的动态调度方案 ,首先论述了钢铁生产的动态调度问题的种类、特点 .其次 ,从理论与实践应用两方面分析了该领域的研究方法 .具体介绍了基于模型、智能、人机交互方法 .并分析了各种方法间交叉组合的方式 .进而研究工程实现模式 。

基于内分泌激素调节机制的免疫算法的Flowshop调度问题

针对不确定条件下具有零等待的Flowshop调度问题,采用三角模糊数来描述不确定的产品处理时间,在模糊规划理论的基础上建立了相应的调度模型,通过中间值最大隶属度算法,将原来的模糊调度模型转化为单目标的规划模型;并基于内分泌激素调节规律,利用内分泌系统与免疫系统之间密切的双向调节关系,提出了一种新颖的解决此类问题的自适应内分泌免疫调度算法。仿真实例表明,该算法的收敛速度和搜索精度均明显优于改进的免疫算法,表明该算法的有效性和优越性。

不确定环境下生产项目调度研究综述与展望

综述了不确定环境下生产项目调度的研究现状,分析了生产项目调度过程中存在的各种不确定性,阐述了不确定因素的起因与分类、不确定因素的描述方法,详细探讨了不确定环境下生产项目调度方案的求解与优化方法以及项目调度方案的评价指标,最后指出了该领域面临的挑战和有待进一步研究的问题。