冷轧多机组合同优化排产模型及算法(下)

3.2 单机组粗计划合同内调度 传递时间窗只是确定合同钢卷在各机组生产加工的合理时间范围,对于合同钢卷的具体加工顺序没有给出明确的规定.需要从企业生产工艺的约束和生产成本考虑优化合同钢卷加工次序,即完成单机组钢卷的生产调度.     

基于改进遗传算法的热轧批量计划优化模型

针对钢铁企业的热轧批量计划编制问题,考虑了热轧生产工艺规程、同宽板坯连轧长度限制等约束,建立基于不确定旅行商数的多旅行商问题(MTSP)的热轧批量计划数学模型,把轧制单元计划数最小化和紧邻轧制板坯间轧制宽度、厚度、硬度差异而造成的总惩罚值最小化作为优化目标。结合模型的实际情况,采用基于两交换启发式的改进遗传算法对问题进行求解。最后,利用某钢厂的实际生产数据进行计算试验,同时对结合传统遗传算法和改进遗传算法的优化情况进行对比和结果分析,模型的正确性和算法的有效性得到了验证。     

钢卷信息自动识别系统

正专利号:201621247572.0专利类型:实用新型在冷轧生产中,一个平整机组对应几个重卷机组,为确保两道工序间钢卷信息的有效传递,且不需要操作人员到钢卷旁核查和输入数据,发明提供了一种钢卷信息自动识别传递系统。包括二维码生成装置、图像采集装置、信息处理装置。其优点是钢卷信息自动识别传递,杜绝了出错,减少了操作人员进入作业区存在的安全风险。     

基于互信息的混合蚁群算法及其在旅行商问题上的应用

为了提高蚁群算法的求解性能,从医学图像配准算法的思想出发,提出了一种基于互信息相似度的混合蚁群算法.为了表示最优路径和待配准路径之间的互信息熵,在蚁群算法的概率算子中增加了一个新的相似度影响因子,从而可以增加原算法的全局搜索能力,同时可以加速算法在解空间的搜索速度.将该算法应用在旅行商问题上,根据旅行商问题的特定环境,对混合蚁群算法的算式进行了一定程度的化简,使得算法在解决此类问题时,相应的时间复杂度降低.通过实验与多种传统算法进行对比,结果表明该改进算法在求解性能和跳出局部最小解方面都有一定程度的提高.     

冷轧薄板生产车间作业计划及调度系统的研究与实现

根据冷轧薄板产品、工艺机生产组织特点，开发并应用了冷轧薄板生产车间作业计划及调度系统，实现了合同计划、生产计划和在线机组作业计划的生成和优化，并通过基于人工智能和计划动态编辑技术的计划动态调整系统，及时对具体的作业计划进行修改和实时再调度，形成具体到日的机组计‘划。系统投入运行后，效果明显。     

钢铁生产批量计划软件系统

本文实现了一个以钢铁生产为背景的批量计划的软件系统。系统通过采用单旅行商、多旅行商问题，装箱问题，遗传算法等数学模型和算法，对钢铁生产中炼钢－连铸调度计划、热轧板带轧制计划和热轧钢管轧制与切割计划的安排在微机上作了实现。     

板坯热轧批量计划数学模型及求解算法

根据热轧工艺特点将板坯热轧批量计划编制问题归结为不确定旅行商数的多旅行商问题,建立了以生产成本最小化和产品质量最优化为主次目标且考虑加热区段能耗的生产调度数学模型,并采用遗传算法和禁忌搜索相结合的混合算法进行求解.基于实际生产数据的计算结果表明:该模型充分满足了现场热轧批量计划编制的需求,在轧制单元数最优的基础上,缩短了传搁时间,提高了热送热装率,优化了产品质量.与人机结合方式相比,本文模型的计算结果体现了更好的高产和节能效果.      

冷轧生产线的批量计划与调度方法

从冷轧生产过程抽象出多级多品种连续生产线的批量计划问题,要求保证所有机组连续生产,并在计划时段上满足客户订单的数量要求和中间库容量限制,通过确定各种工艺路线在相关机组上的生产批量的顺序和数量,实现生产费用和库存费用最低的目标。针对该问题建立了数学模型并开发出两阶段算法用于求解,算法首先以符合工艺和管理需要的优先规则对客户订单进行所有机组的产能分配,然后进行机组上的批量调度。最后通过数值计算验证了算法的效率和有效性。     

钢铁冷轧多机组排产算法设计

针对钢铁冷轧生产,以柔性车间调度问题(flexible job-shop scheduling problem,简称FJSP)为基础,总结出一个冷轧多机组排产问题,并提出一种通用高效的多机组排产算法。该算法主要由启发式的初始化、邻域搜索与跳跃搜索模块组成,各模块可根据具体约束条件,灵活配置相应的启发式算子。实验结果表明,该算法相对于传统的变邻域搜索能找到更优的解,且在数据规模增大时保持很快的求解速度,具有高灵活度、高效率的优点。该算法已在某钢铁企业冷轧产线成功上线,取得了良好的效果。     

连铸与热轧工序余材集成匹配模型与算法

针对钢铁企业连铸工序余材板坯及热轧工序余材钢卷对热轧生产合同的匹配问题,基于一体化的管理思想建立了余材板坯、钢卷与合同集成匹配的多目标0-1非线性整数规划模型,在模型中引入板坯材质与合同要求钢种特征差异值矩阵及钢卷钢种与合同要求钢种特征差异值矩阵.采用分段整数编码、基于启发式修复策略的改进遗传算法求解.最后,通过对实际生产数据的仿真实验验证了所提模型和算法的有效性,为科学合理地匹配铸轧工序余材板坯、钢卷提供了有效的解决方法.      

飞机移动生产线物料配送与线边存储集成优化

为了解决飞机移动生产线中多并行作业物料的供给问题,构建了飞机移动生产线物料配送与线边存储集成决策的模型并设计了求解算法.在物料组批和小车调度的基础上,引入了物料在线边空间的存储决策,建立了以小车出行趟数最小化为目标的数学模型并设计了一种以免疫算法为框架的启发式算法.在免疫算法较优的全局搜索能力下,综合考虑小车的配送能力与线边空间的重复使用、共享等因素,使用反向动态小车调度算法和物料存储前瞻算法对物料的组批方式、配送时刻和在线边的存放位置三类变量联合进行决策.对提出的算法进行了数值实验,实验结果证明了模型与算法的有效性.      

多目标多约束混合流水车间插单重调度问题研究

研究了多目标多阶段混合流水车间的紧急订单插单重调度问题，综合考虑工件批量、刀具换装时间、运输能力等约束。先以最小化订单完工时间和最小化总运输时间为双目标建立静态初始订单调度模型，再针对紧急订单插单干扰，增加最小化总加工机器偏差值目标，建立三目标重调度优化模型，并分别用NSGA-II算法与融合基于事件驱动的重调度策略和重排插单策略的NSGA-III算法对两个模型进行求解。最后，以某实际船用管类零件生产企业为案例，先对NSGA-II算法和NSGA-III算法的性能进行评估，得到NSGA-II算法更适用于解决双目标优化问题而NSGA-III算法在解决三目标优化问题时表现更优的结论，再将所建模型与所提算法应用于该企业的十组插单案例中，所得优化率接近三分之一，验证了实用性和有效性。      

Scheduling∕Cost Optimization and Neural Dynamics Model for Construction

A general mathematical formulation is presented for the scheduling of construction projects and is applied to the problem of highway construction scheduling. Repetitive and nonrepetitive tasks, work continuity constraints, multiple-crew strategies, and the effects of varying job conditions on the performance of a crew can be modeled. An optimization formulation is presented for the construction project scheduling problem, with the goal of minimizing the direct construction cost. The nonlinear optimization is then solved by the neural dynamics model developed recently by Adeli and Park. For any given construction duration, the model yields the optimum construction schedule for minimum construction cost automatically. By varying the construction duration, one can solve the cost-duration trade-off problem and obtain the global optimum schedule and the corresponding minimum construction cost. The new construction scheduling model provides the capabilities of both the critical path method (CPM) and linear scheduling method (LSM) approaches. In addition, it provides features desirable for repetitive projects, such as highway construction, and allows schedulers greater flexibility. It is particularly suitable for studying the effects of change order on the construction cost. This research provides the mathematical foundation for development of a new generation of more general, flexible, and accurate construction scheduling systems.     

Optimizing Resource Utilization for Repetitive Construction Projects

Optimizing resource utilization can lead to significant reduction in the duration and cost of repetitive construction projects such as highways, high-rise buildings, and housing projects. This can be achieved by identifying an optimum crew size and interruption strategy for each activity in the project. Available dynamic programming formulations can be applied to provide solutions for this optimization problem; however, their application is limited, as they require planners to specify an arbitrary and an unbounded set of interruption options prior to scheduling. Such a requirement is not practical and may render the optimization problem infeasible. To circumvent the limitations of available formulations, this paper presents an automated and practical optimization model. The model utilizes dynamic programming formulation and incorporates a scheduling algorithm and an interruption algorithm so as to automate the generation of interruptions during scheduling. This transforms the consideration of interruption options, in optimizing resource utilization, from an unbounded and impractical problem to a bounded and feasible one. A numerical example from the literature is analyzed to illustrate the use and capabilities of the model.     

基于粒子群优化算法和博弈论的网络学习控制系统带宽调度

研究了双层网络学习控制系统的带宽调度优化问题.为了合理分配子系统的带宽,引入了网络定价体系和动态带宽调度方法,建立了非合作博弈模型,从而将网络控制系统的网络资源分配问题转换为非合作博弈竞争模型下的Nash均衡点求解问题.在此基础上,采用粒子群优化算法得到此框架下的纳什均衡解,并进一步给出了网络控制系统的时间片调度方法.仿真结果表明了所提方法的有效性.      

钢坯热轧加热炉区生产调度模型与算法

钢坯热轧加热炉区生产调度属于组合优化中的NP-complete问题.本文根据加热炉区生产特点建立了分别以生产能耗最小化和加热质量最优化为主次目标的钢坯加热炉区调度数学模型,将其归结为布尔可满足性问题,构造了采用二进制编码方式的遗传禁忌搜索算法进行求解.基于实际生产数据的模拟优化结果表明,该模型和求解方法充分满足了现场加热炉区生产调度的需求,在满足生产工艺约束的前提下,缩短了生产时间,提高了钢坯入炉温度和加热质量,与传统人工调度方法的结果相比具有更好的节能、高产效果.      

OO Information Model for Construction Project Management

Recently, the writers developed a general and powerful mathematical model for scheduling construction projects. An optimization formulation was presented with the goal of minimizing the direct construction cost. The nonlinear optimization problem was solved by the recently patented neural dynamics model of Adeli and Park. In this paper an object-oriented (OO) information model is presented for construction scheduling, cost optimization, and change order management (CONSCOM) based on the new construction scheduling model. The goal is to lay the foundation for a new generation of flexible, powerful, maintainable, and reusable software system for the solution of construction scheduling problems. The model is presented as a domain-specific development framework using the Microsoft Foundation Class library and utilizing the software reuse feature of the framework. The framework reuse architecture is more flexible and powerful than other reuse techniques such as components and patterns. A companion paper presents the implementation of the OO information model in a prototype software system for management of construction projects, called CONSCOM.     

Improvement Algorithm for Limited Space Scheduling

Selecting construction methods, scheduling activities, and planning the use of site space are key to constructing a project efficiently. Site layout and activity scheduling have been tackled as independent problems. Their interdependence is often ignored at the planning stage and may be dealt with—if at all—when construction is underway. Problems that may have had easy solutions if dealt with earlier, may then be expensive to remedy. This paper addresses the combined problem termed “space scheduling” and presents an algorithmic time-space trade-off model for adjusting activity durations and start dates to decrease the need for space over congested time periods. The model characterizes resource space requirements over time and establishes a time-space relationship for each activity in the schedule, based on alternative resource levels. An example illustrates the presented algorithm that generates a feasible space schedule.     

Irrigation Scheduling. I: Integer Programming Approach

This paper shows how a sequential irrigation schedule for a tertiary unit can be interpreted as a single machine scheduling problem with earliness, tardiness, and a common deadline. An integer program solution is presented for this irrigation scheduling problem. Two different models are presented to reflect different management options at the tertiary level. The first model allows jobs to be scheduled noncontiguously. In the second model only contiguous jobs are allowed. The second model has three submodels reflecting the various ways in which contiguous jobs can be scheduled over a fixed interval. Earlier work in determining unit costs of earliness/tardiness is reviewed and an alternative improved method is suggested. The models presented in this paper are applied to a tertiary unit with 16 users, both as a single interval and multi-interval irrigation scheduling problem. An alternative integer program is also presented which although computationally more efficient can only be used for single period scheduling problems. The models developed in this paper can be used to solve small scheduling problems and also to calibrate the heuristics as presented in the companion paper.