一种基于Hopfield模型的流水作业排序方法

根据Hopfield模型求解优化问题的原理,提出了一种用于求解流水作业排序问题的算法。计算和比较结果表明,这种算法在收敛速度和计算准确性方面可获得较好的结果。     

冷轧生产批量计划与调度问题模型及算法

对冷轧生产系统特点进行分析,将冷轧生产批量计划与调度问题抽象为多阶段、多品种带有中间库的批量计划与调度问题。针对该问题建立了数学模型,通过对库存成本和调整成本惩罚系数的控制可以协调库存水平和调整次数的关系。对所建立的模型,提出了基于二进制粒子群优化与局部搜索的混合求解算法。最后,通过对企业实际生产数据的计算和分析,验证了模型和算法的可行性和有效性。     

重复性项目调度模型的时差分析

时差分析作为工程项目管理的核心内容之一,被广泛用于处理延期索赔和工期压缩等实际工程问题。RSM是针对重复性项目而设计的一类新的项目调度工具,在项目计划与调度领域受到广泛关注。在RSM中,目前尚未有普适的时差分析方法,并且已有的时差概念均要求工序必须连续施工。在考虑工序间断的情况下,区分了RSM中子工序使用时差的两种方式,即"调整开始时间"和"延长工期"。通过将CPM网络中的经典时差概念（包括总时差、自由时差和安全时差）与RSM相结合,提出了适用于RSM的新时差概念体系,以及对应的时间参数和时差计算方法。一个管道工程项目验证了算法的有效性。与已有文献相比,本文提出的时差分析方法具有更强的普适性。     

A Cooperative Savings Game Approach to a Time Sensitive Capacity Allocation and Scheduling Problem

We consider a competitive scheduling setting with arbitrary number of agents each having the option to utilize two parallel resources to satisfy its demand: (i) an in‐house resource dedicated to process only the tasks of each specific agent, and (ii) a flexible resource capable of processing all agents' workloads. In a noncooperative setting, each agent would determine how much of its demand it will subcontract to the flexible resource with the objective to deliver its entire demand as quickly as possible subject to the priority rules set by the owner of the flexible resource (i.e., third‐party). In this study, we also allow for agents to coalesce with other agents and update their initial subcontracting decisions to attain rescheduling savings. Evidently, a grand coalition of all agents can coordinate to achieve the maximum savings possible, but the resulting schedule may yield individual losses for a subset of agents (which we refer to as “losers”), thus necessitating a transfer payment scheme to distribute the rescheduling savings among the agents in an equitable way. We model the rescheduling interactions among the agents as a cooperative savings game, and propose savings distribution schemes that invoke the core allocation concept.     

Practical Implications of Preference‐Based Conference Scheduling

Conference scheduling involves organizing presentations into sessions which are assigned to time periods and rooms. This includes assuring a feasible utilization of time periods and rooms, and avoiding individual schedule conflicts. The problem increases in complexity by considering the preferences of presenters: for time periods, for rooms, etc. A greater level of complexity comes from considering the preferences of conference attendees, which we define as preference‐based conference scheduling (PBCS). This article provides a structure on which PBCS problems are founded, including empirical demonstration of solution techniques. In addition, real‐world strategic planning issues of flexibility and preference detail are explored.     

Max-npv项目进度问题研究评述

首先介绍了不受资源约束Max-npv项目进度问题在模型和算法方面的研究进展;随后,根据资源约束类型的不同,对可更新、不可更新及双重资源约束Max-npv项目进度问题的研究成果,特别是优化算法和启发式算法的设计进行了概述;最后,对Max-npv项目进度问题的研究现状进行了总结并指出进一步的研究方向。     

基于两阶段资源分配协调机制的分布式多项目随机调度

企业趋向于多项目共享全局资源的分布式协同管理。但在多项目实际执行时,全局资源可用量往往由于外部环境的动态变化而存在不确定性,活动中断、资源浪费等现象频发,项目管理变得愈加复杂。本文将不确定的全局资源可用量建模为随机变量,设计两阶段资源分配协调机制,在预分配阶段,考虑项目允许的最大活动中断次数约束,建立各项目调度的马尔可夫动态决策过程模型;预分配结束后,基于活动重要度依次对剩余全局资源进行协调再分配,以提高资源利用率并减少平均项目延期。设计基于全局资源协调分配的Rollout近似动态规划算法进行求解。开展问题库算例实验研究与案例分析,验证协调机制与求解算法的性能;同时,探讨并分析不确定参数对目标结果的影响。     

辩证思维在破解现实领导工作难题中的应用

在现实工作中,领导者如果缺乏辩证思维,普遍会面临低效率的领导力危机,具体表现为坠入事务主义的泥潭、落入非此即彼的窠臼、步入盲人摸象的困境、掉入竭泽而渔的陷阱、陷入欲速不达的怪圈。新发展阶段,辩证思维在领导者的思维方式中占据核心地位,是领导者破解现实工作难题的根本之法、创新之法、提升之法。在现实工作中,领导者要自觉把握辩证思维的两点论重点论转化论否定论以及内因论,切实通过理论与实践相结合、科学与文化相结合、真理与价值相结合等路径不断提升辩证思维的能力与破解难题的本领。     

基于VaR的金融资产配置模型

本文根据均值-方差模型的框架,建立了用VaR代替方差或标准差作为风险的测量指标时的均值-VaR模型,同时使用等VaR线分析了两种模型的内在联系。作为模型的扩展本文还分别考虑了存在无风险资产,负债和非正态分布时的情形。此外讨论了均值-VaR模型有效边界的一些性质。     

需求不确定条件下的制造商订单分配模型

制造商的订单分配作为供应链模型微观层面的重要组成部分,对提升整个供应链效率有很大影响,但需求层面的不确定因素加大了订单分配的难度。以按比例分配为原则,讨论在需求不确定条件下完全信息与不完全信息两类多供应商-单制造商的订单分配模型。重点研究完全信息条件下各方的分散决策和集中决策,由于后者能避免各参与方对其他决策方的边际影响,所以能够实现供应链总利润的最大化;其次又将不完全信息引入模型,讨论制造商如何通过折算因子结合已有信息对供应商的私人信息进行估计,进而做出决策。最后以需求服从正态分布为例对两类模型进行验证。     

基于模糊权重的多目标订单分配模型

随着竞争的日益加剧,采购成了影响企业生存和发展的关键因素。在这种情况下,正确的订单分配是成功实行采购的关键。实际上,影响订单分配的许多信息并不是确定的已知条件,例如目标、约束条件和影响权重等。本文通过考虑上述信息的不确定性和模糊性,构建一个包含模糊目标、模糊权重和随机约束的订单分配模型。然后,利用数值算例证明了模型的可解性。最后,指出了未来可能的几个研究方向。     

A Model for Master Production Scheduling in Uncertain Environments

In uncertain environments, the master production schedule (MPS) is usually developed using a rolling schedule. When utilizing a rolling schedule, the MPS is replanned periodically and a portion of the MPS is frozen in each planning cycle. The cost performance of a rolling schedule depends on three decisions: the choice of the replanning interval (R), which determines how often the MPS should be replanned; the choice of the frozen interval (F), which determines how many periods the MPS should be frozen in each planning cycle; and the choice of the forecast window (T), which is the time interval over which the MPS is determined using newly updated forecast data. This paper uses an analytical approach to study the master production scheduling process in uncertain environments without capacity constraints, where the MPS is developed using a rolling schedule. It focuses on the choices of F, R, and T for the MPS. A conceptual framework that includes all important MPS time intervals is described. The effects of F, R, and T on system costs, which include the forecast error, MPS change, setup, and inventory holding costs, are also explored. Finally, a mathematical model for the MPS is presented. This model approximates the average system cost as a function of F, R, T, and several environmental factors. It can be used to estimate the associated system costs for any combination of F, R, and T.     

Modelling Resource Allocation in a Decentralized Organization with an AI-Based,Goal-Directive Model*

Modelling the resource allocation decision process in a decentralized organization using mathematical programming decomposition approaches has proven intractable for all but the smallest of problems. In this paper three artificial intelligence (AI) techniques are integrated to model the resource allocation decision process, and the solution for a three-level decentralized organization is illustrated. The techniques are (1) the filtered beam search, which selects a list of potential projects at the subordinate level, (2) the world model, which describes the ordinate and superordinate's worlds and their decision-making processes, and (3) the blackboard model, which allows for global, but selective, storage of information. Benefits of the new approach include: several different mechanisms of managerial control may be modelled, the true information flow in an organization is more closely mirrored, and problems of a more realistic size are now viable. There are three primary ways in which the new model could be useful to management: The desirability and effects of different organizational structures can be modeled, the efficacy of various coordination mechanisms along the organizational structure can be examined, and a subset of projects from a wider list of possibilities can be selected. Also, an example is given showing how the model may be extended to scenarios with asymetric information and divergence of preferences, whereby subordinates have different objectives than their managers and where there is no way for managers to verify the truthfulness of their subordinates' responses.     

A Hierarchical Production Planning and Scheduling Model

A hierarchical production planning and scheduling system is developed that integrates planning decisions into a unified and consistent framework. A three-tiered approach is used to address long-term inventory control, short-term production planning, and daily scheduling tasks. A product grouping scheme introduces uniformity into the solution process and simplifies overall model complexity. Results of the model implementation are reported.     

混合PSO算法求解混装工艺下的加热炉调度问题

针对钢铁生产中为减轻混装的影响在冷热板坯混装处空炉的情况,以提高成品质量、降低能耗为目标,建立了混装工艺下并行加热炉调度的数学模型,并提出了基于粒子群算法和邻域搜索技术的混合算法,仿真实验验证了算法的可行性和有效性.     

基于现金流均衡目标的多模式项目调度问题研究

首先对基于现金流均衡目标的多模式项目调度问题进行界定;随后定义两组0-1决策变量并构建问题的优化模型;鉴于问题的强NP-hard属性,设计专门的模拟退火启发式算法;最后用一个实例对研究进行说明,并计算分析关键参数对目标函数的影响.结果表明:承包商最大累计资金缺口随项目截止日期的延迟、支付比例和预付款比例的提高而减小,随着质量保证金比例的提高而增大.     

A Framework for the Complexity of High-Multiplicity Scheduling Problems

The purpose of this note is to propose a complexity framework for the analysis of high multiplicity scheduling problems. Part of this framework relies on earlier work aiming at the definition of output-sensitive complexity measures for the analysis of algorithms which produce “large” outputs. However, different classes emerge according as we look at schedules as sets of starting times, or as related single-valued mappings.     

基于峰值负荷的签派员席位任务分配问题

本文研究的问题来源于航空公司运行控制中心的签派部门,签派员在放行航班时,既要保证航班的正点起飞,又要调节放行航班的工作劳动强度保证放行的质量,使航班在安全状态下运行。这里放行航班的工作劳动强度为单位时间内的工作时间,峰值负荷即劳动强度最大值。峰值负荷过高则工作紧张,进而推断该放行席位的任务分配不合理。文中将问题描述为任务有优先序的单机排序问题,每个任务都有一个到达时间（release time）、截止期限（deadline）和处理时间（procession time）,处理时间因任务的不同而不同,目标是在绝对不准延误完成任务前提下,使单位时间的峰值负荷最小。在使单位时间峰值负荷最小的目标下,本文提出了一个有效算法,并证明该算法下的任务安排是最优安排。     

Solving Resource Allocation Problems When Earning Effects Are Present

Learning effects play an important role in certain resource allocation problems, and several authors have proposed models for these problems that capture the relevant relationships. However, the models may be difficult to implement or have shortcomings in the prescribed solution procedures. In this paper, we selectively review the work to date and present a simple reformulation that facilitates solution by off-the-shelf software.     

具有凸资源消耗函数的最小化Makespan的平行机调度问题

研究了一类资源受限的平行机调度问题,其中假定作业的处理时间是其消耗资源量的凸减函数,调度的目标是在限定资源总量的情况下最小化Makespan(最大完工时间)。给出了此类NP-hard问题的形式化描述。定义了关键机器与非关键机器,给出了非最优解必定存在非关键机器的论断。尽快缩短非关键机器与关键机器之间工作量的差距能够有效逼近最优解,从而构造了快速的模拟退火算法。设计了一个下界用于衡量解的精度,并用于构造模拟退火算法迭代结束条件。算法性能通过20000组随机数值算例进行了测试,实验结果表明所构造的模拟退火算法能够在0.1秒之内有效求解1000个作业的问题并将相对误差控制在0.01%以内。该算法体现出很高的精度和计算效率。