基于决策者风险偏好的模糊鲁棒性项目调度优化

不确定条件下模糊鲁棒性项目调度计划的生成受决策者风险偏好影响。本文研究模糊活动工期下考虑决策者风险偏好的鲁棒性项目调度优化问题，目标是合理安排活动开始时间，生成特定风险偏好下鲁棒性最大的进度计划。首先界定问题，构建优化模型；随后针对问题NP-hard属性和模型特点设计交替禁忌搜索启发式算法，求解得到不同风险偏好下满意的进度计划；最后用实例验证说明，并分析关键参数影响。结论如下：决策者风险偏好由规避转乐观时，项目冲突区间总和增多；截止日期、资源可用量较紧张时，风险偏好变化对冲突区间总和变化影响更大；风险偏好乐观时，截止日期变化对冲突区间总和变化影响更大。研究成果可为不同风险偏好决策者在不具历史数据的高不确定环境中制定合理前摄性计划提供决策支持。     

基于拍卖谈判机制的分布式多技能多项目调度

求解分布式多项目调度问题的关键是设计有效的资源协调机制以解决项目间的全局资源冲突。当全局资源为多技能人力资源时,调度项目活动开始时间的同时还需要满足“活动-技能-资源”的匹配关系,从而为多项目制定高质量的调度计划与全局资源指派方案。基于多Agent系统,建立局部调度优化与全局协调决策的双层模型;采用基于正向逆向调度改进的遗传算法求解初始局部调度计划;以人力资源各时段的使用权作为拍卖品,设计考虑人力资源多技能异质特点的拍卖谈判机制协调全局资源冲突。改编MPSPLIB算例集并开展实验研究,研究结果表明：本文设计的拍卖谈判机制与改进的遗传算法相结合可以有效协调不同规模问题的全局资源分配;拍卖谈判机制在测试问题集上的求解结果优于序贯博弈谈判机制;问题规模越大或资源冲突程度越强,项目协调调度难度越大,全局资源分配过程越复杂。     

基于活动延期风险加权时差的资源受限项目调度鲁棒性度量

在项目调度鲁棒性研究中,当活动出现延期风险时,由于各活动性质不同,其延期风险权重也不同,权重越大的活动越有可能影响项目的完工时间。针对资源受限项目调度问题,提出一个基于活动延期风险加权时差的鲁棒性度量新指标。在出现不确定因素干扰时,该指标不仅考虑了活动延期风险权重的影响,同时为实现时差在多个任务之间的共享,还考虑了紧前任务数量的影响。建立一个以加权时差最大化为目标的资源受限项目调度鲁棒优化模型,并针对模型特点,设计了基于禁忌搜索的模拟退火算法。最后,通过算例验证了该度量方式和算法的合理性和有效性,对比分析结果表明所提出的指标优于现有的度量指标,较好地满足了项目调度质量鲁棒性的要求。     

一种求解柔性资源约束前摄性项目调度问题的启发式算法

在不确定环境中,一个具有较高鲁棒性的进度计划可以保证项目的稳定实施。考虑到现实中资源可能具有多种技能,会对制定鲁棒性较高进度计划的过程产生影响,因此本文研究了柔性资源约束下前摄性项目调度优化问题。首先界定研究问题;然后从鲁棒性最大化的视角出发,构建了研究问题的优化模型,在对模型进行分析的基础上将其分解为经典鲁棒优化和资源技能分配两个子模型;随后设计了求解问题的基于削峰算法的启发式算法;最后用一个实际案例验证了算法有效性,并分析了关键参数对进度计划鲁棒性的影响,得到如下结论:项目进度计划鲁棒性随着项目工期的延长、资源可用量的增加或资源柔性的提高而增大。     

基于资源约束的突发事件应急救援鲁棒性调度优化

突发事件应急救援的调度优化,对于救援活动的顺利实施及应急资源的有效使用具有至关重要的作用。本文研究资源约束下的突发事件应急救援鲁棒性调度优化问题,其中,鲁棒性定义为各活动的时间缓冲与其权重系数乘积的总和,目标是在资源可用量及救援期限的约束下,安排活动开始时间和执行模式以最大化应急救援计划的鲁棒性。作者构建了问题的0-1规划优化模型,针对其NP-hard属性,基于问题特征设计双环路禁忌搜索启发式算法。通过对一个算例的计算分析,得到如下结论:给定网络结构及时间参数,利用权重系数的定义可以将时间缓冲分配到重要活动上,由此提高应急救援计划的鲁棒性;随着资源可用量的增加,计划的鲁棒性呈上升趋势,而当救援期限延长时,计划的鲁棒性单调增加。本文研究可为突发事件应急救援基准计划的制定提供决策支持。     

集装箱码头泊位计划的鲁棒优化模型

针对集装箱码头作业中的不确定性因素,构建泊位计划的鲁棒优化模型与算法,目的是降低不确定性因素对集装箱码头作业系统的影响。首先,提出泊位计划鲁棒性度量指标,利用算例对各指标的效果进行分析。在此基础上,设计泊位计划鲁棒优化的两阶段优化算法。算法的第一阶段不考虑泊位计划的鲁棒性,以船舶总延误时间最小为目标;算法的第二阶段以所选择的鲁棒性指标最大为目标,以第一阶段获得的船舶总延误时间为约束条件,获得鲁棒调度方案。最后,研究作业资源(装卸桥数量)的变化对泊位计划鲁棒性的影响。算例分析表明,权重松弛量是有效的度量泊位计划鲁棒性的指标,两阶段算法可以有效解决泊位计划鲁棒优化问题。     

随机活动工期下求解资源约束项目最大期望净现值的动态调度算法

本文研究了随机活动工期下如何调度资源约束项目使得项目的期望净现值最大。首先对问题进行了界定,建立了相应的优化模型,其次针对问题的特点设计了一种动态规划算法。在算法设计的过程中,本文通过对项目网络图结构及不同状态最优值之间关系的分析,优化了动态规划算法状态的生成过程及状态最优值的求解过程,从而加快了算法的求解。使用随机生成的540个不同规模、不同结构的仿真案例对算法的有效性进行了验证,并分析了项目网络特征对算法效率的影响。实验发现:项目的次序强度对算法所需时间有着较大的影响,随着项目次序强度的减小,生成的状态数量会增加,从而计算时间也会增加。本文的研究可以为不确定环境下的项目调度提供决策支持。     

基于MAS的多模式分布式资源约束多项目调度

针对实践中分布式多项目的活动往往具有多种执行模式,提出多模式分布式资源约束多项目调度问题。在项目动态到达环境下,考虑活动不同的执行模式,以工期最短和多项目延期成本最小为目标分别构建局部单项目调度模型和全局多项目决策模型,采用改进变邻域搜索算法求解初始局部调度计划,并设计基于模式调整的全局协商调度算法求解全局决策模型,通过双层算法实现分布式多项目调度中局部单项目调度与全局多项目调度系统性协调,减少项目中断和多项目延期成本。基于构建的多模式测试集进行的多项目数值实验表明：本文设计的双层算法可有效求解多模式分布式多项目调度问题,并且对不同规模问题求解具有良好的适应性。     

多目标资源受限项目鲁棒调度研究

由于资源受限项目调度属于NP-hard问题,传统的RCPSP主要集中于工期最短单一目标的基本问题研究,而忽略了项目调度对鲁棒性等多目标属性特征的要求。本文以经典的串行进度生成机制为基础,引入了衡量项目稳定性的鲁棒性要素,创建了项目鲁棒调度串行生成机制(RSSGS),提出了项目鲁棒性的测度新指标,构建了优化鲁棒结构的工期最短和鲁棒性最大的双目标优化模型,并结合分层优化原理,设计了改进的SA算法。最后,采用算例验证了该模型的可行性和合理性。     

模糊人工蜂群算法的多选择多维背包问题求解

针对传统人工蜂群算法早熟收敛问题,基于模糊化处理和蜂群寻优的特点,提出一种模糊人工蜂群算法。将模糊输入输出机制引入到算法中来保持蜜源访问概率的动态更新。根据算法计算过程中的不同阶段对蜜源访问概率有效调整,避免算法陷入局部极值。通过对多选择多维背包问题的仿真实验和与其他算法的比较,表明本算法可行有效,有良好的鲁棒性。     

基于MAS协作机制的动态计算资源调度模型

针对网格环境的自治性、动态性、分布性和异构性等特征.提出基于多智能体系统(Mutil Agent System,MAS)博弈协作的资源动态分配和任务调度模型,建立了能够反映供求关系的网格资源调度模型和任务求解算法,证明了资源分配博弈中Nash均衡点的存在性、唯一性和Nash均衡解,该方法能够利用消费者agent的学习和协商能力,考虑和引入消费者的心理行为,使得消费者的资源申请和任务调度具有较高的合理性和有效性.实验结果表明,资源调度算法不但可以有效减少不必要的延迟,而且在响应时间的平滑性、吞吐率及资源利用率方面比传统算法要好,从而使得整个资源的供需合理、负载均衡.     

Heuristics for multimode scheduling problems with dedicated resources

We study scheduling problems with multiple modes and dedicated resources arising in production and project management, which constitute a special class of the general multimode resource-constrained project scheduling problem. A task may require simultaneously a set of discrete, renewable resources to be processed and the processing can be performed in different modes, that is with different resource sets, processing times, or costs. Precedence constraints can exist among tasks. The total budget that can be allocated to the project can be limited. The problem consists of identifying a mode for each task and a starting time for its processing respecting precedence, resource, and budget constraints. A graph model and an iterative solution scheme are presented. Specific heuristic algorithms for the cases with and without budget constraints are given and computational results are discussed.     

Project selection,scheduling and resource allocation with time dependent returns

In this paper we formulate and analyze the joint problem of project selection and task scheduling. We study the situation where a manager has many alternative projects to pursue such as developing new product platforms or technologies, incremental product upgrades, or continuing education of human resources. Project return is assumed to be a known function of project completion time. Resources are limited and renewable. The objective is to maximize present worth of profit. A general mathematical formulation that can address several versions of the problem is presented. An implicit enumeration procedure is then developed and tested to provide good solutions based on project ordering and a prioritization rule for resource allocation. The algorithm uses an imbedded module for solving the resource-constrained project scheduling problem at each stage. The importance of integrating the impact of resource constraints into the selection of projects is demonstrated.     

Approximation algorithms for scheduling on multi-core processor with shared speedup resources

We consider a joint resource partition and scheduling problem. We are given $m$ identical cores and discrete resources of total size $k$. We need to partition the resources among these cores. A set of jobs must be processed non-preemptively on these cores after the resource partition. The processing time of a job on a core depends on the size of resources allocated to that corresponding core. The resource allocation scheme is static, i.e., we cannot change the amount of resources that was allocated to a core during the whole scheduling. Hassidim et al. (2013) investigated this problem with a general processing time function, i.e., the processing time of a job is an arbitrary function of the level of resources allocated to that core. They provided an algorithm with approximation ratio of 36. In this paper, we improve the approximation ratio to 8 by presenting a new resource partition scheme. Next, we consider a special model where the core’s speed is proportional to its allocated resource, then we present two algorithms with improved approximation ratios.     

汽车4S店维修车间的优化调度分析

调度研究的问题是将稀缺资源分配给在一定时间内的不同任务,它是一个决策过程,其目的是优化一个或多个目标。对实际问题的优化调度可以帮助企业提高资源利用率,减少客户等待时间,提升竞争力,对汽车4S维修服务站的优化调度问题进行研究,剖析这一实际应用问题的调度目标、机器环境、加工特征和约束等细节,提出了优化调度模型,设计了调度算法。然后,通过实例,简要分析了模型及算法的可行性.     

The multi-mode resource-constrained project scheduling problem with generalized precedence relations

In this paper, we tackle the challenging problem of scheduling activities to minimize the project duration, in which the activities (a) are subject to generalized precedence relations, (b) require units of multiple renewable, non-renewable and doubly constrained resources for which a limited availability is imposed, and (c) can be performed in one of several different ways, reflected in multiple activity scenarios or modes. These multiple modes give rise to several kinds of trade-offs (time/resource, time/cost and resource/resource trade-offs) which allow for a more efficient allocation and use of resources. We present a local search-based solution methodology which is able to handle many real-life project scheduling characteristics such as time-varying resource requirements and availabilities, activity ready times, due dates and deadlines, activity overlaps, activity start time constraints and other types of temporal constraints.     

人力资源约束下的项目群调度问题建模与求解

基于人员胜任力是影响工作绩效的关键因素,将资源受限项目调度问题中的可更新资源通过一系列科学合理的方法或者手段转变为存在胜任力差异的人力资源,由此构建起一个强调胜任力差异的人力资源约束项目调度问题模型,此模型最突出的优势在于选取了能够客观合理评估人员胜任力的指标,提供了严谨科学的关系式,将复杂的多项目总工期与总成本的双目标最小化问题转换为综合指标单目标最大化问题,建立数学优化模型,采用遗传算法求解。通过算例研究证实,相较于传统多模式模型,基于人员胜任力水平差异的模型明显更胜一筹,其优势集中表现为最优工期更短、最优成本更低。考虑了胜任力差异的数学优化模型更符合研发项目群管理实践,同时遗传算法在求解方面不仅效率高,并且更容易获得客观准确的结果。     

Finding the shortest path with honey-bee mating optimization algorithm in project management problems with constrained/unconstrained resources

Effective project management requires the development of a realistic plan and a clear communication of the plan from the beginning to the end of the project. The critical path method (CPM) of scheduling is the fundamental tool used to develop and interconnect project plans. Ensuring the integrity and transparency of those schedules is paramount for project success. The complex and discrete nature of the solution domain for such problems causes failing of traditional and gradient-based methods in finding the optimal or even feasible solution in some cases. The difficulties encountered in scheduling construction projects with resource constraints are highlighted by means of a simplified bridge construction problem and a basic masonry construction problem. The honey-bee mating optimization (HBMO) algorithm has been previously adopted to solve mathematical and engineering problems and has proven to be efficient for searching optimal solutions in large-problem domains. This paper presents the HBMO algorithm for scheduling projects with both constrained and unconstrained resources. Results show that the HBMO algorithm is applicable to projects with or without resource constraints. Furthermore, results obtained are promising and compare well with those of well-known heuristic approaches and gradient-based methods.     

A hybrid scatter search for the discrete time/resource trade-off problem in project scheduling

We develop a heuristic procedure for solving the discrete time/resource trade-off problem in the field of project scheduling. In this problem, a project contains activities interrelated by finish-start-type precedence constraints with a time lag of zero, which require one or more constrained renewable resources. Each activity has a specified work content and can be performed in different modes, i.e. with different durations and resource requirements, as long as the required work content is met. The objective is to schedule each activity in one of its modes in order to minimize the project makespan. We use a scatter search algorithm to tackle this problem, using path relinking methodology as a solution combination method. Computational results on randomly generated problem sets are compared with the best available results indicating the efficiency of the proposed algorithm.