移动网格环境下可靠任务调度研究

移动网格的资源环境具有很高的动态性,在任意时刻可能发生资源加入、退出、故障、移动等。采用任务复制策略实现对资源不可靠性的容错。用weibull分布刻画资源的可靠性,建立任务复制模型;形式化描述了基于复制策略的独立任务调度问题,给出调度目标和约束条件;通过遗传算法解决调度问题。仿真结果表明,调度算法具有良好的可扩展性,调度性能与资源可靠性呈线性关系。     

考虑资源闲置成本的多项目调度问题研究

针对资源受限多项目整体进度优化问题,考虑资源分配过程中的资源闲置成本,提出了一种集成工期延迟和资源闲置成本的多目标调度协同优化模型。通过该模型提高了资源的利用效率,理论上实现了多项目在目标成本最小情况下的整体进度方案。综合利用模拟退火算法和遗传算法的优点,设计退火遗传算法对该模型进行求解,通过算例验证了算法和模型的有效性。     

运用遗传算法优化项目级现金流问题的研究

针对项目级现金流的优化问题,结合传统的资源受限项目调度模型,得到一种带现金流折现的非线性规划项目调度模型,并设计启发式遗传算法对其进行优化求解.通过引入现金流分析,项目调度模型能反映企业的财务指标,更切合实际.通过设计相应的编码方式、遗传算子和调度生成策略,提出了一种改进的遗传算法并用于求解此优化问题,数值实验结果证明了该算法的正确性和高效性.     

基于遗传算法的网格制造资源优化选择

制造资源的选择和优化是制造网格应用过程中的关键问题.本文通过对已有制造资源搜索方法进行分析,指出其存在的局限性;在对资源选择问题进行数学描述的基础上,提出了一个基于遗传算法的制造资源组合优化模型,并对该模型的算法进行了设计;最后,给出了一个典型算例,以说明该模型和算法的有效性.     

虚拟组织服务资源的优化配置模型

为了提高虚拟组织服务资源配置的效率,提出了以服务成本、服务时间、服务满意度为目标的资源优化配置模型,采用遗传算法进行求解。在求解中为提高遗传算法的搜索性能,对不可行染色体进行筛选,同时在交叉变异过程中利用邻域搜索提高算法的收敛速度。通过一个具体的实例验证了遗传算法在资源优化配置模型中的有效性。     

基于遗传算法的烟草配送车路径优化问题

在建立烟草配送车路径优化问题模型的基础上,采用轮盘赌复制法、部分匹配交叉算法、和适应度函数自适应调整等技术,设计了基于自然数编码的遗传算法,最后以这种方法进行了实验计算,通过计算结果表明,用遗传算法进行烟草车配送路径优化,可以方便有效地求得问题的最优解或近似最优解.     

基于遗传算法的函数求解方法改进

针对一些工程技术中求最优值问题转化为遗传算法模型后,定义域难以限定或交叉、变异产生定义域外的不可行解的问题,提出了在选择复制操作前,增加筛选复制操作的方法.通过设置函数求导求解对照组,对改进的遗传算法的最优解进行验证,实验表明,增加筛选复制步骤后的遗传算法具有更好的适用性,且能有效解决不可行解干扰遗传准确性的问题.     

基于多目标遗传算法的工程资源优化配置

为了使工程资源能够在工程应用中最大程度的优化配置, 利用遗传算法模拟自然进化过程求得最优解的特点, 对遗传算法和多目标优化问题的理论基础和模式定理的进行了分析, 讨论了遗传算法在解决多目标优化工程资源问题过程中的优势, 最后将多目标遗传算法应用于具体工程资源配置实例予以实现. 仿真优化结果表明: 遗传算法在工程资源优化配置过程中更具有先进性, 可靠性和优化性.     

远亲杂交遗传算法及其在供应链优化中的应用

基于生物系统中普遍存在“远亲杂交优于近亲繁殖”的现象,提出了基于远亲杂交的遗传算法：远亲杂交保持演化群体良好的多样性,克服了遗传算法局部收敛的缺陷,提高了算法的全局搜索能力。针对供应链优化研究,本文提出了一个新型供应链优化模型,同时把新算法应用于求解该优化问题,结果表明,对供应链优化问题的求解,远亲杂交遗传算法优于基本遗传算法和分枝界定法。     

团购模式下云制造服务资源组合优化模型与算法

在云制造服务环境中,为了进一步降低需求者的服务成本,提出了一种团购模式下云制造服务资源组合优化模型与算法。在云制造平台发展的初期阶段,以服务需求者的视角分析云制造服务资源组合优化管理问题,通过团购模式研究了资源组合优化模型与算法,模型中考虑团购定价、团购信任度等关键影响因素,对云制造资源组合优化进行综合决策;设计改进的遗传算法进行模型求解,进一步对团购模式下云制造服务资源组合模型进行仿真分析。通过不同规模问题的仿真实验验证了模型与算法的有效性和可行性,仿真结果表明,在团购规模逐渐增大的情况下,团购模式比个体模式更具有成本优势。     

改进GAs算法在大规模资源分配问题中的应用

采用改进ＧＡｓ算法建立了求解大规模规划的资源分配模型．针对大规模资源分配问题的具体特点，设计了合适的ＧＡｓ算子，并以实例验证了算法的合理性及有效性．     

An improved resource allocation scheme for plane cover multiple access using genetic algorithm

An improved resource allocation scheme is proposed in this paper which uses genetic algorithms (GAs) in conjunction with the recently developed plane cover multiple-access (PCMA) scheme in order to maximize the attainable capacity of packet-based wireless cellular networks. The studied problem has been proven to be in the class of nondeterministic polynomial (NP)-hard problem, therefore, the powerful search capability of the GA is a key factor in improving the performance of cellular resource allocation. Computer simulation results suggest that the proposed approach outperforms the "uniform" and the "greedy" algorithm-based "min " methods in terms of the number of serviced users.     

项目资源均衡研究综述

作为一类经典的项目调度问题,资源均衡研究的是如何通过安排活动来均衡整个项目周期内资源的使用.资源均衡问题因其重要的理论价值和应用背景,一直是项目调度领域的重点研究课题.鉴于此,对国内外项目资源均衡的研究成果进行了系统性总结与梳理:介绍了资源均衡问题的数学模型和常用的测试问题库;综述了求解资源均衡问题的各类算法;总结了资源均衡问题的一些扩展问题和应用情况.最后指出了未来进一步的研究方向.     

The total adjustment cost problem: Applications,models, and solution algorithms

Resource leveling problems arise whenever it is expedient to reduce the fluctuations in resource utilization over time, while maintaining a prescribed project completion deadline. Several resource leveling objective functions may be defined, consideration of which results in well-balanced resource profiles. In this paper, we concentrate on a special objective function that determines the costs arising from increasing or decreasing the resource utilizations. The resulting total adjustment cost problem occurs, for example, in the construction industry and can be formulated using mixed-integer linear programming models. Apart from a discrete time-based formulation, two polynomial formulations, namely an event-based model and a start-based model, which exploit structural properties of the problem are presented. In addition, a heuristic solution algorithm is proposed to generate start solutions for the problem. We use CPLEX 12.4 to solve medium-scale instances known from the literature. A computational performance analysis shows that the discrete time-based model and the start-based model are suitable for practical applications.     

Hybrid genetic algorithmsfor a multiple-objective scheduling problem

This paper describes the characteristics of two hybrid genetic algorithms (GAs) for generating allocation and sequencing of production lots in a flow-shop environment based on a non-linear, multi-criteria objective function. Both GAs are used as search techniques: in the first model the task of the GA is to allocate and sequence the jobs; in the second model, the GA is combined with a dispatching rule (Earliest Due Date, EDD) thus limiting its task only on the allocation of the jobs. Both GAs are characterized by a dynamic population size with dynamic birth rate, as well as by multiple-operator reproduction criteria and by adaptive crossover and mutation rates. A discrete-event simulation model has been used in order to evaluate the performances of the tentative schedules. The proposed algorithms have been subsequently compared with a classical branch and bound method.     

多项目资源均衡问题及其遗传算法

针对单项目资源均衡优化在企业实际应用中的不足,提出了多项目资源均衡优化的概念,建立了多项目资源均衡问题模型。在此基础上给出一种遗传算法的求解方法,在算法中有效地利用了网络计划图的拓扑排序,减少了遗传操作过程中非法个体的修复计算量,加快了算法的收敛速度。实例计算表明,多项目资源均衡优化可以有效地实现整个企业资源的均衡配置,遗传算法在求解该问题时具有可行性和高效性。     

基于遗传算法的导弹技术准备资源平衡优化

针对目前我军在导弹技术准备流程资源均衡利用方面存在的不足,提出了一种改进的遗传算法,很好地解决了资源平衡问题.首先分析了网络计划中工序逻辑关系特点,采用均方差指标建立资源平衡优化模型.在算法设计中,针对资源平衡问题的特点专门设计了修复算子,用于解决交叉和变异会产生非法染色体的问题.算法比传统算法更少依赖问胚本身的特有信息,因而适用范围更广.最后以某型导弹吊装流程为例进行了实例分析,表明方法具有很强的寻优能力,对于促进保障单位合理利用资源、科学安排工程调度具有重要的现实意义.     

Project resources scheduling and leveling using Multi-Attribute Decision Models: Models implementation and case study

Project scheduling is one of the most vital processes in Project Management. It is a widely discussed topic in academic and practical circles due to its importance and complexity. Manpower, machines, materials and equipment are used for the execution of project activities, but these mostly have limited availability, which can constrain project scheduling procedures. Project resources might exceed or fall short of the resource demand in a project's time horizon. These considerations present issues to project managers who must try to properly allocate among these demands in order to achieve a near optimal utilization during a project's lifetime. Resource leveling is among the greatest challenges faced by project managers as the success of a project largely depends on it. This is because peaks and valleys in the resource usage histogram are responsible for cost overruns due to the necessary recruitment, dismissal and training of the personnel Moreover, issues may arise regarding the efficient management of available resources given that large peaks correspond to fluctuations in resource allocation during a project's life cycle or construction period. To address these issues, resource leveling provides procedures and frameworks that ensure the efficient management of resources to obtain smooth resource usage profiles. These procedures attempt to identify activities that should be delayed to resolve resource over-allocations under time and cost constraints. Given the existence of a variety of available rules that could be followed by project managers to prioritize activities, the paper at hand examines the implementation of five Multi-Attribute Decision Making models and how they perform in the scheduling of a solar park construction project. Namely these models are the Weighted Sum Method, Analytic Hierarchy Process, PROMETHEE, TOPSIS, Ordered Weighted Average (OWA) and Hybrid Weighted Average (HWA). Finally, the derived results are discussed in comparison with those obtained by the standard resource leveling procedures of MS-Project.     

基于MAS市场机制的动态计算资源调度模型研究

针对动态计算网格资源调度问题,结合多Agent系统(multi agent syste,MAS)协同技术和市场竞价博弈机制,对计算网格资源分配技术进行了深入研究,提出了能够反映供求关系的基于市场经济的网格资源调度模型,该模型一方面能够充分利用消费者Agent的协商能力,另一方面能够充分考虑消费者的行为,使得消费者的资源申请和分配具有较高的合理性和有效性.同时,设计了消费者的效用函数,论证了资源分配博弈中Nash均衡点的存在性和惟一性以及Nash均衡解.基于所提资源调度模型,设计了一种网格资源调度算法.仿真实验表明,资源调度算法能够为消费者的资源数量提供参考,规范消费者竞价,从而使得整个资源的分配趋于合理.     

基于遗传算法的工程项目资源均衡研究

提出一种基于遗传算法的工程项目“工期固定,资源均衡”问题的解法。针对问题特点,采用自然数作为染色体编码方式,设计了相应的遗传操作算子,提出一种新型修复策略,用于修复在交叉过程中产生的非法个体使其成为可行解。算例表明,该方法的计算结果优于传统的启发式方法,更为灵活通用,可较好应用于大型工程项目的资源优化问题。