带广义紧前约束的资源受限项目计划问题求解

介绍带广义紧前约束资源受限项目计划问题的约束条件和数学模型,对该问题的网络拓扑和时间约束条件进行了分析,对该问题求解的相关定义、定理、预处理过程进行了介绍,提出该问题的蚁群禁忌优化算法.     

多执行模式项目调度问题的克隆选择优化

针对多执行模式资源受限项目调度问题的具体特点,采用基于调度的编码方式、半随机的初始种群产生方式、受限变异等策略,提出一种克隆选择优化算法用于求解项目活动的最优调度以使整个工程工期最短.该方法将问题特性与免疫克隆选择算法所具有的全局搜索特性、解的多样性和不易早熟的特点相融合,在能获得最优解的前提下,使得所花费的代价大为降低.通过对标准测试库PSPLIB中调度问题的仿真实验表明,该算法具有良好的性能,对于各组测试集中的大部分问题都能在合理的时间内寻找到最优解.与其它启发式算法相比,该方法具有更优的性能.     

Experimental Evaluation of Agent-based Approaches to Solving Multi-mode Resource-Constrained Project Scheduling Problem

ABSTRACT

In this paper, a rank-based nonparametric statistical test for measuring the effect of cooperation between optimization agents solving the multi-mode resource-constrained project scheduling problem is presented. To solve this NP-hard optimization problem, different methods are applied including population- and agent-based approaches. One of them is a team of asynchronous agents composed of multiple optimization agents, management agents, and common memories, which through interactions produce solutions of hard optimization problems. Optimization agents represent different methods including local search, path relinking, or tabu search. Interactions are managed through various cooperation strategies based on applying heuristics, reinforcement learning, or population learning.     

Two-Phase Genetic Local Search Algorithm for the Multimode Resource-Constrained Project Scheduling Problem

In this paper, the resource-constrained project scheduling problem with multiple execution modes for each activity is explored. This paper aims to find a schedule of activities such that the makespan of the schedule is minimized subject to the precedence and resource constraints. We present a two-phase genetic local search algorithm that combines the genetic algorithm and the local search method to solve this problem. The first phase aims to search globally for promising areas, and the second phase aims to search more thoroughly in these promising areas. A set of elite solutions is collected during the first phase, and this set, which acts as the indication of promising areas, is utilized to construct the initial population of the second phase. By suitable applications of the mutation with a large mutation rate, the restart of the genetic local search algorithm, and the collection of good solutions in the elite set, the strength of intensification and diversification can be properly adapted and the search ability retained in a long term. Computational experiments were conducted on the standard sets of project instances, and the experimental results revealed that the proposed algorithm was effective for both the short-term (with 5000 schedules being evaluated) and the long-term (with 50000 schedules being evaluated) search in solving this problem.      

资源限制混合流水车间调度的启发式算法

本文针对从流程工业生产过程中抽象出的考虑资源限制的混合流水车间调度问题,提出了基于规则集的几种启发式算法,并以数值试验证明了算法的有效性。     

Hybrid Differential Evolution and Greedy Algorithm (DEGR) for solving Multi-Skill Resource-Constrained Project Scheduling Problem

Paper presents a hybrid Differential Evolution and Greedy Algorithm (DEGR) applied to solve Multi-Skill Resource-Constrained Project Scheduling Problem. The specialized indirect representation and transformation of solution space from discrete (typical for this problem), to continuous (typical for DE-approaches) are proposed and examined. Furthermore, Taguchi Design of Experiments method has been used to adjust parameters for investigated method to reduce the procedure of experiments. Finally, various initialisation, clone elimination, mutation and crossover operators have been applied there. The results have been compared with the results from other reference methods (HantCO, GRASP and multiStart Greedy) using the benchmark iMOPSE dataset. This comparison shows that DEGR effort is very robust and effective. For 28 instances of iMOPSE dataset DEGR has achieved the best-known solutions.     

蚁群算法在资源受限项目调度问题中的应用

资源受限的项目调度问题(RCPSP,Resource-ConstrainedProjectSchedulingProblems)已经被证明是一种NP-hard的组合优化问题,随着问题规模的增大,使用经典的数学方法如数学规划等方法,已经很难解决问题。论文提出了一种用于求解资源受限的项目调度问题的蚁群算法。针对资源受限的项目调度问题的具体特点,提出了蚂蚁巡游网络图的动态生成方式,信息素的表示及更新方式,以及启发信息的计算方法。针对PSPLIB中的测试集对算法中的主要参数进行了优化,最后,使用PSPLIB中的四种测试集对算法进行了测试,计算结果表明了算法的有效性。     

The Quay Crane Scheduling Problem

The recent growth in worldwide container terminals’ traffic resulted in a crucial need for optimization models to manage the seaside operations and resources. Along with the recent increase in ship size and the container volume, the advancements in the field of Quay Crane Scheduling introduced the need for new modeling approaches. This is the motivation behind the current paper, which focuses on developing a novel yet simple formulation to address the Quay Crane Scheduling Problem (QCSP). The objective of the problem is to determine the sequence of discharge operations of a vessel that a set number of quay cranes will perform so that the completion time of the operations is minimized. The major contribution is attributed to the way that minimization is performed, which is by minimizing the differences between the container loads stacked over a number of bays and by maintaining a balanced load across the bays. Furthermore, important considerations are taken into account, such as the bidirectional movement of cranes and the ability to travel between bays even before completion of all container tasks. These realistic assumptions usually increase model complexity; however, in the current work this is offset by the novel simple objective. This paper presents a mixed-integer programming (MIP) formulation for the problem, which has been validated through multiple test runs with different parameters. Results demonstrate that the problem is solved extremely efficiently, especially for small problem sizes.     

The Tricriteria Two-Machine Flowshop Scheduling Problem

The literature on the two-machine flowshop scheduling problem reveals that the problem has been addressed with bicriteria of either makespan and mean flowtime or makespan and maximum tardiness (lateness). This paper extends the problem to all the three criteria (tricriteria) where the objective is to minimize a weighted sum of makespan, mean flowtime, and maximum lateness. A dominance relation and a lower bound are established. The dominance relation and the lower bound are used to develop a branch-and-bound algorithm. The dominance relation is also used to develop several heuristics. An extensive computational analysis is conducted to evaluate the performance of the dominance relation and the heuristics. The analysis shows that the dominance relation is effective. The analysis also shows that the heuristics are quite efficient, and some heuristics have an error of less than 1%. Moreover, these heuristics have the desirable property that the error does not increase by the number of jobs.     

项目调度及其优化

研究了项目调度问题及其优化算法,在对调度问题作了详细分类的基础上,对各种调度问题的优化算法做出．总结,并针对目前各种调度模型存在的不足,提出了均衡优化调度和可持续发展调度等新的调度目标。     

资源约束网络中基于LSSVM的预测反馈调度

针对资源约束网络负载的动态变化,设计了一个基于最小二乘支持向量机(LSSVM)的反馈调度器.它可以周期性地监测网络资源,在线预测下一周期的可适用网络利用率,并根据预测值采用插值法得到控制回路的下一个采样周期,从而实现系统资源的动态分配.对采用固定带宽分配、基于LSSVM以及基于Elman神经网络的反馈调度进行了比较,结果表明,所提出的策略能使系统在可变负载情况下稳定运行,并在控制质量和网络服务质量之间取得平衡.     

作业调度问题研究

生产调度理论与方法研究是一类NP完全问题.在CIMS广泛地应用于企业管理的过程中,会遇到企业生产自动生成及其实时调整的问题.本文分析了当前实际作业调度存在的一些问题和需要考虑的各种因素,列举了主要的作业调度方法和典型应用,指出了各种方法的优缺点,并对未来研究方向做出了展望.     

具有双优先级的信元调度系统中的费用优化问题

本文对具有双优先级的信元调度系统的费用问题进行了量化分析,得到了重要结论：某种策略使得系统丢包最少但不一定总是使系统收益最大,并提出了具体的得到最优服务水平的优化解决方案。     

利用DNA遗传算法求解Flow-Shop调度问题

由于经典遗传算法在求解调度问题尤其是处理复杂的、混淆的和多任务问题时不够灵活且计算速度慢,论文引入DNA技术借助生物学理论对其进行改进。DNA遗传算法继承了遗传算法全局搜索的能力,同时利用DNA双螺旋结构和碱基互补配对原则进行编码运算,提高了算法的有效性和收敛速度,从而很好地解决了NP-hard性质的Flow-Shop调度问题。     

车间调度算法的研究和开发

针对车间调度问题,提出了一种改进的拉氏松弛算法,在增加辅助目标函数的基础上,通过对子问题的限制和搜索策略的改变,使拉氏算法的计算量减少,近优解的搜索能力有很大改善,本文还提出了一种基因优化算法,充分利用拉氏算法得到的多个近优解,进一步优化结,仿真结果表明对车间调度问题得到了较好的结果,本方法也可用于其它有约束的规则问题。     

Job- shop 提前/拖期调度问题的研究

基于模糊控制和遗传算法,提出了求解Ｊｏｂ－ｓｈｏｐ提前／拖期间问题的联合算法,用遗传算法确定可行调度序列,然后用模糊控制器对开工时间加以调整,模糊控制的引入为有效地求解Ｊｏｂ－ｓｈｏｐ提前／拖期调度总理２提供了新的方法,仿真实验证明了联合自救的有效性。     

置换流水线车间调度问题的研究

随着科学技术的发展和生产规模的不断扩大,置换流水线车间调度问题已经越来越受到广大学者的关注。目前,该领域已经出现了许多优化算法,其大大提高了生产的效率。尽管有一些文献已经进行了比较和综述,但是它们没有包括最新的求解方法和研究结果。因此,文中从一个崭新的视角对该问题进行综述,并详细地对比各种算法,使广大学者对其有一个更新、更全面的了解。     

视频点播系统中的节目调度

节目调度问题是视频服务器设计和实现中的一个重要问题 ,优化的节目调度和节目管理可以极大的提高视频服务器的性能 .本文对视频服务器的节目调度方案进行了简要归纳 ,然后提出一种节目调度方案的优化使用方法 .理论分析表明 ,这种方法可以有效的节省服务器的资源 ,提高服务器的服务水平 .     

一种求解多处理机调度问题的a-平坦化调度算法

在分析多处理机调度问题的基础上,提出了α-平坦的概念,并将其引入到多处理机调度问题中;基于此,提出了一种新的基于α-平坦的求解多处理机调度问题的算法。算法首先对作业集合做平坦化处理,然后再对处理后所得的新问题进行求解,最终获得原调度问题的一个近似解。实验结果表明,通过该算法可以求得较好的结果,相对于其它启发式算法,该算法具有较好的稳定性。     

约束满足自适应神经网络求解车间调度问题

提出一种基于约求满足的自适应神经网络方法求解车间作业调度问题。在该算法中,神经网络在运行过程中能够根据问题的约束类型、约束满足情况、启发式规则的选择来自适应调节神经元之间的连接权值,从而求得问题的可行解。仿真实验证明了算法的有效性。