Semi-Online Algorithms for Scheduling with Machine Cost

In this paper, we consider the following semi-online List Model problem with known total size. We are given a sequence of independent jobs with positive sizes, which must be assigned to be processed on machines. No machines are initially provided, and when a job is revealed the algorithm has the option to purchase new machines. By normalizing all job sizes and machine cost, we assume that the cost of purchasing one machine is 1. We further know the total size of all jobs in advance. The objective is to minimize the sum of the makespan and the number of machines to be purchased. Both non-preemptive and preemptive versions are considered. For the non-preemptive version, we present a new lower bound 6/5 which improves the known lower bound 1.161. For the preemptive version, we present an optimal semi-online algorithm with a competitive ratio of 1 in the case that the total size is not greater than 4, and an algorithm with a competitive ratio of 5/4 otherwise, while a lower bound 1.0957 is also presented for general case.     

网络管理中多agent的半在线调度算法

多agent调度算法在基于多agent的网络管理中对任务执行效率起着至关重要的作用.现有的多agent调度算法由于缺乏考虑任务间的依赖关系,使得面对复杂任务系统时会产生大量的网络负载和等待时间.为此,在建立一个适合网络管理任务特点的多agent调度框架的基础上,提出了一种基于任务依赖关系的多agent半在线调度算法.理论分析和测试结果表明,这种半在线调度算法优于已有的全在线调度算法,其性能更接近离线最优调度算法,从而为网络管理任务中多agent的动态调度提供了一种新的途径.     

预测调度算法在平行机问题中的应用

常用的实时生产调度的在线算法由于只利用当前已到达的工件信息,导致调度性能不够理想。针对复杂度较高的平行机调度问题,通过对在线算法OMPR(单机可中断松弛)的改进,设计了一种具体的预测调度算法PPSA(平行机预测调度算法)。预测调度算法合理地把预知信息与已知信息结合起来进行决策,使调度解的性能得到进一步提高。仿真分析显示,该算法的性能明显优于在线算法OMPR,表明预测调度算法是一种计算简单、性能优良的实时调度算法。     

改进的遗传算法在作业调度中的应用

作业调度问题（JSP）是一类典型的NP-hard问题,遗传算法作为一种通用的优化算法在求解JSP中得到了广泛的应用。本文主要针对作业车间调度问题,基于改进的遗传算法 ,根据种群的进化状况,从而确定种群的适应度值,使之能够保持种群的多样化。     

并行任务调度的近似算法

并行任务调度不论是从理论上还是应用上近年来都倍受关注。但是目前出现的大量算法很难应用于实际,基于此,论文探讨了典型的调度问题P3｜fix｜Cmax,这类问题是强NP-难的。论文在Goemans的研究基础上,给出了一个很简单的线性算法,构造出调度性能为9/8的半规则调度,改进了Goemans的7/6的结果。     

Tabu Search Algorithms for Cyclic Machine Scheduling Problems

Tabu search algorithms are developed for solving a large class of cyclic machine scheduling problems with the objective to minimize the cycle time. Neighborhoods are derived which generalize the block-approach based neighborhoods which have been successfully applied to noncyclic job-shop problems. For a variant of this neighborhood opt-connectivity is proved.The tabu-search procedure is applied to cyclic job-shop scheduling problems. Computational results are presented.Supported by INTAS, Project 00-217.Supported by Cusanuswerk.     

复杂并行机调度问题基于分解的优化算法

针对纺织生产过程中广泛存在的带特殊工艺约束的大规模并行机调度问题，提出了一种基于分解的优化算法。首先将原调度问题分解为机台选择和工件排序两个子问题，然后针对机台选择子问题提出一种进化规划算法，并采用一种具有多项式时间复杂度的最优算法求解工件排序子问题，以得到问题特征信息（即每台机器对应拖期工件数的最小值），该问题特征信息用以指导进化规划算法的迭代过程。不同规模并行机调度问题的数值计算结果及实际制造企业应用效果表明，本文提出的算法是有效的。     

网络并行环境下多处理机任务的调度

随着网络技术的不断发展，网络上可供共享的资源越来越丰富，集群技术的兴起更是扩展了并行计算的环境．这种环境下系统中很多任务依赖于多种资源(或多个处理机)，称这样的任务为多处理机任务．本文研究基于多处理机任务的调度模型Pm{fix}Cmax,当m≥3时，这类调度问题是强NP—难的，所以只能寻求有好的逼近性能的多项式时间近似算法．文中给出了当m＝4或5时线性时间的近似调度算法，优于目前已有的最好结果，最后我们还讨论了当k≥3时的一般调度问题．     

混和进化算法求解具有分段恶化效应的并行机调度问题

本文提出了一种新的混合进化算法求解具有线性恶化的并行机调度问题,目标是使总完工时间最小.该算法采用对立策略以及最小比率优先规则生成初始种群,并且引入种群多样度指标加快算法的收敛;同时加入含有3-opt扰动算子的变邻域搜索算法对遗传算法得到的结果进行局部搜索.通过对不同规模算例的实验进行仿真,其结果与传统GA和VNS算法相比,效果均有所提升.     

基于启发式规则的混合遗传算法及其在生产计划优化中的应用

以最优或近似最优的作业顺序编制满足关键资源约束的生产计划优化问题一直是企业生产管理中重要的研究课题之一。文章提出了一种基于传统启发式规则的混合遗传算法。该算法将染色体分为两段,前段表示资源安排策略,后段表示为优先分配规则序列,并设计了一种新的交叉算子。最后,介绍了根据此算法编制的一个制造企业生产控制的软件系统。     

Multicycle Polling Scheduling Algorithms for FieldBus Networks

The paper deals with the scheduling of periodic information flow in a FieldBus environment. The scheduling problem is defined from an analytical point of view, giving a brief survey of the most well-known solutions. One of these is called multicycle polling scheduling, which is based on the hypothesis that all the production periods of the periodic processes to be scheduled are harmonic. Although in some process control or manufacturing scenarios, this hypothesis may be acceptable, there are many real industrial processes to which it cannot be applied. The aim of the paper is to make a contribution towards solving the scheduling problem. It essentially concerns extension of the theory on which multicycle polling scheduling is based to a much more realistic and general scenario, where the periods of all the processes to be scheduled have arbitrary values. The authors present a new formulation of multicycle polling scheduling, called extended multicycle polling scheduling, and demonstrate that it comprises the scenario currently considered in the literature. Two algorithmic solutions for extended multicycle polling scheduling are then proposed, giving a computational complexity analysis which will highlight the capability of the algorithmic scheduling solutions to be performed on-line. The paper concludes by comparing the multicycle polling scheduling approach known in literature and the one presented in the paper. Comparison is performed by evaluating the use of available bandwidth to serve both periodic and asynchronous traffic in the two approaches.     

平行机排序邻域搜索算法设计

为了提高平行机调度的精度,提出了邻域搜索算法。数值试验表明了该算法能找到最优解或跟最优解非常接近的近似解。交换下降算法能有效地应用于多种平行机排序问题。     

混合EDA求解三阶段异构并行机装配集成调度问题

本文提出一种混合分布估计算法（hybrid estimation of distribution algorithm，HEDA）用于求解带载重约束的三阶段异构并行机集成调度问题（three-stage heterogeneous parallel machine integrated scheduling problem with capacitated constraint，THPMISP_CC），第一阶段为加工阶段，即带释放时间的多工序异构并行机调度问题；第二阶段为带载重约束的运输阶段，即多维背包优化调度问题；第三阶段为装配阶段.本文研究工件从加工、运输到装配三阶段的集成调度优化问题.首先，本文构建了THPMISP_CC的数学模型，其优化目标为三阶段整体最大完工时间（Makespan）；然后，提出的HEDA用于优化THPMISP_CC；最后，对算法运用于THPMISP_CC模型的结果进行分析和比较，验证模型的可行性及算法的有效性.     

遗传算法解柔性作业车间调度问题应用综述

柔性作业车间调度问题是典型的NP难问题,对实际生产应用具有指导作用。近年来,随着遗传算法的发展,利用遗传算法来解决柔性作业车间调度问题的思想和方法层出不穷。为了促进遗传算法求解柔性作业车间调度问题的进一步发展,阐述了柔性作业车间调度问题的研究理论,对已有改进方法进行了分类,通过对现存问题的分析,探讨了未来的发展方向。     

Semi-online scheduling with machine cost

For most scheduling problems the set of machines is fixed initially and remains unchanged for the duration of the problem.Recently Imreh and Nogaproposed to add the concept of machine cost to scheduling problems and considered the so-called List Model problem.An online algorthm with a competitive ratio 1.618 was given while the lower boud is 4/3.In this paper,two different semi-onlne versions of this problem are studied‘.In the first case,it is assumed that the processing time of the largest job is known a priori.A semi-online algorithm is presented with the competitive ratio at most 1.5309 while the lower bound is 4/3,In the second case,it is assumed that the total processing time of all jobs is known in advance.A semi-online algorithm is presented with the competitive ratio at most 1.414 while the lower bound is 1.161.It is shown that the additional partial available information about the jobs leads to the possibility of constructing a schedule with a smaller competitive ratio than that of online algorithms.     

考虑能耗与工时恶化作用下的并行机调度优化

在热处理加工环境中,工件温度随着其开工时刻的延误不断下降,为了能够正常加工不得不保温或重新加热.针对这一现象,本文考虑了能耗与工时恶化作用下的并行机调度问题,以最小化总拖期和能耗为目标构建了混合整数规划模型.由于问题的复杂性,提出了一种遗传变搜索算法,其通过遗传操作获得变邻域搜索操作的解集,而后使用变邻域结构进行寻优操作.算例测试表明：较之传统遗传算法以及数学规划器Gurobi的计算结果,所提出的算法可以有效减少综合能耗和拖期成本.     

New Hybrid Optimization Algorithms for Machine Scheduling Problems

Dynamic programming, branch-and-bound, and constraint programming are the standard solution principles for finding optimal solutions to machine scheduling problems. We propose a new hybrid optimization framework that integrates all three methodologies. The hybrid framework leads to powerful solution procedures. We demonstrate our approach through the optimal solution of the single-machine total weighted completion time scheduling problem subject to release dates, which is known to be strongly NP-hard. Extensive computational experiments indicate that new hybrid algorithms use orders of magnitude less storage than dynamic programming, and yet can still reap the full benefit of the dynamic programming property inherent to the problem. We are able to solve to optimality all 1900 instances with up to 200 jobs. This more than doubles the size of problems that can be solved optimally by the previous best algorithm running on the latest computing hardware.     

有中断时间代价的一致并行机抢先调度问题

提出了一种具有中断时间代价的抢先调度问题(P|ptmn(δ)|C_max):在抢先调度中,一个任务发生一次中断,其总的执行时间会增加一个δ.该问题在工程任务分配、分布式计算和网络通信等实际问题中有着广泛的应用背景.证明了这是一个NP-hard问题,给出了一个时间复杂度为O(nlogn+m)的脱线近似算法LPT-Wrap,其近似比小于等于1.40825,并分析了P|ptmn(δ)|C_max的在线特性,给出一个线性时间复杂度的在线近似算法,其竞争比为2.     

带等级约束的多重工件在线(半在线)排序问题

论文提出了带等级约束的多重工件排序问题,每个客户提交多个加工时间和等级相同的工件。目标是寻找一个调度方案,使得机器的最大完工时间最小。当客户的信息未知时,论文设计了一个竞争比为5/3的在线算法。当所有工件的加工时间总和已知时,论文设计了一个竞争比为3/2的半在线算法。这些结论对经典带等级约束的两台平行机排序问题进行了推广。     

RAID的并行I／O调度算法分析

由于越来越多的应用受限于I／O，存储系统正起着越来越重要的作用，磁盘阵列RAID是一种提供高性能I／O的最常见存储设备，本文分析了RAID并行I／O调度算法的I／O执行时间和磁盘利用率，为合理配置高性能阵列提供了依据。