带单服务器的自由作业排序问题的启发式算法

研究带单服务器的自由作业排序问题,证明在只有两台机器且加工时间相同的情况下该问题是强NP-困难的,引入了求解该问题的启发式算法,证明该算法的紧界为5/4.在具有m台机器的情况下,给出相应的启发式算法,其紧界为2-3/(m+2).     

自由作业稠密时间表的性质研究

稠密时间表作为自由作业问题的近似解,其加工总长与最优值之比具有上界2-1/m(m为机器数),是一个尚未证明的猜想.利用组合方法证明了稠密时间表性能比猜想成立的一个充分条件.利用该条件及有关文献的结果,给出了机器数不超过7的自由作业稠密时间表性能比猜想的证明.     

最后完工机器至多两个空闲的自由作业稠密时间表(英文)

对于自由作业问题,在安排工件时避免不必要空闲所得的时间表称为稠密时间表.稠密时间表的加工总长不超过最优值的2-1/m倍,是一个在机器数m6时尚未被证明的猜想.本文通过引入工件与机器特征函数及机器关于工件非间断等概念,研究当最后完工机器至多有两个空闲区间时,性能比猜想成立的充分条件.     

可转包的两机自由作业排序问题(英文)

本文研究两机器自由作业问题,每工件恰有两个操作,除本身两台机器用于加工外,制造商可以将部分工件转包给承包商加工.该承包商有一台机器,可以加工全部操作。一旦承担转包任务,制造商需要支付转包费用给承包商,该费用与承包商机器单位时间价格有关.制造商需要确定转包工件集及未转包工件的排序时间表,使得转包费用与时间表的加工总长最小.本文证明该问题是NP困难的,设计动态规划算法,并讨论承包商机器时间的定价方案.     

具有周期维护最小化时间表长的两台平行机调度问题(英文)

本文讨论了具有周期维护的两台平行机调度问题,目标函数为最小化时间表长.设T为维护周期,t为每次对机器维护需要的时间,当t≤T/3时,本文证明了对于该问题由LPT算法得到的最坏误差界为2.     

带有拒绝的单机和同型机排序问题

研究了带有拒绝的单机和同型机排序问题. 对于单机情形, 工件的惩罚费用是对应加工时间的\alpha倍.如果工件有到达时间, 目标为最小化时间表长与惩罚费用之和, 证明了这个问题是可解的.如果所有工件在零时刻到达, 目标为最小化总完工时间与惩罚费用之和, 也证明了该问题是可解的.对于同型机排序问题, 研究了工件分两批在线实时到达的情形, 目标为最小化时间表长与惩罚费用之和.针对机器台数2和m, 分别给出了竞争比为2和4-2/m的在线算法.     

关于平行机排序问题的两点注记

本文考虑了有完工约束的平行机排序问题,证明了问题 pm|T|∑c_i是 NP-完全的,而对问题 pm|T,[_i≡p|∑w_ic_i 提出 O(n~2)的算法,并证明其最优性.将 n 个互相独立的工件(工件集 N={1,2,…,n))放在 m 台等速率平行机(机器M={M_i,…,M_m})上加工.已知每个工件必须且仅须在一台机器上加工一次,并且加工时不允许中断.工件 i(i∈N)在不同机器上加工时间不变,设为 p_i,罚权 w_i 也与机器无关,p_i 和 w_i 皆为非负实数.我们将多台机器加工工件的一个安排称为一个时间表.当时间表π确定后,记工件 i 的完工时间为 c_i(π     

两台平行机完工时间平方和最小的排序问题

在两个竞争公司进行零和博弈过程中, 最大化两个公司收益的乘积, 在两台平行机的离线排序问题中相当于最小化两台机器完工时间的平方和. 给出了该问题修改的延缓开始\ LPT\ 算法: 首先, 将工件按照加工时间$\p_j\ $的\ LPT\ 序重新标记; 若加工时间最长的前\ $2m$\ 个工件的总加工时间\ $P(2m)< (2m+1)p_{2m+1}$, 最优的安排加工前\ $2m+1$\ 个工件, 一旦有机器空闲, 依次从第\ $2m+2$\ 个工件安排加工; 否则,\ $P(2m)\geq (2m+1)p_{2m+1}$, 最优的安排加工前\ $2m$\ 个工件, 一旦有机器空闲, 依次从第\ $2m+1$\ 个工件安排加工. 证明了该算法的最差性能比不超过\ $1+ ( \frac{1}{2m+2} )^2$, 且界是紧的.     

P|rj,on-line|∑Cj的一类在线算法与竞争比分析

本文研究平等机上的在线排序问题,优化目标是使总完工时间最小,算法SSPT是此问题的一类在线算法,论文引入一个拟时间表,此时间表具有SRPT时间表的部分性质,论文通过此辅助时间表证明了SSPT算法是(3-(1/m))-competitive的.     

一类带平行机的两阶段柔性流水调度近似算法

本文研究一类柔性流水调度与平行机调度相结合的两阶段流水调度模型,模型中第1阶段有1台机器,第2阶段有m台同构并行机,每个任务在第2阶段需要size_i台机器同时并行执行.目标是所有任务都完成的完工时间最小化.该模型已被证明出是强NP难的,并给出了在某种特定情况下近似比为3的近似算法.本文首先详细分析了前人近似算法基本过程,给出该算法近似比分析的局限性;接着给出了一个近似比为3的算法,摒弃了前人给出的近似比为3时的约束条件;最后研究了当第2阶段机器数为2和3时的两种特定情况,采用列表调度思想,给出了近似比为2.5和2.67的近似算法.     

处理机具有不同开始加工时间的可中断排序问题

本文对处理机具有的不同开始加工时间的可中断排序问题进行讨论，得到下面结论：若处理机具有相同开始加工时间的可中断排序问题存在最优排序算法，则相应的处理机具有不同开始加工时间的可中断排序问题也存在最优排序算法。     

A disjunctive graph model and framework for constructing new train schedules

Train scheduling is a complex and time consuming task of vital importance in many countries. To create completely new train schedules that are more accurate and efficient than permitted by current techniques, a novel “hybrid” job shop approach is proposed and implemented in this paper. Unique characteristics of train scheduling are firstly incorporated into a disjunctive graph representation of the solution. Dedicated “stand-alone” constructive algorithms that utilise this representation are then developed. The modelling approach and the constructive algorithms are essential as they provide the basis for which meta-heuristics and other iterative refinement algorithms can be applied. A numerical investigation and case study is provided and demonstrates the viability of the modelling approach. Furthermore it is demonstrated that good quality solutions are provided with reasonable computational effort.     

List scheduling algorithms to minimize the makespan on identical parallel machines

In this paper we present constructive algorithms for the classical deterministic scheduling problem of minimizing the makespan on identical machines. Since the problem is known to beNP-hard in the strong sense, the approximate algorithms play a relevant role when solving this problem. The proposed algorithms are based on list scheduling procedures, but the assignment rule is not the same for the full set of jobs. Computational results show that these algorithms perform very well. This research has been partially supported by the Research Project H015/2000, Universidad de Alcalá. The authors are indebted to Joaquín Pérez and the referees for their helpful remarks and comments. We also wish to thank Paul Alexander Ayres for his help in the correct use of English.     

Cyclical scheduling and multi-shift scheduling: Complexity and approximation algorithms

We consider the multiple shift scheduling problem modelled as a covering problem. Such problems are characterized by a constraint matrix that has, in every column, blocks of consecutive 1s, each corresponding to a shift. We focus on three types of shift scheduling problems classified according to the column structure in the constraint matrix: columns of consecutive 1s, columns of cyclical 1s, and columns of k consecutive blocks. In particular, the complexity of the cyclical scheduling problem, where the matrix satisfies the property of cyclical 1s in each column, was noted recently by Hochbaum and Tucker to be open. They further showed that the unit demand case is polynomially solvable. Here we extend this result to the uniform requirements case, and provide a 2-approximation algorithm for the non-uniform case. We also establish that the cyclical scheduling problem’s complexity is equivalent to that of the exact matching problem—a problem the complexity status of which is known to be randomized polynomial (RP). We then investigate the three types of shift scheduling problems and show that, while the consecutive ones version is polynomial and the k-block columns version is NP-hard (for k≥2), for the k-blocks problem we give a simple k-approximation algorithm, which is the first approximation algorithm determined for the problem.     

问题1｜pmtn,dj｜hmax的一个最优算法

给出并证明了求解问题１｜ｐｍｔｎ，ｄｊ｜ｈｍａｘ的一个最优算法。     

一种改进的多模式项目反应性调度问题

既有的项目反应性调度问题只关注了基准调度方案的稳定性,而忽略了项目调度目标的最优实现。本文提出了一种两阶段多模式资源受限项目反应性调度问题。第一阶段,在新的项目执行环境下,对项目进行完全重调度,得到新的最优调度目标值。第二阶段,以新的最优调度目标值为约束,以最大化调度稳定性为目标,求得新的最优调度方案。针对问题特点,基于IBM ILOG优化编程语言OPL和CPLEX V12.8.0,设计出该问题的求解程序。最后,基于标准算例,对本文提出的反应性调度方法、既有的反应性调度方法、完全重调度方法进行了充分的比较测试,结果表明本文提出的反应性调度方法在缩短项目工期、保护基准方案的稳定性方面具有明显优势。     

A Constraint-Based Method for Project Scheduling with Time Windows

This paper presents a heuristic algorithm for solving RCPSP/max, the resource constrained project scheduling problem with generalized precedence relations. The algorithm relies, at its core, on a constraint satisfaction problem solving (CSP) search procedure, which generates a consistent set of activity start times by incrementally removing resource conflicts from an otherwise temporally feasible solution. Key to the effectiveness of the CSP search procedure is its heuristic strategy for conflict selection. A conflict sampling method biased toward selection of minimal conflict sets that involve activities with higher-capacity requests is introduced, and coupled with a non-deterministic choice heuristic to guide the base conflict resolution process. This CSP search is then embedded within a larger iterative-sampling search framework to broaden search space coverage and promote solution optimization. The efficacy of the overall heuristic algorithm is demonstrated empirically on a large set of previously studied RCPSP/max benchmark problems.     

无线网络中全调度问题的一种随机分布式算法

无线网络中的全调度,要确保网络中每个节点所可能的链路信息和广播信息都能无冲突地进行传输.通过简单的构造方法,证明了多项式时间内,能找到一个长度为$O(\bigtriangleup_{\rm out}^2\bigtriangleup_{\rm in})$的全调度;并且给出了全调度问题的一种随机分布式算法,证明了这种随机分布式算法,对任意的常数$h$,~$0     

Learning heuristics for basic block instruction scheduling

Instruction scheduling is an important step for improving the performance of object code produced by a compiler. A fundamental problem that arises in instruction scheduling is to find a minimum length schedule for a basic block—a straight-line sequence of code with a single entry point and a single exit point—subject to precedence, latency, and resource constraints. Solving the problem exactly is known to be difficult, and most compilers use a greedy list scheduling algorithm coupled with a heuristic. The heuristic is usually hand-crafted, a potentially time-consuming process. In contrast, we present a study on automatically learning good heuristics using techniques from machine learning. In our study, a recently proposed optimal basic block scheduler was used to generate the machine learning training data. A decision tree learning algorithm was then used to induce a simple heuristic from the training data. The automatically constructed decision tree heuristic was compared against a popular critical-path heuristic on the SPEC 2000 benchmarks. On this benchmark suite, the decision tree heuristic reduced the number of basic blocks that were not optimally scheduled by up to 55% compared to the critical-path heuristic, and gave improved performance guarantees in terms of the worst-case factor from optimality.     

A Relation between Multiprocessor Scheduling and Linear Programming

The general non preemptive multiprocessor scheduling problem (NPMS) is NP-Complete, while in many specific cases, the same problem is Time-polynomial. A first connection between PMS and linear programming was established by Yannanakis, Sauer and Stone, who associated to any PMS instance some specific linear program. The main result inside this paper consists in a characterization of the partially ordered structures which allow the optimal values of any associated PMS instance to be equal to the optimal values of the corresponding linear programs.