基于改进遗传算法的单机成组作业调度

提出了单机成组作业调度的改进遗传算法。优化目标为总流程时间的单机成组作业调度问题明显是NP-hard问题,此问题的多项式求解方法不能求取最优解,而一些启发式算法也只能求出此问题的次优解。为获得单机成组作业最优调度,通过采用整数实值编码,随机采样选择,单点交叉以及变异检查,设计了单机成组作业调度的改进遗传算法。仿真结果表明,算法能够找到此问题的最优解,其性能优于加权最短加工时间(WSPT)启发式算法。改进遗传算法能够灵活解决各种单目标调度及多目标调度问题。     

作业车间调度转换瓶颈算法可行性研究*

讨论了转换瓶颈( SB) 算法在解作业车间调度问题时需要解决的子问题。转换瓶颈算法是解决作业车间调度最小makespan( 完工时间) 问题的有效启发式算法。它是基于反复地解决某些单机调度问题这样的子问题。然而所解决的单机调度问题的解可能会导致算法最终得不到可行解, 即使是单机调度最优解也可能得到不可行解。为此, 给出了一个简单的反例证明了产生不可行解的情况, 并对产生不可行解的原因作了详细分析。该研究有利于对转换瓶颈技术进行更好的理解和应用。     

作业车间调度转换瓶颈算法的不可行解问题

文章讨论了作业车间调度问题转换瓶颈算法的一个缺陷。转换瓶颈算法是解决作业车间调度最小makespan(完工时间)问题的很有效的启发式算法。它是基于反复的解决某些单机调度问题。然而在转换瓶颈算法中用Carlier算法解单机调度问题并不总能得到可行解,文中给出了一个反例证明了有产生不可行解的情况。另外,文章还以简洁的方法证明了转换瓶颈算法若用Schrage算法替代Carlier算法解单机调度问题不会产生不可行解。     

异构负载下单机调度与预测性维修的集成建模

在生产调度的过程中,设备常常因加工不同作业而承受不同负载即异构负载,设备受异构负载的影响导致其加工每项作业过程中的退化速率不同,从而影响生产调度与维修计划的排程,进而带来资源闲置和时间成本增加的问题.为了解决该问题,在考虑异构负载影响下,提出单机调度与预测性维修的联合策略,以最小总加权期望完成时间为目标构建相应的集成模型.对单机调度过程中受异构负载影响的设备,建立基于维纳过程的退化模型,根据其退化规律,推导相应设备剩余寿命的累积分布函数.通过数值实验,分别针对异构负载与平均负载的情况比较相应集成模型的优化结果,结果表明了在集成模型中考虑异构负载的必要性,并通过参数灵敏度分析验证了所建集成模型的有效性.     

基于并行处理技术的分布式3维数据动态调度策略

为了缓解单机环境下系统资源紧张的问题,在分析单机模式3维数据显示缺点的基础上,首先提出分布环境下的数据处理和调度方案,然后给出了一个通用的逻辑层面的系统模型,最后分析多种数据动态调度策略与优化方案,并给出了客户方和服务方的处理流程。得出并行处理在一定程度上可降低硬件成本,加快运算速度,更好完成3维数据处理任务。     

中厚板热轧生产调度优化方法

中厚板热轧生产调度, 是一个有优先约束、等待时间和缓冲容量有限的单机调度问题. 用AON (Activity-on-node)网络对问题进行描述, 提出并证明了面向单机调度问题的AON网络平衡定理, 根据平衡定理, 建立了以轧机利用率最大为优化目标的非线性约束优化数学模型, 并利用优化软件LINGO进行求解. 计算实例表明, 所提出的数学优化方法, 与现有的启发式方法相比, 能够获得更好的优化目标, 所得到的生产调度方案, 生产节奏稳定, 更有利于组织生产.     

模糊环境下的差异作业单机批调度优化问题的研究*

针对现实生产制造系统中存在的时间参数模糊化问题,本文用梯形模糊数表征时间参数,给出了一种具有模糊加工时间和模糊批次间隔的、以最小化制造跨度为目标的模糊差异作业单机批调度问题模型。在对模糊差异作业单机批调度问题进行有效求解方面,针对基本粒子群算法容易陷入局部最优的问题,本文给出了一种基于遗传操作的混合粒子群算法,利用遗传算法思想对粒子进行交叉、变异操作,增强了算法跳出局部最优的能力。仿真实验验证了该算法具有可行性和有效性。     

具有线性恶化加工时间的调度问题

讨论了工件具有线性恶化加工时间的调度问题.在这类问题中,工件的恶化函数为线性 函数.对单机调度问题中目标函数为极小化最大完工时间加权完工时间和,最大延误以及最大费 用等问题分别给出了最优算法.对两台机器极小化最大完工时间的Flowshop问题,证明了利用 Johnson规则可以得到最优调度.对于一般情况,如果同一工件的工序的加工时间均相等,则 Flowshop问题可以转化为单机问题.     

单机实时系统中的一种混合型实时容错调度算法

目前研究单机实时系统的调度算法文章大多只能调度单一类型的任务。本文在PKSA算法的基础上,建立了一种混合型实时容错模型,提出一种调度算法不仅可以调度有容错需求的周期任务,同时也能够调度无容错需求的周期任务和非周期非实时任务,实现了调度混合型任务的目的。     

单机随机调度中机器的失效分析

随机调度问题已越来越受到人们的重视,单机随机调度的研究已经取得了不少结果,而 当机器失效时会出现什么现象呢?这是实际生产中更关心的问题.本文考虑了机器允许失效 时的单机随机调度问题,在部件的加工时间,机器的寿命和修复时间都服从指数分布的情况 下,得到并证明了使目标函数∑ωjCj,∑ωjUj，∑ωjTj最小的最优调度策略与机器是否失效 无关这一更具一般性的结论.     

Notes on “some single-machine scheduling problems with general position-dependent and time-dependent learning effects”

This paper provides a continuation of the idea presented by Yin et al. [Yin et al., Some scheduling problems with general position-dependent and time-dependent learning effects, Inform. Sci. 179 (2009) 2416-2425]. For each of the following three objectives, total weighted completion time, maximum lateness and discounted total weighted completion time, this paper presents an approximation algorithm which is based on the optimal algorithm for the corresponding single-machine scheduling problem and analyzes its worst-case bound. It shows that the single-machine scheduling problems under the proposed model can be solved in polynomial time if the objective is to minimize the total lateness or minimize the sum of earliness penalties. It also shows that the problems of minimizing the total tardiness, discounted total weighted completion time and total weighted earliness penalty are polynomially solvable under some agreeable conditions on the problem parameters.     

Two-station single-track railway scheduling problem with trains of equal speed

In this paper, the single-track railway scheduling problem with two stations and several segments of the track is considered. Two subsets of trains are given, where trains from the first subset go from the first station to the second station, and trains from the second subset go in the opposite direction. The speed of trains over each segment is the same. A polynomial time reduction from the problem under consideration to a special case of the single-machine equal-processing-time scheduling problem with setup times is presented. Different polynomial time algorithms are developed for special cases with divers objective functions under various constraints. Moreover, several theoretical results which can be ranked in a series of similar investigations of NP-hardness of equal-processing-time single-machine scheduling problems without precedence relations are obtained.     

Minimizing maximum tardiness and delivery costs in a batched delivery system

High delivery costs usually urge manufacturers to dispatch their jobs in batches. However, dispatching the jobs in batches can have profound negative effects on important scheduling objective functions such as minimizing maximum tardiness. This paper considers a single machine scheduling problem with the aim of minimizing the maximum tardiness and delivery costs in a single-machine scheduling problem with batched delivery system. A mathematical model is developed for this problem which can serve to solve it with the help of a commercial solver. However, due to the fact that this model happens to be a mixed integer nonlinear programming model the solver cannot guarantee to reach the global solution. For this reason, a branch and bound algorithm (B&B) is presented to obtain the global solution. Besides, a heuristic algorithm for calculation of the initial upper bound is introduced. Computational results show that the algorithm can be beneficial for solving this problem, especially for large size instances.     

Bounded parallel-batch scheduling on single and multi machines for deteriorating jobs

We consider the bounded parallel-batch scheduling problem in which the processing time of a job is a simple linear function of its starting time. The objective is to minimize the makespan. When the jobs have identical release dates, we present an optimal algorithm for the single-machine problem and an fully polynomial-time approximation scheme for the parallel-machine problem. When the jobs have distinct release dates, we show that the single-machine problem is NP-hard and present an optimal algorithm for one special case.     

A dynamic-programming-based exact algorithm for general single-machine scheduling with machine idle time

This paper proposes an efficient exact algorithm for the general single-machine scheduling problem where machine idle time is permitted. The algorithm is an extension of the authors’ previous algorithm for the problem without machine idle time, which is based on the SSDP (Successive Sublimation Dynamic Programming) method. We first extend our previous algorithm to the problem with machine idle time and next propose several improvements. Then, the proposed algorithm is applied to four types of single-machine scheduling problems: the total weighted earliness-tardiness problem with equal (zero) release dates, that with distinct release dates, the total weighted completion time problem with distinct release dates, and the total weighted tardiness problem with distinct release dates. Computational experiments demonstrate that our algorithm outperforms existing exact algorithms and can solve instances of the first three problems with up to 200 jobs and those of the last problem with up to 80 jobs.     

具有恶化效应和学习效应的单机成组调度问题

讨论了一类具有恶化效应和学习效应的单机成组调度问题, 其中工件的加工时间为开工时间和组内工序的函数. 通过对问题性质的分析以及多项式时间算法的描述, 得出如下结论: 在单机成组调度问题中, 即便工件的加工时间同时受恶化效应和学习效应的制约, 极小化完工时间问题以及极小化总资源消耗的问题仍是多项式时间可解的.     

A tight approximation ratio of a list scheduling algorithm for a single-machine scheduling problem with a non-renewable resource

Journal of Scheduling - In this paper, we investigate an open problem by Györgyi and Kis for a single-machine scheduling problem with a non-renewable resource (NR-SSP) and total weighted...     

Single-machine scheduling with deteriorating jobs and setup times to minimize the maximum tardiness

In many realistic production situations, a job processed later consumes more time than the same job when it is processed earlier. Production scheduling in such an environment is known as scheduling with deteriorating jobs. However, research on scheduling problems with deteriorating jobs has rarely considered explicit (separable) setup time (cost). In this paper, we consider a single-machine scheduling problem with deteriorating jobs and setup times to minimize the maximum tardiness. We provide a branch-and-bound algorithm to solve this problem. Computational experiments show that the algorithm can solve instances up to 1000 jobs in reasonable time.     

Dual constrained single machine sequencing to minimize total weighted completion time

We study a single-machine sequencing problem with both release dates and deadlines to minimize the total weighted completion time. We propose a branch-and-bound algorithm for this problem. The algorithm exploits an effective lower bound and a dynamic programming dominance technique. As a byproduct of the lower bound, we have developed a new algorithm for the generalized isotonic regression problem; the algorithm can also be used as an O(nlogn)-time timetabling routine in earliness-tardiness scheduling. Extensive computational experiments indicate that the proposed branch-and-bound algorithm competes favorably with a dynamic programming procedure. Note to Practitioners-Real-life production systems usually involve multiple machines and resources. The configurations of such systems may be complex and subject to change over time. Therefore, model-based solution approaches, which aim to solve scheduling problems for specific configurations, will inevitably run into difficulties. By contrast, decomposition methods are much more expressive and extensible. The single-machine problem and its solution procedure studied in this paper will prove useful to a decomposition method that decomposes multiple-machine, multiple-resource scheduling problems into a number of single-machine problems. The total weighted completion time objective is relevant to production environments where inventory levels and manufacturing cycle times are key concerns. Future research can be pursued along two directions. First, it seems to be necessary to further generalize the problem to consider also negative job weights. Second, the solution procedure developed here is ready to be incorporated into a machine-oriented decomposition method such as the shifting bottleneck procedure.