阻塞混流生产机器人制造单元调度问题可行解性质研究

针对阻塞混流生产机器人制造单元调度问题的可行解性质进行研究。首先,定义了机器人活动,将机器人运行排序和工件加工排序转化为机器人活动调度,将二维调度问题转化为一维调度问题;其次,提出了可行机器人活动调度概念,给出了几个等价定义;最后,给出了可行机器人活动调度经过一定变换,仍然是可行调度的条件。这些性质为优化算法的设计提供了理论基础。     

A heuristic solution framework for the resource constrained (multi-)project scheduling problem with sequence-dependent transfer times

We consider the problem of scheduling multiple projects subject to joint resource constraints. Most approaches proposed in the literature so far are based on the unrealistic assumption that resources can be transferred from one project to the other without any expense in time or cost. In order to contribute to closing this gap to reality, we generalise the multi-project scheduling problem by additionally including sequence- and resource-dependent transfer times, which represent setup activities necessary when a resource is removed from one project and reassigned to another (or from one job to another within the same project). In this paper, we define the modified resource constrained multi-project scheduling problem with transfer times (called RCMPSPTT), which aims at minimising the multi-project duration for the single-project approach or the mean project duration for the multi-project approach. We formulate both perspectives as an integer linear program, propose priority rule based solution procedures and present results of comprehensive computational experiments. Provided that the combination of scheduling scheme and priority rules is chosen appropriately, the procedures obtain good results. In particular, resource oriented priority rules are identified to be successful.     

基于FNP-ADC模型的弹药调度系统保障效能评估

正确评估诸如弹药调度系统此类复杂武器装备的系统效能,可为作战指挥决策提供重要支撑依据,从装备系统结构组成及复杂性出发,合理地表示工作状态及其转移过程,在流水网络计划(flow network planning,FNP)技术框架下应用ADC模型开展效能评估.以FNP时间参数为基础,确定了组成分系统故障一般概率分布下的可用性、可信性和保障能力表示方法,分别表示为影响因素的函数关系,最终建立了FNP-ADC模型.综合进行保障效能评估,可进一步分析因素对效能的影响程度,并给出了案例分析.     

带有资源转移时间的RCPSP资源流模型及算法

本文在传统资源受限项目调度问题(resource-constrained project scheduling problem, RCPSP)中引入资源转移时间,为有效获得问题的最优解,采用资源流编码方式表示可行解,建立了带有资源转移时间的RCPSP资源流优化模型,目标为最小化项目工期。根据问题特征设计了改进的资源流重构邻域算子,分别设计了改进的禁忌搜索算法和贪心随机自适应禁忌搜索算法求解模型。数据实验结果表明,相较于现有文献中的方法,所提两种算法均可针对更多的项目实例求得最优解,并且得到最优解的时间更短,求解效率更高。此外,分析了算法在求解具有不同特征的项目实例时的性能,所得结果为项目经理结合项目特征评价算法适用性提供了指导。     

Flow shop scheduling jobs with position-dependent processing times

The paper is devoted to some flow shop scheduling problems, where job processing times are defined by functions dependent on their positions in the schedule. An example is constructed to show that the classical Johnson's rule is not the optimal solution for two different models of the two-machine flow shop scheduling to minimize makespan. In order to solve the makespan minimization problem in the two-machine flow shop scheduling, we suggest Johnson's rule as a heuristic algorithm, for which the worst-case bound is calculated. We find polynomial time solutions to some special cases of the considered problems for the following optimization criteria: the weighted sum of completion times and maximum lateness. Some furthermore extensions of the problems are also shown.     

Local search algorithms for the multiprocessor flow shop scheduling problem

The multiprocessor flow shop scheduling problem is a generalization of the ordinary flow shop scheduling problem. The problem consists of both assigning operations to machines and scheduling the operations assigned to the same machine. We review the literature on local search methods for flow shop and job shop scheduling and adapt them to the multiprocessor flow shop scheduling problem. Other local search approaches we consider are variable-depth search and simulated annealing. We show that tabu search and variable-depth search with a neighborhood originated by Nowicki and Smutnicki outperform the other algorithms.     

Recent developments in Dual Resource Constrained (DRC) system research

Real world manufacturing systems are usually constrained by both machine and human resources. Human operators are often the constraining resource and transfer between workstations to process jobs when required. This kind of system is known as a Dual Resource Constrained (DRC) system and presents additional technical challenges which must be considered during planning and scheduling. These technical challenges can be categorised into the five main dimensions of job release mechanisms, job dispatching, worker flexibility, worker assignment and transfer costs. This paper aims to provide an overview of recent developments in DRC research concerned with each of these areas and also discusses some possible approaches to solving the resource scheduling problem in a DRC system. The focus is on materials published after 1995 and up to 2009. Previous reviews on DRC systems are commented on and followed by a review of recent works associated with each of the five dimensions of DRC system research. Advancements made and new methodologies proposed are discussed and future research directions are identified.     

A network solution to a general vehicle scheduling problem

Dantzig and Fulkerson and later Bellmore et al. have shown that certain vehicle (tanker) scheduling problems can be formulated as minimum cost flow problems on a network. In this paper, the results of Dantzig and Fulkerson are extended to the case where more than one type of vehicle can be used in the determination of an optimal fleet. (In tanker scheduling terminology; how many small, medium and large tankers would form an optical fleet.) It is seen how the problem can be formulated as a modified transportation problem where flow in some arcs is conditioned to there being flow on certain other arcs. These “conditional” transportation problems were solved directly as linear programs and showed the peculiarity of terminating all integer in spite of having a constraint matrix, which does not satisfy the well known sufficient conditions for urimodularity. We discuss the implementation of the model and its empirical results.     

Online scheduling of ordered flow shops

We consider online as well as offline scheduling of ordered flow shops with the makespan as objective. In an online flow shop scheduling problem, jobs are revealed to a decisionmaker one by one going down a list. When a job is revealed to the decision maker, its operations have to be scheduled irrevocably without having any information regarding jobs that will be revealed afterwards. We consider for the online setting the so-called Greedy Algorithm which generates permutation schedules in which the jobs on the machines are at all times processed without any unnecessary delays. We focus on ordered flow shops, in particular proportionate flow shops with different speeds and proportionate flow shops with different setup times. We analyze the competitive ratio of the Greedy Algorithm for such flow shops in the online setting. For several cases, we derive lower bounds on the competitive ratios.     

Reducing patient-flow delays in surgical suites through determining start-times of surgical cases

A scheduling strategy to determine starting times of surgeries in multiple operating rooms (OR) is presented. The constraints are resource limit of a downstream facility, post-anesthesia care unit (PACU), and the service time uncertainties. Given sets of surgeries that need to be done on a day, this problem is formulated as a flexible job shop model with fuzzy sets. Patient-waitings in the process flow, clinical resource idling, and total completion times are considered for evaluation. This multi-objective problem is solved by a two-stage decision process. A genetic algorithm is used for determining relative order of surgeries in the first stage and definite starting times for all the surgical cases are obtained by a decision-heuristic in the second stage. The resultant schedule is evaluated by a Monte-Carlo simulation. The performance is shown to be better than our previous approach, a simulation based scheduling which already outperforms simple scheduling rules in regional hospitals. Additionally, the ratio of PACU to OR is examined using the proposed scheduling strategy.     

Application of a Heuristic Scheduling Rule for a Tyre Testing Department

This paper presents the development and application of a heuristic scheduling rule for the Testing Department of a tyre and rubber company. The company had set down five major objectives for this department: (1) minimize average flow-time; (2) maintain an average flow-time of less than two weeks; (3) maintain pre-set maximum individual test flow times; (4) assign a higher priority to important jobs; (5) maintain a balanced mix between truck and passenger tyres. A composite scheduling rule was designed to meet these objectives which contains the following four components: (a) slack-time per remaining operation; (b) shortest processing time; (c) an urgency factor to prioritize important jobs; (d) a balancing factor to enable a desired proportion between truck and passenger tyres. This composite rule is tested against the existing scheduling scheme used by the foreman and against the simple S.P.T. rule. The results are very encouraging.     

Routing and scheduling in a flexible job shop by tabu search

A hierarchical algorithm for the flexible job shop scheduling problem is described, based on the tabu search metaheuristic. Hierarchical strategies have been proposed in the literature for complex scheduling problems, and the tabu search metaheuristic, being able to cope with different memory levels, provides a natural background for the development of a hierarchical algorithm. For the case considered, a two level approach has been devised, based on the decomposition in a routing and a job shop scheduling subproblem, which is obtained by assigning each operation of each job to one among the equivalent machines. Both problems are tackled by tabu search. Coordination issues between the two hierarchical levels are considered. Unlike other hierarchical schemes, which are based on a one-way information flow, the one proposed here is based on a two-way information flow. This characteristic, together with the flexibility of local search strategies like tabu search, allows to adapt the same basic algorithm to different objective functions. Preliminary computational experience is reported.     

基于随机活动工期的现金流动态均衡前摄性与反应性项目调度优化

承包商的现金流动态均衡对不确定条件下项目的顺利实施有重要影响。作者研究基于随机活动工期的现金流动态均衡前摄性及反应性项目调度问题,目标是在随机活动工期条件下,为承包商生成现金流均衡基准进度,并根据执行过程中的实际情况,动态地对其进行反应性调整。首先,通过建立前摄性调度优化模型生成基准进度,并提出两个反应性调度策略对其进行调整。其次,为以上诸模型的求解设计了模拟退火和禁忌搜索相结合的混合算法tabu-SA。最后,针对前摄性调度模型,在随机生成的算例集合上对算法进行测试,并进行大规模仿真实验。研究结果可以为随机活动工期下承包商保持现金流动态均衡、确保项目顺利实施,提供定量化决策支持。     

A survey of scheduling problems with setup times or costs

The first comprehensive survey paper on scheduling problems with separate setup times or costs was conducted by [Allahverdi, A., Gupta, J.N.D., Aldowaisan, T., 1999. A review of scheduling research involving setup considerations. OMEGA The International Journal of Management Sciences 27, 219–239], who reviewed the literature since the mid-1960s. Since the appearance of that survey paper, there has been an increasing interest in scheduling problems with setup times (costs) with an average of more than 40 papers per year being added to the literature. The objective of this paper is to provide an extensive review of the scheduling literature on models with setup times (costs) from then to date covering more than 300 papers. Given that so many papers have appeared in a short time, there are cases where different researchers addressed the same problem independently, and sometimes by using even the same technique, e.g., genetic algorithm. Throughout the paper we identify such areas where independently developed techniques need to be compared. The paper classifies scheduling problems into those with batching and non-batching considerations, and with sequence-independent and sequence-dependent setup times. It further categorizes the literature according to shop environments, including single-machine, parallel machines, flow shop, no-wait flow shop, flexible flow shop, job shop, open shop, and others.     

Decomposition approaches in permutation scheduling problems with application to the M-machine flow shop scheduling problems

In this article, we consider three decomposition techniques for permutation scheduling problems. We introduce a general iterative decomposition algorithm for permutation scheduling problems and apply it to the permutation flow shop scheduling problem. We also develop bounds needed for this iterative decomposition approach and compare its computational requirements to that of the traditional branch and bound algorithms. Two heuristic algorithms based on the iterative decomposition approach are also developed. extensive numerical study indicates that the heuristic algorithms are practical alternatives to very costly exact algorithms for large flow shop scheduling problems.     

Analysis of flow shop scheduling anomalies

Anomalies in flow shop scheduling are rare; only two anomalies have been reported. We present five new anomalies for the permutation flow shop models with the minimum makespan objective and seven more anomalies for the minimum total flow time objective. These anomalies (including the existing ones) are divided into three types corresponding to an increased processing time of a single operation, the addition of a job and the addition of a machine. We derive two properties which, when satisfied, eliminate the possibility of certain anomalies. We conclude that restrictions such as no-delay schedules, no job waiting or no machine idle time (after it starts processing) often result in anomalies. We also show that anomalies can also occur in non-permutation flow shops (four new anomalies presented).     

重入排序问题综述

重入排序问题打破传统假设：工件在加工过程中不止一次地访问某台机器,是一种新型的排序问题. 重入的特点源于半导体生产, 并广泛存在于其他领域. 对重入排序问题已有文献中的成果进行梳理和分析,按问题所处机器环境的不同, 对内容和方法进行分类介绍和总结：包括单机问题、流水作业问题、混合流水作业问题及其他机器环境下的重入排序问题. 最后展望未来的趋势和研究方向.     

A tabu-search heuristic for the flexible-resource flow shop scheduling problem

This paper presents a tabu-search heuristic for the flexible-resource flow shop scheduling (FRFS) problem [7]. The FRFS problem generalizes the classic flow shop scheduling problem by allowing job-operation processing times to depend on the amount of resource assigned to an operation; the objective is to determine simultaneously the job sequence, resource-allocation policy, and operation start times that optimize system performance. The tabu-search heuristic (TSH) employs a nested-search strategy based on a decomposition of the FRFS problem into these three components. We discuss computational experience with the THS procedure on more than 1600 test problems. The results show that TSH is effective in obtaining near-optimal solutions to the FRFS test problems. In particular, TSH generates optimal solutions for more than 70% of the test problems for which optimal solutions are known; overall, these solutions are within 0.3% of optimality on the average, and within 2.5% of optimality in the worst case.This research was supported in part by National Science Foundation grant SES90-22940.     

Trapezoidal type inequalities for n-time differentiable functions

In this paper we consider the flow shop scheduling problems with the effects of learning and deterioration. In this model the processing times of a job is defined as a function of its starting time and position in a sequence. The scheduling objective functions are makespan and total completion time. We prove that even with the introduction of learning effect and deteriorating jobs to job processing times, some special flow shop scheduling problems remain polynomially solvable.     

A contribution to the stochastic flow shop scheduling problem

This paper deals with performance evaluation and scheduling problems in m machine stochastic flow shop with unlimited buffers. The processing time of each job on each machine is a random variable exponentially distributed with a known rate. We consider permutation flow shop. The objective is to find a job schedule which minimizes the expected makespan. A classification of works about stochastic flow shop with random processing times is first given. In order to solve the performance evaluation problem, we propose a recursive algorithm based on a Markov chain to compute the expected makespan and a discrete event simulation model to evaluate the expected makespan. The recursive algorithm is a generalization of a method proposed in the literature for the two machine flow shop problem to the m machine flow shop problem with unlimited buffers. In deterministic context, heuristics (like CDS [Management Science 16 (10) (1970) B630] and Rapid Access [Management Science 23 (11) (1977) 1174]) and metaheuristics (like simulated annealing) provide good results. We propose to adapt and to test this kind of methods for the stochastic scheduling problem. Combinations between heuristics or metaheuristics and the performance evaluation models are proposed. One of the objectives of this paper is to compare the methods together. Our methods are tested on problems from the OR-Library and give good results: for the two machine problems, we obtain the optimal solution and for the m machine problems, the methods are mutually validated.