An effective mathematical formulation for the unidirectional cluster-based quay crane scheduling problem

The quay crane scheduling problem plays an important role in the paradigm of port container terminal management, due to the fact that it closely relates to vessel berthing time. In this paper, we focus on the study of a special strategy for the cluster-based quay crane scheduling problem that forces quay cranes to move unidirectionally during the scheduling. The scheduling problem arising when this strategy is applied is called the unidirectional quay crane scheduling problem in the literature. Different from other researches attempting to construct more sophisticated searching algorithms, in this paper, we seek for a more compact mathematical formulation of the unidirectional cluster-based quay crane scheduling problem that can be easily solved by a standard optimization solver. To assess the performance of the proposed model, commonly accepted benchmark suites are used and the results indicate that the proposed model outperforms the state-of-the-art algorithms designed for the unidirectional cluster-based quay crane scheduling problem.     

Crossdocking— Just in Time scheduling: an alternative solution approach

In this paper, a scheduling problem which allows a warehouse to function as a crossdock where transit storage time for cargo is minimized according to Just in Time scheduling is studied. A model that uses the machine scheduling notation to describe the problem is written. As the problem is NP-hard, a solution approach based on a combination of two metaheuristics, Reactive GRASP and Tabu Search (RGTS), is provided. Experiments are carried out to determine the usefulness of this approach. The results obtained from the exact method that uses the ILOG CPLEX 9.1 solver for 16 problem instances and the results obtained from the RGTS metaheuristic scheduling algorithm and two other algorithms proposed by other authors for the same problem instances are discussed. Analysis and comparisons are made.     

Scheduling for single agile satellite,redundant targets problem using complex networks theory

Scheduling for the Earth observation satellites (EOSs) imaging mission is a complicated combinatorial optimization problem, especially for the agile EOSs (AEOSs). The increasing observation requirements and orbiting satellites have exacerbated the scheduling complexity in recent years. In this paper, the single agile satellite, redundant observation targets scheduling problem is studied. We introduce the theory of complex networks and find similarities between AEOS redundant targets scheduling problem and the node centrality ranking problem. Then we model this problem as a complex network, regarding each node as a possible observation opportunity, and define two factors, node importance factor and target importance factor, to describe the node/target importance. Based on the two factors, we propose a fast approximate scheduling algorithm (FASA) to obtain the effective scheduling results. Simulation results indicate the FASA is quite efficient and with broad suitability. Our work is helpful in the EOSs and AEOSs scheduling problems by using complex network knowledge.     

基于运行时间预测的枢纽内多线路协调调度研究

针对传统调度模型预见性不强的弱点,提出一个基于支持向量机(SVM)的公交车辆到达枢纽时间的预测模型,基于该模型构建以所有乘客节约时间最大为目标的调度模型,动态协调公交车辆从枢纽的发车时间,并基于遗传算法对该模型进行求解。最后,我们以大连市沙河口火车站枢纽为实例,对该模型和算法的可行性进行了检验,结果显示,本文提出的调度方法优于传统调度策略。     

Games,Critical Paths and Assignment Problems in Permutation Flow Shops and Cyclic Scheduling Flow Line Environments

In this paper we address the non-pre-emptive flow shop scheduling problem for makespan minimization in a new modelling framework. A lower bound generation scheme is developed by using appropriately defined linear assignment problems and, based on this new approach, a special class of permutation flow shop problems is identified. We present a game theoretic interpretation of our modelling approach which leads to an integer programming formulation of the scheduling problem. A new branch and bound scheme is developed based on these results. The major advantage of our modelling framework and branch-and- bound approach is that it can be easily extended to address a general class of cyclic scheduling problems for production flow lines with blocking. After a discussion of this extension, we report on computational experience that indicates the very satisfactory performance of the new optimal solution procedure for cyclic scheduling problems with finite capacity buffers.     

A comprehensive approach of planning and scheduling based on petri nets

The main results available on the use of black-and-white Petri nets for modelling, planning and scheduling manufacturing systems are presented. In the first part of the paper, the basics of Petri nets necessary to understand the subsequent presentation are introduced. Particular attention is paid to event graphs, a particular type of Petri nets used for modelling and evaluating ratio-driven systems. The second part of the paper is devoted to ratio-driven systems, their modelling and their scheduling. Job-shops, assembly systems, and KANBAN systems are used to illustrate this section. Finally, the general case is investigated of manufacturing systems subject to changing demands. An approach based on conflict-free Petri nets with input and output transitions is proposed for planning and scheduling this type of system.     

Time complexity of single machine scheduling with stochastic precedence constraints

This paper deals with single machine scheduling problems with stochastic precedence relations (so calledGERT networks). Until now most investigations on such problems, dealt with algorithms running in polynomial time. On the other hand, for scheduling problems with deterministic precedence relations exist a lot of results about time complexity. Therefore, the object of this paper is to consider time complexity of scheduling problems with stochastic precedence constraints and to describe the boundary between theNP-hard problems and those which can be solved in polynomial time.     

Genetic algorithm-based subproblem solution procedures for a modified shifting bottleneck heuristic for complex job shops

In this paper, we consider a modified shifting bottleneck heuristic for complex job shops. The considered job shop environment contains parallel batching machines, machines with sequence-dependent setup times and reentrant process flows. Semiconductor wafer fabrication facilities (Wafer Fabs) are typical examples for manufacturing systems with these characteristics. Our primary performance measure is total weighted tardiness (TWT). The shifting bottleneck heuristic uses a disjunctive graph to decompose the overall scheduling into scheduling problems for single tool groups. The scheduling algorithms for these scheduling problems are called subproblem solution procedures (SSPs). In previous research, only subproblem solution procedures based on dispatching rules have been considered. In this paper, we are interested in how much we can gain in terms of TWT if we apply more sophisticated subproblem solution procedures like genetic algorithms for parallel machine scheduling. We conduct simulation experiments in a dynamic job shop environment in order to assess the performance of the suggested subproblem solution procedures. It turns out that using near to optimal subproblem solution procedures leads in many situations to improved results compared to dispatching-based subproblem solution procedures.     

A solution for cyclic scheduling of multi-hoists without overlapping

In this paper, we study the cyclic scheduling problem for electroplating lines where products are loaded into the system at one end and unloaded at the other end. The electroplating jobs must be processed within a given time window in each tank. There is no buffer between tanks. Two hoists sharing a common track are used to move products between the tanks in the production line. The objective is to minimize the production cycle time through scheduling hoist moves. A solution procedure is proposed in this study. The production line is first divided into two non-overlapping zones with a hoist assigned to each zone. Then a mixed integer linear programming model is developed for scheduling hoist moves. Computational results on a benchmark example problem are given in the paper to demonstrate the application of the proposed method.     

A note on an iterative forward/backward scheduling technique with reference to a procedure by Li and Willis

In this note we propose an iterative scheduling technique which consists of consecutive forward/backward scheduling passes aimed at reducing the project duration by smoothing out the project's resource profile. The idea of iterative scheduling is initiated by Li and Willis in their related paper. The only common point between their scheduling technique and the one proposed here is the iterative feature. The two techniques differ both in algorithmic aspects and in the way activities are selected for scheduling at a decision point. In the technique proposed here activities are evaluated by well-reputed dispatching rules and a conflict based decision-making process called Local Constraint Based Analysis (LCBA). The results on benchmark problems from the literature demonstrate that LCBA specifically exploits the flexible activity time windows provided by the iterative scheduling technique.     

A Rollout Metaheuristic for Job Shop Scheduling Problems

In this paper we deal with solution algorithms for a general formulation of the job shop problem, called alternative graph. We study in particular the job shop scheduling problem with blocking and/or no-wait constraints. Most of the key properties developed for solving the job shop problem with infinite capacity buffer do not hold in the more general alternative graph model. In this paper we report on an extensive study on the applicability of a metaheuristic approach, called rollout or pilot method. Its basic idea is a look-ahead strategy, guided by one or more subheuristics, called pilot heuristics. Our results indicate that this method is competitive and very promising for solving complex scheduling problems.     

并行多机调度问题的一种遗传算法

运用遗传算法对最小化完工时间的并行多机调度问题进行了研究，给出了最小完工时间的一个下界，由此提出了初始种群的一种构造方法，并用计算实例表明该方法适用于大规模并行多机调度问题     

A Microcomputer Based Solution to a Practical Scheduling Problem

This paper presents a scheduling problem with constraints imposed on the waiting time between stages. The process in which it occurs involves the preparation, cooking and chilling of meals. A maximum of 30 min is permitted for waiting between the completion of the cooking stage and the start of chilling down to temperature of <3°C. If this is not achieved, then the food has to be discarded. Clearly the scheduling of the final cooking stage and chilling facilities is crucial in this context. The development of a procedure to do this scheduling, using a microcomputer, is described and some typical results presented. Further uses of the model are briefly outlined.     

Solving the discrete-continuous project scheduling problem via its discretization

In this paper a discrete-continuous project scheduling problem is considered. In this problem activities simultaneously require discrete and continuous resources. The processing rate of each activity depends on the amount of the continuous resource allotted to this activity at a time. All the resources are renewable ones. The activities are nonpreemtable and the objective is to minimize the makespan. Discretization of this problem leading to a classical (i.e. discrete) project scheduling problem in the multi-mode version is presented. A simulated annealing (SA) approach to solving this problem is described and tested computationally in two versions: with and without finding an optimal continuous resource allocation for the final schedule. In the former case a nonlinear solver is used for solving a corresponding convex programming problem. The results are compared with the results obtained using SA for the discrete-continuous project scheduling problem where the nonlinear solver is used for exact solving the continuous part in each iteration. The results of a computational experiment are analyzed and some conclusions are included.     

A scatter search algorithm for project scheduling under partially renewable resources

In this paper we develop a heuristic algorithm, based on Scatter Search, for project scheduling problems under partially renewable resources. This new type of resource can be viewed as a generalization of renewable and non-renewable resources, and is very helpful in modelling conditions that do no fit into classical models, but which appear in real timetabling and labor scheduling problems. The Scatter Search algorithm is tested on existing test instances and obtains the best results known so far.     

Packing problems and project scheduling models: an integrating perspective

This paper considers two problem classes, namely packing and project scheduling problems that are important to researchers as well as practitioners. The two problem categories are described, and a classification is given for the different kinds of packing problems and project scheduling concepts. While both problem classes are different with respect to their fields of application, similarities of their mathematical structures are examined. It is shown that all packing problems considered here are special cases of models for project scheduling. The aim is to indicate which project scheduling models can be used to capture the different types of packing problems. Finally, some implications for research on optimisation algorithms for these two problem classes are discussed, and the applicability of the results of this work in practice are pointed out.     

Single machine scheduling to minimize weighted earliness subject to no tardy jobs

This paper considers the single machine scheduling problem where the objective is to minimize the total weighted earliness subject to no tardy jobs. Known results for a well researched single machine scheduling problem where the objective is to minimize the weighted completion time subject to no tardy jobs have been used in analyzing this problem. Several important results are proved and both exact and approximate methods are developed to solve this problem.     

随机环境下基于成本经济的项目调度权衡优化研究

针对随机环境下项目前摄性调度与反应性调度在应对不确定因素过程中起到的不同作用,从成本经济角度出发,研究了如何通过两种调度方法的权衡实现项目计划与执行的最优配合。在此基础上构建了基于成本的前摄反应调度权衡模型,通过对鲁棒性成本与调整成本进行量化分析,实现两种调度方案的最佳权衡。考虑到问题的NP难属性,设计了基于混合变邻域禁忌搜索的随机两点启发式算法,并通过大规模算例测试验证了算法的有效性。结果表明,根据承包商对成本的敏感度,前摄性调度与反应性调度在应对不确定性因素干扰中承担的工作量会随着成本权衡比的变化而发生改变,逐渐从前摄性方法为主过渡到以反应性方法为主。最后,从项目管理角度给出了有价值的管理启示。     

实时系统中单处理器调度算法的优化设计研究

研究实时系统的建模与调度问题是运筹与控制领域研究的热点问题, 对实时系统中的单处理器的调度算法进行了分析与研究, 特别是对其中的单调速率算法和最早时间限优先算法进行了深入的研究, 指出单调速率算法是一种典型的静态调度算法, 并且证明了单调速率算法是单处理器最优的静态优先级调度算法, 同时还指出最早时间限优先算法是一种典型的动态优先级调度算法,证明了最早时间限优先算法是单处理器的最优的动态优先级调度算法. 最后, 为了更好地进行实时系统的建模与调度, 引入了一种新的对任务执行行为进行抽象的方法--T-LET平面方法, 利用这种方法建立了单处理器流调度模型和BLREF调度算法, 并指出这种模型和算法都具有很强的几何背景.     

The resource-constrained modulo scheduling problem: an experimental study

In this paper, we focus on the resource-constrained modulo scheduling problem (RCMSP), a general periodic scheduling problem, abstracted from the problem solved by compilers when optimizing inner loops at instruction level for VLIW parallel processors. Heuristic solving scheme have been proposed since many years to solve this problem, among which the decomposed software pipeling method. In this method, a cyclic scheduling problem ignoring resource constraints is first considered and a so-called legal retiming of the operations is issued. Second, a standard acyclic problem, taking this retiming as input, is solved through list scheduling techniques. In this paper, we propose a novel hybrid approach, which uses the decomposed software pipeling method to obtain a good retiming. Then the obtained retiming is used to build an integer linear programming formulation of reduced size, which allows to solve it exactly. Experimental results show that a lot more problems are solved with this new approach. The gap to the optimal solution is less than 1 % on most of the tested problem instances and the method appears to be competitive with a recently proposed constraint programming algorithm (Bonfietti et al., Lect. Notes Comput. Sci. 6876:130–144, 2011).