Numerical analysis of a discrete-time finite capacity queue with a burst arrival

We study a discrete-time, multi-server, finite capacity queue with a burst arrival. Once the first job of a burst arrives at the queue, the successive jobs will arrive every time slot until the last job of the burst arrives. The number of jobs and the inter-arrival time of bursts are assumed to be generally distributed, and the service time is assumed to be equal to one slot. We propose an efficient numerical method to exactly obtain the job loss probability, the waiting time distribution and the mean queue length using an embedded Markov chain at the arrival instants of bursts.     

Optimal admission policies for a finite queue with bursty arrivals

We consider a service system with a single server, a finite waiting room and two classes of customers with deterministic service time. Primary jobs arrive at random and are admitted whenever there is room in the system. At the beginning of each period, secondary jobs can be admitted from an infinite pool. A revenue is earned upon admission of each job, with the primary jobs bringing a higher contribution than the secondary jobs, the objective being to maximize the total discounted revenue over an infinite horizon. We model the system as a discrete time Markov decision process and show that a monotone admission policy is optimal when the number of primary arrivals has a fixed distribution. Moreover, when the primary arrival distribution varies with time according to a finite state Markov chain, we show that the optimal policy is conditionally monotone and that the numerical computation of an optimal policy, in this case, is substantially more difficult than in the case of stationary arrivals.This research was supported in part by the National Science Foundation, under grant ECS-8803061, while the author was at the University of Arizona.     

具有两个不相容工件族单位工件的有界分批在线排序问题

研究具有两个不相容工件族单位工件单机有界平行分批的在线排序问题.工件按时在线到达,目标是最小化最大完工时间.在有界平行分批排序中,容量有限制机器最多可将b个工件形成一批同时加工,每个工件及每一批的加工时间为1.不相容工件族是指来自不同工件组的工件不能放在同一批加工.对该问题提供了一个竞争比为√17+3/4的最好可能的在线算法.     

Scheduling on a Batch Processing Machine with Split Compatibility Graphs

We consider the problem of minimizing the makespan on a batch processing machine, in which jobs are not all compatible. Only compatible jobs can be included into the same batch. This relation of compatibility is represented by a split graph. All jobs are available at the same date. The capacity of the batch processing machine is finite or infinite. The processing time of a batch is given by the processing time of the longest job in the batch. We establish the NP-hardness of the general problem and present polynomial algorithms for several special cases.     

Scheduling of plant maintenance personnel

Given (i) a set of maintenance jobs to be processed over a fixed time horizon, (ii) the breakdown of each job into finite time intervals in which the skills required are known, and (iii) the pool of available manpower for each skill type over the horizon, we formulate and solve the problem of scheduling personnel and jobs to minimize personnel idle time, by integer programming.     

含有批处理机的三机流水作业加工总长问题在某些情形下的强NP困难性

本文研究含有批处理机的三台机器流水作业加工总长问题在某些情形下的计算复杂性。在批处理机上同时加工的工件组成一个工件批，一个工件批的所有工件同时开始、同时结束。当批处理机的容量有限时，我们证明了下列情形为强NP困难的：第一台机器是批处理机、其余两台机器是单机；第二台机器是单机、其余两台机器是批处理机；第三台机器是批处理机、其余两台机器是单机。     

Processing games with restricted capacities

This paper analyzes processing problems and related cooperative games. In a processing problem there is a finite set of jobs, each requiring a specific amount of effort to be completed, whose costs depend linearly on their completion times. The main feature of the model is a capacity restriction, i.e., there is a maximum amount of effort per time unit available for handling jobs. There are no other restrictions whatsoever on the processing schedule.Assigning to each job a player and letting each player have an individual capacity for handling jobs, each coalition of cooperating players in fact faces a processing problem with the coalitional capacity being the sum of the individual capacities of the members. The corresponding processing game summarizes the minimal joint costs for every coalition. It turns out that processing games are totally balanced. The proof of this statement is constructive and provides a core element in polynomial time.     

资源量与开工时刻限制下航空公司地面作业调度问题

根据航空公司实际地面作业背景,提出了一个资源量与开工时刻双重限制下的排序模型.已知有若干个任务和有限的资源量,每个任务有一个到达时刻及要求完工期限.以极小化最大的延误时间为目标给出了一个启发式的多项式算法,并界定了近似解与最优解的误差范围.     

单位工件的平行机并行分批在线排序问题的算法

本文研究一类批容量有界的并行分批、平行机在线排序问题。模型中有n个相互独立的工件J={J₁,…,J_n}要在m台批处理机上加工。批处理机每次可同时加工至多B(Bj(1≤j≤n)的到达时间为r_j,加工时间为1,工件是否会到达事先未知,而只有等到工件的到达时间才能获知它的到达。目标为最小化工件的最大完工时间。针对该排序问题,本文设计了两个竞争比均达到最好可能的在线算法。     

Modelling and scheduling of an asynchronous cyclic production line with multiple parts

In this study, we model and analyse a production line with asynchronous part transfers, processing time variability, and cyclic scheduling in the same framework. We consider a production line with multiple parts and finite interstation buffers. The line produces a batch of n jobs repetitively using the same order of jobs in every batch. The processing time of a job on a station is a random variable and is assumed to have a phase-type distribution. Parts are transferred between the stations in an asynchronous manner. We first present a continuous time Markov chain model to analyse the performance of this system for a given sequence. A state-space representation of the model and the associated rate matrix are generated automatically. The steady state probabilities of the Markov chain are determined by using a recursive method that exploits the special structure of the rate matrix. The cycle time, the production rate, and the expected Work-In-Progress (WIP) inventory are used as the main performance measures. We then present an approximate procedure to determine the cyclic sequence that minimises the cycle time. We then investigate the effects of operating decisions, system structure, processing time variability, and their interaction in the same framework. Numerical results for the performance evaluation and scheduling of cyclic production lines are also presented.     

An Eigenvalue Approach to Analyzing a Finite Source Priority Queueing Model

In this paper, we present a novel approach to determining the steady-state distribution for the number of jobs present in a 2-class, single server preemptive priority queueing model where the low priority source population is finite. Arrivals are assumed to be Poisson with exponential service times. The system investigated is a quasi birth and death process, and the joint distribution is derived via the method of generalized eigenvalues. Using this approach, we are able to obtain all eigenvalues and corresponding eigenvectors explicitly. Furthermore, we link this method to the matrix analytic approach by obtaining an explicit solution for the rate matrix R. Two numerical examples are given to illustrate the procedure and highlight some important computational features.     

Optimal on-line flow time with resource augmentation

We study the problem of scheduling n jobs that arrive over time. We consider a non-preemptive setting on a single machine. The goal is to minimize the total flow time. We use extra resource competitive analysis: an optimal off-line algorithm which schedules jobs on a single machine is compared to a more powerful on-line algorithm that has ? machines. We design an algorithm of competitive ratio , where Δ is the maximum ratio between two job sizes, and provide a lower bound which shows that the algorithm is optimal up to a constant factor for any constant ?. The algorithm works for a hard version of the problem where the sizes of the smallest and the largest jobs are not known in advance, only Δ and n are known. This gives a trade-off between the resource augmentation and the competitive ratio.We also consider scheduling on parallel identical machines. In this case the optimal off-line algorithm has m machines and the on-line algorithm has ?m machines. We give a lower bound for this case. Next, we give lower bounds for algorithms using resource augmentation on the speed. Finally, we consider scheduling with hard deadlines, and scheduling so as to minimize the total completion time.     

On-line scheduling on a batch machine to minimize makespan with limited restarts

We study the on-line scheduling on an unbounded batch machine to minimize makespan. In this model, jobs arrive over time and batches are allowed limited restarts. Any batch that contains a job which has already been restarted once cannot be restarted any more. We provide a best possible on-line algorithm for the problem with a competitive ratio .     

Lagrangian relaxation algorithms for real-time hybrid flowshop scheduling with finite intermediate buffers

We investigate the problem of scheduling N jobs on parallel identical machines in J successive stages with finite buffer capacities between consecutive stages in a real-time environment. The objective is to find a schedule that minimizes the sum of weighted completion time of jobs. This problem has proven strongly NP-hard. In this paper, the scheduling problem is formulated as an integer programming model considering buffers as machines with zero processing time. Lagrangian relaxation algorithms are developed combined with a speed-up dynamic programming approach. The complication and time consumption of solving all the subproblems at each iteration in subgradient optimization motivate the development of the surrogate subgradient method, where only one subproblem is minimized at each iteration and an adaptive multiplier update scheme of Lagrangian multipliers is designed. Computational experiments with up to 100 jobs show that the designed surrogate subgradient algorithm provides a better performance as compared to the subgradient algorithm.     

A performance analysis of dispatching rules and a heuristic in static flowshops with missing operations of jobs

An experimental investigation of the performance of dispatching rules and a heuristic for scheduling in static flowshops with missing operations is undertaken in this study. The measure of performance is the minimization of total flow time of jobs. Permutation schedules are generated by using the heuristic for scheduling. General schedules, which can be permutation or non-permutation schedules, are obtained by using dispatching rules. Four dispatching rules, including a new dispatching rule, are considered. Two types of flowshops are studied: one with no missing operations of jobs and another with missing operations of jobs. In the latter type of flowshops, jobs with varying number of missing operations are considered. An extensive investigation of the performance of the dispatching rules and the heuristic is carried out. It is observed that the heuristic minimizes total flow time of jobs more than dispatching rules up to a certain level of missing operations of jobs in flowshops, after which dispatching rules perform better. The performance of the heuristic and the dispatching rules in terms of minimizing the makespan as a secondary measure is also reported.     

On a methodology for discrete–continuous scheduling

Discrete–continuous problems of scheduling nonpreemptable jobs on parallel machines are considered. The problems arise e.g. when jobs are assigned to multiple parallel processors driven by a common electric, hydraulic or pneumatic power source. Existing models have assumed job processing rates as a function of the number of jobs currently being processed, or equivalently the number of machines currently in operation. In this paper a more general model is proposed in which processing rates of a job assigned to a machine depend on the amount of a continuous, i.e. continuously divisible resource (e.g. power) allotted to this job at a time. Thus the problem consists of two interrelated subproblems: (i) to sequence jobs on machines, and (ii) to allocate the continuous resource among jobs already sequenced. We provide a comprehensive analysis of the problem. This includes properties of optimal schedules, efficiently (in particular analytically) solvable cases, formulations of the possibly simplest mathematical programming problems for finding optimal schedules in the general case, heuristics and the worst-case analysis. Although our objective function in this paper is to minimize makespan of a set of independent jobs, the presented methodology can be applied to other criteria, precedence-related jobs, and many resource types (apart from, or instead of machines).     

Flexible job shop scheduling problem for parallel batch processing machine with compatible job families

Flexible Job-Shop Scheduling Problem (FJSP) with Parallel Batch processing Machine (PBM) is studied. First, a Mixed Integer Programming (MIP) formulation is proposed for the first time. In order to address an NP-hard structure of this problem, the formulation is modified to selectively schedule jobs. Although there are many jobs on a given floor, semiconductor manufacturing is most challenged by priority jobs that promise a significant amount of financial compensation in exchange for an expedited delivery. This modification could leave some non-priority jobs unscheduled. However, it vastly expedites the discovery of improving solutions by first branching on integer variables with higher priority jobs. This study then turns job-dependent processing times into job-independent ones by assuming a machine has an equal processing time on different jobs. This assumption is roughly true or acceptable for the sake of the reduced computational time in the industry. These changes significantly reduce computational time compared to the original model when tested on a set of common problem instances from the literature. Computational results show that this proposed model can generate an effective schedule for large problems. Author encourages other researchers to propose an improved MIP model.     

Dynamic Scheduling on a Single Batch Processing Machine with Split Compatibility Graphs

We consider the problem of minimizing the makespan on a batch processing machine, in which jobs are not all compatible. Only compatible jobs can be included into the same batch. This relation of compatibility is represented by a split graph. Jobs have release dates. The capacity of the batch processing machine is finite or infinite. The processing time of a batch is given by the processing time of the longest job in the batch. We establish the NP-hardness of the general problem and present polynomial algorithms for several special cases. Relating scheduling theory and graph theory appears to be an interesting and important concept.     

Interval Scheduling on identical machines

Interval Scheduling problems (IS) address the situation where jobs with fixed start and fixed end times are to be processed on parallel identical machines. The optimization criteria of interest are the maximization of the number of jobs completed and, in case weights are associated with jobs, the subset of jobs with maximal total weight. We present polynomial solutions to several IS problems and study computational complexity issues in the situation where bounds are imposed on the total operating time of the machines. With this constraint, we show that tractability is achieved again when job preemption is allowed.     

Integrated production and delivery scheduling with disjoint windows

Consider a company that manufactures perishable goods. The company relies on a third party to deliver goods, which picks up delivery products at regular or irregular times. At each delivery time, there is a time window that products can be produced to be delivered at that delivery time. The time windows are disjoint. Suppose we have a set of jobs with each job specifying its delivery time, processing time and profit. The company can earn the profit if the job is produced and delivered at its specified delivery time. From the company point of view, we are interested in picking a subset of jobs to produce and deliver so as to maximize the total profit. The unpicked jobs will be discarded without penalty. We consider both the single machine case and the parallel and identical machine case.In this article we consider three kinds of profits: (1) arbitrary profit, (2) equal profit, and (3) profit proportional to its processing time. In the first case, we give a fully polynomial time approximation scheme (FPTAS) for a single machine with running time . Using the bound improvement technique of Kovalyov, the running time can be further reduced to . In the second case, we give an O(nlogn)-time optimal algorithm for a single machine. In the third case, we give an FPTAS for a single machine with running time . All of our algorithms can be extended to parallel and identical machines with a degradation of performance ratios.