A modified HOL priority scheduling discipline: Performance analysis

In this paper, we introduce and analyze a modified HOL (head-of-the-line) priority scheduling discipline. The modification is incorporated to cope with the so-called starvation problem of regular HOL priority queues. We consider a discrete-time single-server queueing system with two priority queues of infinite capacity and with the introduced priority scheme. We show that the use of probability generating functions is suitable for analyzing the system contents and the packet delay. Some performance measures (such as means and variances) of these stochastic quantities will be derived. Furthermore, approximate expressions of the tail probabilities are obtained from the probability generating functions, by means of the dominant-singularity method. These expressions, together with their characteristics, constitute one of the main contributions of this paper. Finally, the impact and significance of the m-HOL (modified HOL) priority scheduling on these performance measures is illustrated by some numerical examples.     

Scheduling orders for multiple product types to minimize total weighted completion time

We consider the problem of scheduling orders for multiple different product types in an environment with m dedicated machines in parallel. The objective is to minimize the total weighted completion time. Each product type is produced by one and only one of the m dedicated machines; that is, each machine is dedicated to a specific product type. Each order has a weight and may also have a release date. Each order asks for certain amounts of various different product types. The different products for an order can be produced concurrently. Preemptions are not allowed. Even when all orders are available at time 0, the problem has been shown to be strongly NP-hard for any fixed number (?2) of machines. This paper focuses on the design and analysis of efficient heuristics for the case without release dates. Occasionally, however, we extend our results to the case with release dates. The heuristics considered include some that have already been proposed in the literature as well as several new ones. They include various static and dynamic priority rules as well as two more sophisticated LP-based algorithms. We analyze the performance bounds of the priority rules and of the algorithms and present also an in-depth comparative analysis of the various rules and algorithms. The conclusions from this empirical analysis provide insights into the trade-offs with regard to solution quality, speed, and memory space.     

Multi-level scheduling decisions in a class of FMS using simulation based metamodels

This paper pertains to a detailed simulation study conducted on a typical Flexible Manufacturing System (FMS). Initially, the configurations of the FMS under study have been established. Two types of FMSs have been evolved: one is failure free and the other is failure prone. For each of these cases, simulation models have been developed using SLAMSYSTEM. Orders arriving randomly at the FMS are subjected to three levels of scheduling decisions namely, launching of parts into the system, routing of parts through machines and sequencing of parts on AGVs at a central buffer. The simulation results have been used to develop metamodels for the two types of FMSs. These metamodels have been subjected to statistical analysis to ascertain their adequacy to represent the simulation models. These metamodels have been found to be useful for simulating the FMSs under study so as to evaluate various multi-level scheduling decisions in the FMS.     

Optimal revenue management in two class pre-emptive delay dependent Markovian queues

In this paper, we present a comparative study on the total revenue generated with pre-emptive and non pre-emptive priority scheduler for a fairly generic problem of pricing the server’s surplus capacity in a single server Markovian queue. The specific problem is to optimally price the server’s surplus capacity by introducing a new class of customers (secondary class) without affecting the pre-specified service level of its current customers (primary class) when pre-emption is allowed. Pre-emptive scheduling is used in various applications. First, a finite step algorithm is proposed to obtain global optimal operating and pricing parameters for this problem. These optimal operating and pricing parameters constitute a unique Nash equilibrium in a certain two player non cooperative game. We then describe the range of service level where pre-emptive scheduling gives feasible solution and generates some revenue while non pre-emptive scheduling has infeasible solution. Further, some complementary conditions are identified to compare revenue analytically for certain range of service level where strict priority to secondary class is optimal. Our computational examples show that the complementary conditions adjust in such a way that pre-emptive scheduling always generates more revenue. Theoretical analysis is found to be intractable for the range of service level when pure dynamic policy is optimal. Hence, extensive numerical examples are presented to describe different instances. It is noted in numerical examples that pre-emptive scheduling generates at least as much revenue as non pre-emptive scheduling. A certain range of service level is identified where improvement in revenue is quite significant.     

A heuristic algorithm for a production planning problem in an assembly system

This paper focuses on a production planning problem in an assembly system operating on a make-to-order basis. Due dates are considered as constraints in the problem, that is, tardiness is not allowed. The objective of the problem is to minimise holding costs for final product inventory as well as work-in-process inventory. A non-linear mathematical model is presented and a heuristic algorithm is developed using a solution property and a network model for defining solutions of the problem. A series of computational tests were done to compare the algorithm with a commercial planning/scheduling software and backward finite-loading methods that employ various priority rules. The results showed that the suggested algorithm outperformed the others.     

Job Shop Scheduling with Tooling Constraints: a Tabu Search Approach

Flexible manufacturing systems (FMSs) are automated factories in which many different part types are produced simultaneously. The tool-loading problem now adds further to the delicate task of finding an optimal schedule for such systems. In this paper, a tabu search approach is developed to solve the job shop scheduling problem with tooling constraints.     

Tri-directional Scheduling Scheme: Theory and Computation

In this paper we introduce a new scheduling scheme based on so called tri-directional scheduling strategy to solve the well known resource constrained project scheduling problem. In order to demonstrate the effectiveness of tri-directional scheduling scheme, it is incorporated into a priority rule based parallel scheduling scheme. Theoretical and numerical investigations show that the tri-directional scheduling scheme outperforms forward, backward and even bidirectional schemes depending on the problem structure and the priority rule used. Based on empirical evidence, it seems that as the number of activities are increased, the tri-directional scheduling scheme performs better irrespective of the priority rule used. This suggests that tri-directional scheme should also be applied within the category of heuristic methods.     

An estimation of distribution algorithm for scheduling problem of flexible manufacturing systems using Petri nets

Based on the place-timed Petri net models of flexible manufacturing systems (FMSs), this paper proposes a novel effective estimation of distribution algorithm (EDA) for solving the scheduling problem of FMSs. A candidate solution is represented as an individual with two sections: the first contains the route information while the second is a permutation with repetition for parts. The feasibility of individuals is checked and guaranteed by a highly permissiveness deadlock controller. A feasible individual is interpreted into a deadlock-free schedule while the infeasible ones are amended. The probabilistic model in EDA is constructed via a voting procedure. An offspring individual is then produced based on the model from a seed individual, and the set of seed individuals is extracted by a roulette method from the current population. The longest common subsequence is also embedded into the probabilistic model for mining good genes. A modified variable neighborhood search is applied on offspring individuals to obtain better solutions in their neighbors and hence to improve EDA’s performance. Computational results show that our proposed algorithm outperforms all the existing ones on benchmark examples for the studied problem. It is of important practice significance for the manufacturing of time-critical and multi-type products.     

Dynamic multi-priority,multi-class patient scheduling with stochastic service times

Efficient patient scheduling has significant operational, clinical and economical benefits on health care systems by not only increasing the timely access of patients to care but also reducing costs. However, patient scheduling is complex due to, among other aspects, the existence of multiple priority levels, the presence of multiple service requirements, and its stochastic nature. Patient appointment (allocation) scheduling refers to the assignment of specific appointment start times to a set of patients scheduled for a particular day while advance patient scheduling refers to the assignment of future appointment days to patients. These two problems have generally been addressed separately despite each being highly dependent on the form of the other. This paper develops a framework that incorporates stochastic service times into the advance scheduling problem as a first step towards bridging these two problems. In this way, we not only take into account the waiting time until the day of service but also the idle time/overtime of medical resources on the day of service. We first extend the current literature by providing theoretical and numerical results for the case with multi-class, multi-priority patients and deterministic service times. We then adapt the model to incorporate stochastic service times and perform a comprehensive numerical analysis on a number of scenarios, including a practical application. Results suggest that the advance scheduling policies based on deterministic service times cannot be easily improved upon by incorporating stochastic service times, a finding that has important implications for practice and future research on the combined problem.     

Analysis of discrete-time queueing systems with priority jumps

This text is a summary of the author’s PhD thesis supervised by Herwig Bruneel and Joris Walraevens, and defended on 5 March 2009 at Ghent University. The thesis is written in English and is available from the author upon request. The work deals with several priority scheduling disciplines with so-called priority jumps. An efficient priority scheduling discipline is of great importance in modern telecommunication devices. Static priority scheduling achieves maximum service differentiation between different types of traffic, but may have a too severe impact on the performance of lower-priority traffic. Introducing priority jumps aims for a more gradual service differentiation. In the thesis, we propose several (types of) jumping mechanisms, and we analyse their effect on the performance of a discrete-time queueing system.     

Discrete-time queues with discretionary priorities

In this paper, we consider a discrete-time two-class discretionary priority queueing model with generally distributed service times and per slot i.i.d. structured inputs in which preemptions are allowed only when the elapsed service time of a lower-class customer being served does not exceed a certain threshold. As the preemption mode of the discretionary priority discipline, we consider the Preemptive Resume, Preemptive Repeat Different, and Preemptive Repeat Identical modes. We derive the Probability Generating Functions (PGFs) and first moments of queue lengths of each class in this model for all the three preemption modes in a unified manner. The obtained results include all the previous works on discrete-time priority queueing models with general service times and structured inputs as their special cases. A numerical example shows that, using the discretionary priority discipline, we can more subtly adjust the system performances than is possible using either the pure non-preemptive or the preemptive priority disciplines.     

基于遗传算法的浸染生产排缸策略

针对目前印染企业在浸染生产过程中产品种类和加工设备多、调度复杂的特性，建立了一种用于浸染生产调度的数学模型，并应用遗传算法进行排缸调度求解。以生产任务的分配优先级顺序作为染色体的编码来求解多个生产任务在多个染缸上的调度分配命题，从而得出了最优排缸策略，适用于快速、高效地解决实际生产中大量生产任务调度问题。仿真结果表明了该策略的有效性和实用性。     

The impact of breakdowns disciplines and repeated attempts on performances of Small Cell Networks

This paper aims at presenting an approach to study performance and reliability of Small Cell Networks, taking into account the retrial phenomenon, the finite number of customers (mobiles) served in a cell and the random breakdowns of the base station channels. We consider the classical disciplines namely, active and dependent breakdowns and moreover we propose new breakdowns disciplines, in which we give to the interrupted customers due to a channel failure, a higher priority compared to other customers. To this end, we use the Generalized Stochastic Petri Nets (GSPNs) model as a support. However, one of the major drawbacks of this high-level formalism in performance evaluation of large networks is the state space explosion problem which increases when considering repeated calls and multiple unreliable channels. Hence, the novelty of this investigation is the presentation, for the different breakdowns disciplines with and without priority, of an approach which allows a direct computing of the infinitesimal generator describing the customers behavior and the channels allocation in as small cell, neither generating nor storing the reachability set. In addition, we develop the formulas of the main stationary performance and reliability indices, as a function of the network parameters, the stationary probabilities and independently of the reachability set markings. Through numerical examples, we discuss the effect of retrials, breakdowns disciplines and the priority on performances.     

A preemptive repeat priority queue with resampling: Performance analysis

In this paper, we analyze a discrete-time preemptive repeat priority queue with resampling. High-priority packets have preemptive repeat priority, and interrupted low-priority packets are subjected to independent retransmission attempts. Both classes contain packets with generally distributed transmission times. We show that the use of generating functions is beneficial for analyzing the system contents and packet delay of both classes. The influence of the priority scheduling on the performance measures is illustrated by some numerical examples. This work has been supported by the Interuniversity Attraction Poles Programme–Belgian Science Policy.     

Queueing models for the analysis of communication systems

Queueing models can be used to model and analyze the performance of various subsystems in telecommunication networks; for instance, to estimate the packet loss and packet delay in network routers. Since time is usually synchronized, discrete-time models come natural. We start this paper with a review of suitable discrete-time queueing models for communication systems. We pay special attention to two important characteristics of communication systems. First, traffic usually arrives in bursts, making the classic modeling of the arrival streams by Poisson processes inadequate and requiring the use of more advanced correlated arrival models. Second, different applications have different quality-of-service requirements (packet loss, packet delay, jitter, etc.). Consequently, the common first-come-first-served (FCFS) scheduling is not satisfactory and more elaborate scheduling disciplines are required. Both properties make common memoryless queueing models (M/M/1-type models) inadequate. After the review, we therefore concentrate on a discrete-time queueing analysis with two traffic classes, heterogeneous train arrivals and a priority scheduling discipline, as an example analysis where both time correlation and heterogeneity in the arrival process as well as non-FCFS scheduling are taken into account. Focus is on delay performance measures, such as the mean delay experienced by both types of packets and probability tails of these delays.     

Performance of static priority rules for shared facilities in a remanufacturing shop with disassembly and reassembly

In this paper, we propose a stylized model of a basic remanufacturing shop that handles two remanufacturable products. Product A is comprised of two components A1 and A2, whereas product B is a single entity. After disassembly, component A1 is remanufactured at facility F1; component A2 and product B are remanufactured at facility F2. Both remanufacturing facilities have limited capacity, and are modeled as M/G/1 queues. First, we argue that, under the assumptions of our model, delaying a component to the shop after disassembly, which is a common release mechanism in actual shops, never improves system performance, measured in terms of total weighted average sojourn time (TWAST). Second, we show that the constrained optimal scheduling rule at facility F2 (constrained to simple non-preemptive static priority rules) that minimizes TWAST depends on the processing time characteristics of A1, A2, and B, and can only be found numerically, in general. Using an extensive numerical study based on a numerical approximation for product A's average sojourn time, we show, however, that using FCFS as a scheduling rule at F2 achieves similar TWAST performance, with an average increase of only 7.5%. We also perform a simulation study and show that a two-moment approximation for product A's average sojourn time performs well except for a narrow utilization band.     

Expected waiting times in polling systems under priority disciplines

In this paper, we analyse a service system which consists of several queues (stations) polled by a single server in a cyclic order with arbitrary switchover times. Customers from several priority classes arrive into each of the queues according to independent Poisson processes and require arbitrarily distributed service times. We consider the system under various priority service disciplines: head-of-the-line priority limited to one and semi-exhaustive, head-of-the-line priority limited to one with background customers, and global priority limited to one. For the first two disciplines we derive a pseudo conservation law. For the third discipline, we show how to obtain the expected waiting time of a customer from any given priority class. For the last discipline we find the expected waiting time of a customer from the highest priority class. The principal tool for our analysis is the stochastic decomposition law for a single server system with vacations.     

Platform modelling and scheduling game with multiple intelligent cloud-computing pools for big data

We develop a generic game platform that can be used to model various real-world systems with multiple intelligent cloud-computing pools and parallel-queues for resources-competing users. Inside the platform, the software structure is modelled as Blockchain. All the users are associated with Big Data arrival streams whose random dynamics is modelled by triply stochastic renewal reward processes (TSRRPs). Each user may be served simultaneously by multiple pools while each pool with parallel-servers may also serve multi-users at the same time via smart policies in the Blockchain, e.g. a Nash equilibrium point myopically at each fixed time to a game-theoretic scheduling problem. To illustrate the effectiveness of our game platform, we model the performance measures of its internal data flow dynamics (queue length and workload processes) as reflecting diffusion with regime-switchings (RDRSs) under our scheduling policies. By RDRS models, we can prove our myopic game-theoretic policy to be an asymptotic Pareto minimal-dual-cost Nash equilibrium one globally over the whole time horizon to a randomly evolving dynamic game problem. Iterative schemes for simulating our multi-dimensional RDRS models are also developed with the support of numerical comparisons.     

Analysis of a discrete-time preemptive resume priority buffer

In this paper, we analyze a discrete-time preemptive resume priority queue. We consider two classes of customers which have to be served, where customers of one class have preemptive resume priority over customers of the other. Both classes contain customers with generally distributed service times. We show that the use of probability generating functions is beneficial for analyzing the system contents and customer delays of both classes. It is shown (theoretically as well as by some practical procedures) how moments and approximate tail probabilities of system contents and customer delays are calculated. The influence of the priority scheduling discipline and the service time distributions on the performance measures is shown by some numerical examples.     

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.