Data structures with dynamical random transitions

We present a (non‐standard) probabilistic analysis of dynamic data structures whose sizes are considered dynamic random walks. The basic operations (insertion, deletion, positive and negative queries, batched insertion, lazy deletion, etc.) are time‐dependent random variables. This model is a (small) step toward the analysis of these structures when the distribution of the set of histories is not uniform. As an illustration, we focus on list structures (linear lists, priority queues, and dictionaries) but the technique is applicable as well to more advanced data structures. © 2005 Wiley Periodicals, Inc. Random Struct. Alg., 2006     

A priority list based heuristic for the job shop problem

A priority list for the job shop scheduling problem is defined to be any permutation of a set of symbols where the symbol for each job appears as many times as the number of its operations. Every priority list can be associated in a natural way with a feasible schedule, and every feasible schedule arises in this way. Priority lists are therefore a representation of feasible schedules that avoid the problems normally associated with schedule infeasibility. As a result, the three ingredients of local search heuristics, namely picking initial starting schedules, constructing search neighbourhoods and computing makespans, become faster and easier when performed in the space of priority lists rather than in the space of feasible schedules. As an illustration of their usefulness, a priority list based simulated annealing heuristic is presented, which, although simple, is competitive with the current leading schedule based simulated annealing and tabu search heuristics.     

带有阈值转换和启动时间的优先权排队

在诸如ＩＳＤＮ的通信网络中,多种信息共用一条线路,为了满足不同类型信息的服务质量要求,带有阈值转换的优先权排队系统应是一种合适的模型。本文研究单服务员、两类顾客的带有阈值转换和启动时间的优先权排队系统,首先,分别就抢占和非抢占情形讨论了具有泊松到达、服务时间和启动时间均有指数贩系统,然后就非抢占情况进上步考虑了服务时间和启动时间有一般分布的系统,求出了系统中两类顾客队长的稳态联合概率母函数,藉助这     

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.     

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.     

Blossom V: a new implementation of a minimum cost perfect matching algorithm

We describe a new implementation of the Edmonds’s algorithm for computing a perfect matching of minimum cost, to which we refer as Blossom V. A key feature of our implementation is a combination of two ideas that were shown to be effective for this problem: the “variable dual updates” approach of Cook and Rohe (INFORMS J Comput 11(2):138–148, 1999) and the use of priority queues. We achieve this by maintaining an auxiliary graph whose nodes correspond to alternating trees in the Edmonds’s algorithm. While our use of priority queues does not improve the worst-case complexity, it appears to lead to an efficient technique. In the majority of our tests Blossom V outperformed previous implementations of Cook and Rohe (INFORMS J Comput 11(2):138–148, 1999) and Mehlhorn and Schäfer (J Algorithmics Exp (JEA) 7:4, 2002), sometimes by an order of magnitude. We also show that for large VLSI instances it is beneficial to update duals by solving a linear program, contrary to a conjecture by Cook and Rohe.     

Delay analysis of discrete-time priority queue with structured inputs

This paper investigates a discrete-time priority queue with multi-class customers. Applying a delay-cycle analysis, we explicitly derive the probability generating function of the waiting time for an individual class in a geometric batch input queue under preemptive-resume and head-of-the-line priority rules. The conservation law and waiting time characterization for a general class of discrete-time queues are also presented. The results in this paper cover several previous results as special cases.     

Scheduling in Multiclass Networks with Deterministic Service Times

We consider general feed-forward networks of queues with deterministic service times and arbitrary arrival processes. There are holding costs at each queue, idling may or may not be permitted, and servers may fail. We partially characterize the optimal policy and give conditions under which lower priority should be given to jobs that would be delayed later in the network if they were processed now.     

带有转换时间和阀值的非抢占优先权排队模型

在[3]中,我们研究了在抢占规则下带有转换时间和阈值的两类顾客优先权排队系统,本文就非抢占情形对这样的系统作进一步的研究,同样求出两类顾客队长的稳态联合概率母函数。籍助这些母函数可求出诸如平均队长这样一些重要的系统性能指标。     

Two competing discrete-time queues with priority

This paper considers a class of two discrete-time queues with infinite buffers that compete for a single server. Tasks requiring a deterministic amount of service time, arrive randomly to the queues and have to be served by the server. One of the queues has priority over the other in the sense that it always attempts to get the server, while the other queue attempts only randomly according to a rule that depends on how long the task at the head of the queue has been waiting in that position. The class considered is characterized by the fact that if both queues compete and attempt to get the server simultaneously, then they both fail and the server remains idle for a deterministic amount of time. For this class we derive the steady-state joint generating function of the state probabilities. The queueing system considered exhibits interesting behavior, as we demonstrate by an example.     

A dynamic multi-objective location-allocation model for search and rescue assets

This paper presents a dynamic multi-objective mixed integer linear programming model to optimize the location and allocation of search and rescue (SAR) boats and helicopters to enhance the performance of maritime SAR missions. Our model incorporates simulated incident scenarios to account for demand uncertainty and allows relocation of vessels seasonally. We define three objectives as responding to incidents within a critical time, generating a balanced workload distribution among vessels of various types, and minimizing costs associated with operations and vessel relocations. Implementing a goal programming approach, we solve the problem for various objective function term weights and compare the performance of each solution with respect to 10 different metrics. Using historical incident datasets for the Aegean Sea, we show that the proposed model and solution approach can significantly improve the SAR performance and provide decision support for planners in developing effective and efficient resource location-allocation schemes.     

Calculation of output characteristics of a priority queue through a busy period analysis

In this paper, we analyze some output characteristics of a discrete-time two-class priority queue by means of probability generating functions. Therefore, we construct a Markov chain which – after analysis – provides a.o. the probability generating functions of the lengths of the busy periods of both classes. It is furthermore shown how performance measures, related to the output process, are calculated from these functions. The queueing model is kept fairly simple to explain the method of analysis of the busy periods and the output characteristics of priority queues as clearly as possible.     

Cooperation in Markovian queueing models

In this paper we study some cooperative models in Markovian queues. We stress the case of several agents agreeing to maintain a common server for their populations in which a priority scheme with preemption has been established. In this situation we propose and characterize an allocation rule for the holding costs that provides core allocations.     

Planning and scheduling of selective harvest with management zones delineation

This paper considers an integrated approach to two common problems in a precision agriculture framework: management zone delineation and selective harvest scheduling. Our model minimizes the total costs of harvest operations, establishing planning and scheduling for selective harvest of each selected management zone. Therefore, this tool provides important information for decision making of farmers in the field. Our integrated model is contrasted with the hierarchical approach commonly used in the literature for these cases, where the result of zoning problem is an input to schedule the harvest problem. Both problems were solved through a complete enumeration of all the potential management zones and demonstrated the advantages of our proposed model over the hierarchical approach. Our model reached an average reduction of 10% in harvest operations costs for different instances in a case study.

     

Waiting time distributions in the accumulating priority queue

We are interested in queues in which customers of different classes arrive to a service facility, and where performance targets are specified for each class. The manager of such a queue has the task of implementing a queueing discipline that results in the performance targets for all classes being met simultaneously. For the case where the performance targets are specified in terms of ratios of mean waiting times, as long ago as the 1960s, Kleinrock suggested a queueing discipline to ensure that the targets are achieved. He proposed that customers accumulate priority as a linear function of their time in the queue: the higher the urgency of the customer’s class, the greater the rate at which that customer accumulates priority. When the server becomes free, the customer (if any) with the highest accumulated priority at that time point is the one that is selected for service. Kleinrock called such a queue a time-dependent priority queue, but we shall refer to it as the accumulating priority queue. Recognising that the performance of many queues, particularly in the healthcare and human services sectors, is specified in terms of tails of waiting time distributions for customers of different classes, we revisit the accumulating priority queue to derive its waiting time distributions, rather than just the mean waiting times. We believe that some elements of our analysis, particularly the process that we call the maximum priority process, are of mathematical interest in their own right.     

An efficient implementation of the robust tabu search heuristic for sparse quadratic assignment problems

We propose and develop an efficient implementation of the robust tabu search heuristic for sparse quadratic assignment problems. The traditional implementation of the heuristic applicable to all quadratic assignment problems is of O(N²) complexity per iteration for problems of size N. Using multiple priority queues to determine the next best move instead of scanning all possible moves, and using adjacency lists to minimize the operations needed to determine the cost of moves, we reduce the asymptotic (N → ∞) complexity per iteration to O(N log N). For practical sized problems, the complexity is O(N).     

A finite capacity multi-queueing system with priorities and with repeated server vacations

In this paper, we study an M/G/1 multi-queueing system consisting ofM finite capacity queues, at which customers arrive according to independent Poisson processes. The customers require service times according to a queue-dependent general distribution. Each queue has a different priority. The queues are attended by a single server according to their priority and are served in a non-preemptive way. If there are no customers present, the server takes repeated vacations. The length of each vacation is a random variable with a general distribution function. We derive steady state formulas for the queue length distribution and the Laplace transform of the queueing time distribution for each queue.     

Scheduling farm operations

Scheduling operations on a farm is considered depending on the available men and machinery and on the influence of the weather on materials (moisture content). A simulation model with a heuristic strategy for selecting operations at each moment of decision based on the state of the system and a linear programming model are used in the grain harvest to demonstrate the influence of the models on the resulting variable costs (overtime, drying of wet grain and timeliness losses of wheat and straw) and the influence of input data (weather, attributes of material and number of workable hours) on those costs. The lower costs found with simplified input (hourly, daily, weekly data) in simulation is continued with the linear programming model due to its deviation from the real workable time constraints and decision variables. Such a tendency suggests that LP-models usual in agricultural planning are too simple.     

Mixed gated/exhaustive service in a polling model with priorities

In this paper we consider a single-server polling system with switch-over times. We introduce a new service discipline, mixed gated/exhaustive service, that can be used for queues with two types of customers: high and low priority customers. At the beginning of a visit of the server to such a queue, a gate is set behind all customers. High priority customers receive priority in the sense that they are always served before any low priority customers. But high priority customers have a second advantage over low priority customers. Low priority customers are served according to the gated service discipline, i.e. only customers standing in front of the gate are served during this visit. In contrast, high priority customers arriving during the visit period of the queue are allowed to pass the gate and all low priority customers before the gate. We study the cycle time distribution, the waiting time distributions for each customer type, the joint queue length distribution of all priority classes at all queues at polling epochs, and the steady-state marginal queue length distributions for each customer type. Through numerical examples we illustrate that the mixed gated/exhaustive service discipline can significantly decrease waiting times of high priority jobs. In many cases there is a minimal negative impact on the waiting times of low priority customers but, remarkably, it turns out that in polling systems with larger switch-over times there can be even a positive impact on the waiting times of low priority customers.