Mean sojourn times in multiclass feedback queues with gated disciplines

In this paper, we investigate multiclass feedback queues with gated disciplines. The server selects the stations by a nonpreemptive priority scheduling algorithm and serves customers in the selected station by either a gated FCFS discipline or a gated priority discipline. We take a rather systematic approach to their mean sojourn times. We define conditional expected sojourn times for all customers and derive their expressions from an analysis of busy periods. Since they are shown to be linear in some components of the system states, their steady state mean values can be derived from simple limiting procedures. These mean values can be obtained from a set of linear equations. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 719–741, 2003.     

CON/SLK due date assignment and scheduling on a single machine with two agents

We consider scheduling problems involving two agents (agents A and B), each having a set of jobs that compete for the use of a common machine to process their respective jobs. The due dates of the A‐jobs are decision variables, which are determined by using the common (CON) or slack (SLK) due date assignment methods. Each agent wants to minimize a certain performance criterion depending on the completion times of its jobs only. Under each due date assignment method, the criterion of agent A is always the same, namely an integrated criterion consisting of the due date assignment cost and the weighted number of tardy jobs. Several different criteria are considered for agent B, including the maxima of regular functions (associated with each job), the total (weighted) completion time, and the weighted number of tardy jobs. The overall objective is to minimize the performance criterion of agent A, while keeping the objective value of agent B no greater than a given limit. We analyze the computational complexity, and devise polynomial or pseudo‐polynomial dynamic programming algorithms for the considered problems. We also convert, if viable, any of the devised pseudopolynomial dynamic programming algorithms into a fully polynomial‐time approximation scheme. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 416–429, 2016     

Scheduling jobs with piecewise linear decreasing processing times

We study the problems of scheduling a set of nonpreemptive jobs on a single or multiple machines without idle times where the processing time of a job is a piecewise linear nonincreasing function of its start time. The objectives are the minimization of makespan and minimization of total job completion time. The single machine problems are proved to be NP‐hard, and some properties of their optimal solutions are established. A pseudopolynomial time algorithm is constructed for makespan minimization. Several heuristics are derived for both total completion time and makespan minimization. Computational experiments are conducted to evaluate their efficiency. NP‐hardness proofs and polynomial time algorithms are presented for some special cases of the parallel machine problems. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 531–554, 2003     

The effectiveness of the longest delivery time rule for the flow shop delivery time problem

In the flow shop delivery time problem, a set of jobs has to be processed on m machines. Every machine has to process each one of the jobs, and every job has the same routing through the machines. The objective is to determine a sequence of the jobs on the machines so as to minimize maximum delivery completion time over all the jobs, where the delivery completion time of a job is the sum of its completion time, and the delivery time associated with that job. In this paper, we prove the asymptotic optimality of the Longest Delivery Time algorithm for the static version of this problem, and the Longest Delivery Time among Available Jobs (LDTA) algorithm for the dynamic version of this problem. In addition, we present the result of computational testing of the effectiveness of these algorithms. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2003     

改进柔性资源约束项目调度模型与粒子群算法

在资源受限项目调度问题中,将可再生资源进一步拓展为具有能力差异的柔性资源,建立考虑能力差异的柔性资源受限的多模式项目调度问题模型,该模型是对传统资源约束项目调度问题(RCPSP)更接近实际的拓展。提出了基于粒子群算法的求解算法,粒子群算法求解该模型的思路为,利用蒙特卡洛方法根据资源-能力矩阵与活动模式-能力矩阵得到活动模式-资源矩阵,将考虑能力差异的柔性资源受限的多模式项目调度问题转换为常规的多模式项目调度问题,然后利用基于任务序列与模式表示的粒子群算法对该多模式项目调度问题进行求解。用数值实例说明了模型的合理性与算法的有效性。     

Scheduling parallel machines with inclusive processing set restrictions and job rejection

In this article, we study a parallel machine scheduling problem with inclusive processing set restrictions and the option of job rejection. In the problem, each job is compatible to a subset of machines, and machines are linearly ordered such that a higher‐indexed machine can process all those jobs that a lower‐indexed machine can process (but not conversely). To achieve a tight production due date, some of the jobs might be rejected at certain penalty. We first study the problem of minimizing the makespan of all accepted jobs plus the total penalty cost of all rejected jobs, where we develop a ‐approximation algorithm with a time complexity of . We then study two bicriteria variants of the problem. For the variant problem of minimizing the makespan subject to a given bound on the total rejection cost, we develop a ‐approximation algorithm with a time complexity of . For the variant problem of maximizing the total rejection cost of the accepted jobs subject to a given bound on the makespan, we present a 0.5‐approximation algorithm with a time complexity of . © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 667–681, 2017     

一种基于目标的雷达对抗侦察策略

传统的电子战接收系统的搜索方式主要针对参数完全未知的敌方信号,通过在频域、空域等各维度进行大范围的逐段重复搜索可在较长时间内获得较好的侦察效果,但不适合短时间内对特定目标群的搜索和验证。针对电子战接收机存在的盲目侦察接收、与作战目标结合不紧密等问题,提出了一种基于作战目标的侦察策略,能够智能引导超外差接收机进行搜索截获,有效提升了超外差接收机对重点目标的实时截获与准确识别能力。     

具有吞吐量和时延约束的软件无线电波形部署决策算法

针对当前具有吞吐量和时延约束的软件无线电波形部署决策算法在内存开销方面考虑的不足,提出一个更为通用的波形部署决策系统模型,将波形的处理开销、内存开销和通信带宽开销都纳入到波形部署决策过程中,并设计了一种基于动态规划的波形部署决策算法以最小化波形对平台各种计算资源的占用总和。仿真结果表明,内存对波形部署决策具有重要影响,与未考虑内存开销的解决方案相比,平台支持的平均最大波形数目和平均处理资源利用率均下降40%左右。     

A decomposition heuristic for the twin robots scheduling problem

This article provides an efficient heuristic based on decomposition for the twin robots scheduling problem (TRSP). TRSP concerns two moving robots executing storage and retrieval requests in parallel along a shared pathway. The depots are located at both ends of the line and a dedicated robot is assigned to each of them. While moving goods between their respective depots and some storage locations on the line, noncrossing constraints among robots need to be considered. Our heuristic uses a dynamic programming framework to determine the schedule of one robot while keeping the other one's fixed. It finds near‐optimal solutions even for large problem instances with hundreds of jobs in a short time span. © 2014 Wiley Periodicals, Inc. 62:16–22, 2015     

指定目标不延误条件下的拦截决策算法

从现有的拦截排序准则出发,根据实际作战中进袭目标的特点,应用现代排序理论,分别建立了动态目标拦截排序模型和总损失最小化模型,给出相应的求解算法。最后实例计算得出模型既体现了现有的拦截准则,又对现有的准则进行了推广。