Quay crane scheduling at container terminals to minimize the maximum relative tardiness of vessel departures

In this paper, we study the problem of scheduling quay cranes (QCs) at container terminals where incoming vessels have different ready times. The objective is to minimize the maximum relative tardiness of vessel departures. The problem can be formulated as a mixed integer linear programming (MILP) model of large size that is difficult to solve directly. We propose a heuristic decomposition approach to breakdown the problem into two smaller, linked models, the vessel‐level and the berth‐level models. With the same berth‐level model, two heuristic methods are developed using different vessel‐level models. Computational experiments show that the proposed approach is effective and efficient. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

遗传算法在装备调拨辅助决策中的应用

利用遗传算法求解装备调拨中的路径优化问题和运输装载问题,并利用MATLAB进行了实例仿真,对装备调拨的辅助决策具有积极的意义。     

基于移动Agent的特定数值求解算法研究

在分布式环境下,运用移动Agent技术实现大型复杂系统研究中经常使用的特定数值算法求解,可显著提高计算效率。以分支定界法为例,介绍了其设计思想和实践步骤,并对算法的时间复杂度进行了分析。     

复合固体推进剂颗粒填充模型及其统计特性分析

复合固体推进剂属于高填充比颗粒类复合材料,氧化剂和金属颗粒在基体中的随机分布使其在细观尺度具有非均质的特点。从细观尺度研究固体推进剂燃烧及力学性能时,必须考虑颗粒级配、空间分布和种类等因素的影响。采用分子动力学方法,以硝酸酯增塑聚醚高能复合固体推进剂为研究对象,将固体颗粒模型化为球形,生成其在基体内随机分布的颗粒填充模型。利用Monte-Carlo算法模拟计算颗粒填充模型细观结构的两点概率函数,并研究了颗粒填充体积分数、尺寸与级配等参数对其的影响规律。从统计意义上给出具有各态历经性、统计均匀性和各向同性特点的颗粒填充构型最小周期性代表体元尺寸,可有效减小后续研究的计算量,节约计算成本。所构建的推进剂细观几何构型及对最小周期性代表体元尺寸的计算为后续开展复合固体推进剂细观尺度燃烧、燃面处铝团聚及力学性能数值研究奠定了基础。     

A stochastic programming approach for chemotherapy appointment scheduling

Chemotherapy appointment scheduling is a challenging problem due to the uncertainty in premedication and infusion durations. In this paper, we formulate a two‐stage stochastic mixed integer programming model for the chemotherapy appointment scheduling problem under limited availability of nurses and infusion chairs. The objective is to minimize the expected weighted sum of nurse overtime, chair idle time, and patient waiting time. The computational burden to solve real‐life instances of this problem to optimality is significantly high, even in the deterministic case. To overcome this burden, we incorporate valid bounds and symmetry breaking constraints. Progressive hedging algorithm is implemented in order to solve the improved formulation heuristically. We enhance the algorithm through a penalty update method, cycle detection and variable fixing mechanisms, and a linear approximation of the objective function. Using numerical experiments based on real data from a major oncology hospital, we compare our solution approach with several scheduling heuristics from the relevant literature, generate managerial insights related to the impact of the number of nurses and chairs on appointment schedules, and estimate the value of stochastic solution to assess the significance of considering uncertainty.     

A new energy efficient management approach for wireless sensor networks in target tracking

This paper mainly studied the problem of energy conserving in wireless sensor networks for target tracking in defensing combats. Firstly, the structures of wireless sensor nodes and networks were illustrated; Secondly, the analysis of existing energy consuming in the sensing layer and its calculation method were provided to build the energy conserving objective function; What's more, the other two indicators in target tracking, including target detection probability and tracking accuracy, were combined to be regarded as the constraints of the energy conserving objective function. Fourthly, the three energy conserving approaches, containing optimizing the management scheme, prolonging the time interval between two adjacent observations, and transmitting the observations selectively, were introduced; In addition, the improved lion algorithm combined with the Logistic chaos sequence was proposed to obtain sensor management schemes. Finally, simulations had been made to prove the effectiveness of the proposed methods and algorithm.     

多维离散变换与小波的并行算法及其实现

讨论了多维 DCT和多维 DWT的并行行列算法和并行多项式变换算法 ,并用 Log P模型对算法进行了分析。在仔细分析一维和二维离散小波变换与小波包变换计算结构的基础上 ,提出了它们的并行算法。算法只需相对较少的通信时间 ;适合大规模并行机 ( MPP)和工作站或微机机群系统 ;方法也适合信号处理中的各种塔式分解过程。用 Fortran语言和 PVM编制了算法的程序。在机群系统和大规模并行机上的实验表明 ,算法是正确的且具有较高的加速比。     

主方差分析方法

该文提出一种对高维随机向量 X=( x1 ,x2 ,… ,xp)′p× 1 进行降维处理的实用方法 ,其基本思想是利用矩阵的扫描运算 ,构造 X的很少几个综合指标 (称为主方差变量 )以反映 X的统计特性。给出了该方法的理论依据和直观解释以及算法。特别指出 ,当变量 X多重相关性突出时 ,该文方法显著地优于主成分分析方法。     

任务分配与调度中遗传算子的设计

应用遗传算法等进化方法进行任务分配与调度为越来越多的计算机学者们所关注。基于任务排列的知识表示 ,常规的标准遗传操作算子并不总是有效的。好的遗传算子对算法收敛性及收敛到好点是非常重要的。在列表编码的知识表示基础上 ,设计了三个有针对性的遗传算子 ,即改进的交配算子、内部交配算子和一种作为变异的迁移算子。模拟实验结果与分析表明这些算子对任务分配与调度是有效的。     

BP成像算法的快速实现

BP (Back Projection)算法是一种被广泛应用的SAR成像算法 ,它的突出优点是解决了大积累角情况下不可避免的距离迁移 (rangemigration)问题。但由于计算量过大 ,使得它往往成为提高信号处理效率的瓶颈。本文充分利用轨道SAR地面实验中雷达运动轨迹的特点 ,通过消除BP算法中计算的冗余性 ,极大地降低了计算负担 ,提高了成像速度。本算法在实际应用中取得了良好效果