改进蚁群算法及其仿真研究

在基本蚁群算法在基于蚁群系统(ACS)的基础上进行了改进,提出了一种新的局部更新策略,使得局部更新更有效更强健,同时采用动态的α值和信息素自适应调整策略,扩大了可行解的范围,有效抑制收敛过程中的停滞现象,提高了蚁群算法的求解性能.通过对多种旅行商问题(asp)的仿真实验,并分别与ACS和最大最小蚁群算法(MMAS)进行了比较,结果表明,该算法在性能上远优于ACS和MMAS.     

基于LQR算法的三维桥式吊车定位及防摆控制研究

首先采用牛顿力学方法建立了三维桥式吊车的非线性动力学模型,然后将其在平衡点处进行线性化,得到系统在X方向和Y方向完全解耦的状态空间方程。根据现代控制理论设计了系统的线性二次最优调节器(LQR)并进行SIMULINK仿真,最后利用C++语言和MATLAB将控制算法程序化,实时控制在多媒体定时器中断服务函数内实现,自主搭建了一套三维桥式吊车实验平台。系统成功实现运动范围内的定位及防摆控制,仿真及实验结果表面建立三维桥式吊车解耦模型的合理性与控制算法的有效性。     

An epidemiological study of low-back pain in crane operators

Abstract

A survey among workers in a steel factory was conducted to determine the risk for low-back pain (LBP) among male crane operators. Crane operators (n = 33) were matched for age with male control workers (n = 30)p and examined for frequency and nature of LBP by the on-site medical service. Comparison between crane operators and controls showed a statistically significant odds ratio for LBP of 3-6. Although crane operators had been exposed more often to backstraining factors in previous occupations, in the employed logistic analysis only their current job explained the elevated occurrence of LBP. It is suggested that workers in sedentary position with exposure to whole-body vibration are at special risk for LBP. The results of this study provide evidence to strongly recommend persons with a history of back complaints not to seek employment as crane operators.     

基于蚁群优化算法的Chord模型

提出一种具有物理拓扑匹配能力的Chord模型(Ant-Chord),用以存储网络标识间的映射信息。该模型将整个Chord环中的存储节点看成一个旅行商问题(TSP),利用蚁群优化算法对TSP问题进行快速求解,用得到的解构建Chord环,并通过洛阳铲法对Chord环的路由跳数进行优化。Ant-Chord模型实现简单,对原始Chord模型改动不大,路由表的额外存储开销也较小。仿真结果表明,与同类Chord模型相比,Ant-Chord在资源发现的平均路由跳数、时延方面均有明显优势。     

基于蚁群算法的喷涂机器人路径排序优化

研究喷涂机器人自动路径规划系统中的路径排序和组合问题,考虑路径顺序和喷涂方向的特点,引入开环的广义旅行商问题框架进行建模,并建立相应的优化目标和代价矩阵。利用蚁群优化算法的并行性和正反馈性对问题进行求解,保证算法的全局搜索能力和收敛性。仿真实验结果证明了该方法的有效性。     

Shoulder muscle loading and task performance for overhead work on ladders versus Mobile Elevated Work Platforms

A high incidence of Musculoskeletal Disorders (MSDs) has been reported in the construction sector. The use of ladders in the workplace has long been identified as a significant risk that can lead to workplace accidents. However, it is unclear if platform types have an effect on the physical risk factors for MSDs in overhead work. The aim of this study is to perform a pilot study on the effects of hand activity on both shoulder muscle loading and task performance while working on ladders versus Mobile Elevated Working Platforms (MEWPs). It is hypothesised that work on ladders would result in greater muscle loading demands, increased levels of discomfort, and reduced performance due to the restrictions on postures that could be adopted. A field study (n = 19) of experienced electricians on a construction site found that workers spent approximately 28% of their working time on ladders versus 6% on MEWPs. However, the durations of individual tasks were higher on MEWPs (153 s) than on ladders (73 s). Additionally, maximum levels of perceived discomfort (on a VAS 0–100) were reported for the shoulders (27), neck (23), and lower regions of the body (22). A simulated study (n = 12) found that task performance and discomfort were not significantly different between platform types (ladder vs. MEWP) when completing either of three tasks: cabling, assembly and drilling. However, platform and task had significant effects (p < 0.05) on median electromyographic (EMG) activity of the anterior deltoid and upper trapezius. EMG amplitudes were higher for the deltoid than the upper trapezius. For the deltoid, the peak amplitudes were, on average, higher for ladder work over MEWP work for the hand intensive cabling (32 vs. 27% Maximal Voluntary Exertion (MVE)) and the assembly task (19 vs. 6% MVE). Conversely, for drilling, the peak EMG amplitudes were marginally lower for ladder compared to the MEWP (3.9 vs. 5.1% MVE). The general implication was that working on the MEWP involved lower shoulder muscle loading for cabling and assembly task. A difference due to platform type was not present for drilling work.     

Load-dependent and precedence-based models for pickup and delivery problems

We address the one-to-one multi-commodity pickup and delivery traveling salesman problem (m-PDTSP) which is a generalization of the TSP and arises in several transportation and logistics applications. The objective is to find a minimum-cost directed Hamiltonian path which starts and ends at given depot nodes and such that the demand of each given commodity is transported from the associated source to its destination and the vehicle capacity is never exceeded. In contrast, the many-to-many one-commodity pickup and delivery traveling salesman problem (1-PDTSP) just considers a single commodity and each node can be a source or target for units of this commodity. We show that the m-PDTSP is equivalent to the 1-PDTSP with additional precedence constraints defined by the source–destination pairs for each commodity and explore several models based on this equivalence. In particular, we consider layered graph models for the capacity constraints and introduce new valid inequalities for the precedence relations. Especially for tightly capacitated instances with a large number of commodities our branch-and-cut algorithms outperform the existing approaches. For the uncapacitated m-PDTSP (which is known as the sequential ordering problem) we are able to solve to optimality several open instances from the TSPLIB and SOPLIB.     

The Quay Crane Scheduling Problem

The recent growth in worldwide container terminals’ traffic resulted in a crucial need for optimization models to manage the seaside operations and resources. Along with the recent increase in ship size and the container volume, the advancements in the field of Quay Crane Scheduling introduced the need for new modeling approaches. This is the motivation behind the current paper, which focuses on developing a novel yet simple formulation to address the Quay Crane Scheduling Problem (QCSP). The objective of the problem is to determine the sequence of discharge operations of a vessel that a set number of quay cranes will perform so that the completion time of the operations is minimized. The major contribution is attributed to the way that minimization is performed, which is by minimizing the differences between the container loads stacked over a number of bays and by maintaining a balanced load across the bays. Furthermore, important considerations are taken into account, such as the bidirectional movement of cranes and the ability to travel between bays even before completion of all container tasks. These realistic assumptions usually increase model complexity; however, in the current work this is offset by the novel simple objective. This paper presents a mixed-integer programming (MIP) formulation for the problem, which has been validated through multiple test runs with different parameters. Results demonstrate that the problem is solved extremely efficiently, especially for small problem sizes.     

Honey bees mating optimization algorithm for the Euclidean traveling salesman problem

This paper introduces a new hybrid algorithmic nature inspired approach based on Honey Bees Mating Optimization for successfully solving the Euclidean Traveling Salesman Problem. The proposed algorithm for the solution of the Traveling Salesman Problem, the Honey Bees Mating Optimization (HBMOTSP), combines a Honey Bees Mating Optimization (HBMO) algorithm, the Multiple Phase Neighborhood Search-Greedy Randomized Adaptive Search Procedure (MPNS-GRASP) algorithm and the Expanding Neighborhood Search Strategy. Besides these two procedures, the proposed algorithm has, also, two additional main innovative features compared to other Honey Bees Mating Optimization algorithms concerning the crossover operator and the workers. The main contribution of this paper is that it shows that the HBMO can be used in hybrid synthesis with other metaheuristics for the solution of the TSP with remarkable results both to quality and computational efficiency. The proposed algorithm was tested on a set of 74 benchmark instances from the TSPLIB and in all but eleven instances the best known solution has been found. For the rest instances the quality of the produced solution deviates less than 0.1% from the optimum.