A novel differential evolution mapping technique for generic combinatorial optimization problems

Differential evolution is primarily designed and used to solve continuous optimization problems. Therefore, it has not been widely considered as applicable for real-world problems that are characterized by permutation-based combinatorial domains. Many algorithms for solving discrete problems using differential evolution have been proposed, some of which have achieved promising results. However, to enhance their performance, they require improvements in many aspects, such as their convergence speeds, computational times and capabilities to solve large discrete problems. In this paper, we present a new mapping method that may be used with differential evolution to solve combinatorial optimization problems. This paper focuses specifically on the mapping component and its effect on the performance of differential evolution. Our method maps continuous variables to discrete ones, while at the same time, it directs the discrete solutions produced towards optimality, by using the best solution in each generation as a guide. To judge its performance, its solutions for instances of well-known discrete problems, namely: 0/1 knapsack, traveling salesman and traveling thief problems, are compared with those obtained by 8 other state-of-the-art mapping techniques. To do this, all mapping techniques are used with the same differential evolution settings. The results demonstrated that our technique significantly outperforms the other mapping methods in terms of the average error from the best-known solution for the traveling salesman problems, and achieves promising results for both the 0/1 knapsack and the traveling thief problems.     

Dynamic design of sales territories

We introduce the Multiple Traveling Salesmen and Districting Problem with Multi-periods and Multi-depots. In this problem, the compactness of the subdistricts, the dissimilarity measure of districts and an equity measure of salesmen profit are considered as part of the objective function, and the salesman travel cost on each subdistrict is approximated by the Beardwood–Halton–Hammersley formula. An adaptive large neighbourhood search metaheuristic is developed for the problem. It was tested on modified Solomon and Gehring & Homberger instances. Computational results confirm the effectiveness of the proposed metaheuristic.     

行波效应对大跨度刚构桥地震反应的影响

地震输入问题一直是工程结构抗震研究所关注的焦点.大跨度桥梁结构各地面支承距离较大、延伸较长,进行进震反应分析时应考虑各支承处地震波的不同(多点激励)以及地震波有限波速传播所引起的行波效应.文章以洛河特大桥为例,进行了基于多点激励与行波效应下的动态时程地震反应分析,并比较了考虑多点激励与行波效应对该桥各项地震响应的不同影响.     

Fast fault detection scheme for series-compensated lines during power swing

This paper reports the use of a novel ultra-high speed scheme to release the distance relay to operate for a fault during a power swing in the series compensated line. In the scheme, in order to extract the fault induced voltage and current components, voltage and current samples are analyzed by the multi-resolution morphological gradient (MMG), first. Then, the fault initiated forward travelling wave is computed at the distance relay point. Next, Likelihood ratio [LR] test is utilized to detect a jump in the statistical mean of the calculated forward travelling wave. Finally, a support vector machine (SVM) classifier is employed to distinguish faults from other normal capacitor and switching transients. It is shown that in all of the simulated cases, our ultra-high speed algorithm was successful in fault detection across a wide range conditions including, fault type, fault resistance, fault location, pre-fault loading and fault inception time. Moreover, we found that using the proposed scheme significantly speeded the fault detection, in comparison with the existing phasor based methods. In addition, the improvements noted in our algorithm are achieved with a low computational burden.     

Developing a dynamic neighborhood structure for an adaptive hybrid simulated annealing – tabu search algorithm to solve the symmetrical traveling salesman problem

This paper applies a hybrid simulated annealing – tabu search algorithm to solve the Traveling Salesman Problem (TSP). Fully considering the characteristics of the hybrid algorithm, we develop a dynamic neighborhood structure for the hybrid algorithm to improve search efficiency by reducing the randomness of the conventional 2-opt neighborhood. A circle-directed mutation is developed to achieve this dynamic neighborhood structure. Furthermore, we propose adaptive parameters that can be automatically adjusted by the algorithm based on context specific examples. This negates the need to frequently readjust algorithm parameters. We employ benchmarks obtained from TSPLIB (a library of sample instances for the TSP) to test our algorithm, and find that the proposed algorithm can obtain satisfactory solutions within a reasonable amount of time. The experimental results demonstrate that the proposed hybrid algorithm can overcome the disadvantages of traditional simulated annealing and tabu search methods. The results also show that the dynamic neighborhood structure is more efficient and accurate than the classical 2-opt. Also, adaptive parameters are appropriate for almost all of the numerical examples tested in this paper. Finally, the experimental results are compared with those of other algorithms, to demonstrate the improved accuracy and efficiency of the proposed algorithm.     

A meta-heuristic based goal-selection strategy for mobile robot search in an unknown environment

The single-robot search problem in an unknown environment is defined as the problem of finding a stationary object in the environment whose map is not known a priori. Compared to exploration, the only difference lies in goal selection as the objectives of search and exploration are dissimilar, i.e. a trajectory that is optimal in exploration does not necessarily minimize the expected value of the time to find an object along it. For this reason, in this paper we extend the preliminary ideas presented in Kulich et al. [1] to a general framework that accounts for the particular characteristics of the search problem. Within this framework, an important decision involved in the determination of the trajectory can be formulated as an instance of the Graph Search Problem (GSP), a generalization of the well-known Traveling Deliveryman Problem (TDP) which has not received much attention in the literature. We developed a tailored Greedy Randomized Adaptive Search Procedure (GRASP) meta-heuristic for the GSP, which generates good quality solutions in very short computing times and is incorporated in the overall framework. The proposed approach produces very good results in a simulation environment, showing that it is feasible from a computational standpoint and the proposed strategy outperforms the standard approaches.     

一种通信应用中的X波段行波管预失真器

随着通信技术的发展,行波管功率放大器预失真电路显得日益重要。不过,目前预失真电路在调节过程中增益和相位扩张量不能独立调节,很难保证增益和相位同时满足线性化指标的要求,给调节工作带来了困难。本文介绍一种预失真线性化器电路,该电路结构简单,在相位扩张量变化较小的同时,可以对增益扩张量进行调节控制。实验表明,在频率为8.38~8.58 GHz和额定输入功率范围内,预失真器增益和相位扩张量分别为6 dB和42°,满足通信工程中对行波管功率放大器补偿的需求。     

福州市区三环路交通组织设计

随着福州市新一轮总体规划的实施,城市格局将会有跳跃性的发展。本文在福州市中心城区路网规划及交通组织的基础上,明确了三环路在福州市中心区路网“环＋放射”式路网格局中的骨架地位。通过对三环路通行能力分析、出入口设计和衔接射线的交通组织的分析,体现了其作为城市道路与公路网络的快速衔接、构建中心城与周边组团间的便捷联系和引导城...     

肘板固定支承点位置对动颚行程特征值的影响研究

动颚行程特征值是决定颚式破碎机性能优劣的一个重要运动学参数。以复摆颚式破碎机为研究对象,利用MATLAB进行动颚的运动学建模与仿真分析,研究在当前结构条件下,在保持肘板长度、动颚肘板衬垫中心位置、动颚处于最低位置的排料口尺寸不变时,改变肘板固定支承点位置对动颚行程特征值的影响。计算结果表明,随着肘板支承点位置的变动,进料口动颚行程特征值逐渐减小,但变化不大;排料口动颚行程特征值逐渐增大,在某一支承点位置出现极值,以后逐渐减小,并且保持进料口行程特征值小于排料口行程特征值,即肘板支承点位置的变动不影响一般水平行程从进料口到排料口逐渐减小的要求。这个结论有助于对该产品进行优化设计选择最佳肘板支承点位置提供科学的依据。     

行波磁场铸造表面粗糙缺陷的成因与控制

分析了行波磁场铸造表面粗糙缺陷的形成原因,提出了双边电磁感应器法、三相换位法、增加极数法、补偿线圈法、增设溢流冒口法等5种控制方案,并通过ANSYS软件模拟验证了理论分析的可行性.