An improved global-best harmony search algorithm for faster optimization

In this paper, an improved global-best harmony search algorithm, named IGHS, is proposed. In the IGHS algorithm, initialization based on opposition-based learning for improving the solution quality of the initial harmony memory, a new improvisation scheme based on differential evolution for enhancing the local search ability, a modified random consideration based on artificial bee colony algorithm for reducing randomness of the global-best harmony search (GHS) algorithm, as well as two perturbation schemes for avoiding premature convergence, are integrated. In addition, two parameters of IGHS, harmony memory consideration rate and pitch adjusting rate, are dynamically updated based on a composite function composed of a linear time-varying function, a periodic function and a sign function in view of approximate periodicity of evolution in nature. Experimental results tested on twenty-eight benchmark functions indicate that IGHS is far better than basic harmony search (HS) algorithm and GHS. In further study, IGHS has also been compared with other eight well known metaheuristics. The results show that IGHS is better than or at least similar to those approaches on most of test functions.     

新形势下企业内部和谐党群干群关系的构建

一个企业没有和谐的党群干群关系,各项工作必将受到限制,严重的甚至会阻碍企业发展壮大。加强党风廉政建设,开展党的群众路线教育,以改革促发展,切实为群众办实事,对于构建和谐的党群干群关系意义重大。     

Alternative Economics and Sustainable Future: Diverse Cultures/Beliefs/Values as Indispensable Factors

This article argues for a theoretical framework of alternative economics pertinent to Sustainable Development. The alternative economics requires an appropriate belief/value system based on a dynamic, sound and holistic society-specific culture (abbreviated as “Culture”). To represent the Culture-based belief/value system, a general framework for overarching Integral Harmony is introduced as an appropriate social value system for a paradigm shift toward sustainability. Such a social value system is now related to the value premises of the alternative economics. Then, the framework of alternative economics is explained in terms of basic theoretical construct that is simplified as a summary equation comprising value and real aspects. Finally, a typical working of the alternative economics is demonstrated diagrammatically as constant interactions of the value aspect and the real aspect (abbreviated as “Value-Real Interactions”).     

认知无线电网络中基于和声搜索的频谱分配与功率控制

针对认知无线电网络中功率控制和频谱分配过程存在互相影响的问题,提出一种基于和声搜索的频谱分配和功率控制算法。通过综合分析频谱分配和功率控制过程中的各种约束条件,建立了联合功率控制和频谱分配的系统模型。算法根据系统模型特点设计和声搜索算法下相应编码方案,采用多目标优化方法处理复杂的约束条件,并赋予可行解适当的优先权重。仿真实验表明,算法可以很好地解决认知无线电网络中的频谱分配和功率控制问题。     

Harmony search based algorithm for the optimum design of grillage systems to LRFD-AISC

Harmony search based optimum design method is presented for the grillage systems. This numerical technique imitates the musical performance process that takes place when a musician searches for a better state of harmony. Jazz improvisation seeks to find musically pleasing harmony similar to the optimum design process which seeks to find the optimum solution. The design algorithm considers the serviceability and ultimate strength constraints which are implemented from Load and Resistance Factor Design—American Institute of Steel Construction (LRFD-AISC). It selects the appropriate W-sections for the transverse and longitudinal beams of the grillage system out of 272 discrete W-section designations given in LRFD-AISC. This selection is carried out such that the design limitations described in LRFD-AISC are satisfied and the weight of the system is the minimum. Many design examples are considered to demonstrate the efficiency of the algorithm presented.     

基于和声搜索和模拟退火的混合算法解决TSP问题

和声搜索是一种新的启发式优化算法,算法模拟了音乐创作中乐师们凭借自己的记忆,通过反复地调整乐队中各乐器的音调,最终能达到一个美妙的和声状态的过程.针对和声搜索算法容易陷入局部最优的缺陷,将其与模拟退火算法结合,得到了两种混合算法.实验表明混合算法针对TSP问题具有较高的求解质量.     

An improved fruit fly optimization algorithm for solving the multidimensional knapsack problem

This paper presents an improved fruit fly optimization algorithm (IFFOA) for solving the multidimensional knapsack problem (MKP). In IFFOA, the parallel search is employed to balance exploitation and exploration. To make full use of swarm intelligence, a modified harmony search algorithm (MHS) is proposed and applied to add cooperation among swarms in IFFOA. In MHS, novel pitch adjustment scheme and random selection rule are developed by considering specific characters of MKP and FOA. Moreover, a vertical crossover is designed to guide stagnant dimensions out of local optima and further improve the performance. Extensive numerical simulations are conducted and comparisons with other state-of-the-art algorithms verify that the proposed algorithm is an effective alternative for solving the MKP.     

基于Matlab实现音乐识别与自动配置和声的功能

给出了如何使用Matlab对现实演奏的音乐进行识别、并自动配置相应的和声的一套方法。详细分析了,从一段现有的钢琴单音旋律到最终自动产生和谐的多音色和声的整个过程。综合了物理、数学、自动化、音乐等领域的相关知识,最终实现自动给音乐配和声的功能。     

Multi-product multi-chance-constraint stochastic inventory control problem with dynamic demand and partial back-ordering: A harmony search algorithm

In this paper, a multiproduct inventory control problem is considered in which the periods between two replenishments of the products are assumed independent random variables, and increasing and decreasing functions are assumed to model the dynamic demands of each product. Furthermore, the quantities of the orders are assumed integer-type, space and budget are constraints, the service-level is a chance-constraint, and that the partial back-ordering policy is taken into account for the shortages. The costs of the problem are holding, purchasing, and shortage. We show the model of this problem is an integer nonlinear programming type and to solve it, a harmony search approach is used. At the end, three numerical examples of different sizes are given to demonstrate the applicability of the proposed methodology in real world inventory control problems, to validate the results obtained, and to compare its performances with the ones of both a genetic and a particle swarm optimization algorithms.     

Network partitioning using harmony search and equivalencing for distributed computing

Power system has a highly interconnected network that requires intense computational effort and resources for centralized control. Distributed computing needs the systems to be partitioned optimally into clusters. The network partitioning is an optimization problem whose objective is to minimize the number of nodes in a cluster and the tie lines between the clusters. Harmony Search(HS) Algorithm is one of the recently developed meta heuristic algorithms that can be applied to optimization problems. In this work, the HS algorithm is applied to the network partitioning problem and power flow based equivalencing is done to represent the external system. Simulation is done on IEEE Standard Test Systems. The algorithm is found to be very effective in partitioning the system hierarchically and the equivalencing method gives accurate results in comparison to the centralized control.