Hybrid Firefly Algorithm Harmony Search for Feature Selection with BCNF for Multiple Subtables and EM-GMM for Top Down Initial Partitioning

Harmony search (HS) algorithm is an emerging population oriented stochastic metaheuristic algorithm, which is inspired by the music improvisation process. This paper introduces an Amended harmony search (AHS) algorithm for solving optimization problems. In AHS, an enhanced approach is employed for generating better solution that improves accuracy and convergence speed of harmony search (HS). The effects of various parameters on harmony search algorithm are analyzed in this paper. The proposed approach performs fine tuning of two parameters bandwidth and pitch adjustment rate. The proposed algorithm is demonstrated on complex benchmark functions and results are compared with two recent variants of HS optimization algorithms, improved harmony search (IHS) and highly reliable harmony search (HRHS). Results suggested that the AHS method has strong convergence and has better balance capacity of exploration and exploitation.

A novel Multiuser Detection (MUD) scheme is proposed for DS-CDMA systems employing the so-called Harmony Search (HS) algorithm, which is a novel meta-heuristic optimisation method. We specifically design the HS aided MUD for the communications problem considered and apply it in an iterative joint Channel Estimation (CE), MUD and channel decoding framework. The simulation results demonstrate that a near-single-user performance can be achieved by the proposed algorithm while avoiding the excessive-complexity full-search-based optimum detection even in overloaded DS-CDMA systems. Moreover, the HS algorithm can be efficiently applied in the Expectation Maximisation (EM) based CE framework.

A method based on harmony search (HS) algorithm for designing an optical comb generator with excellent flatness is proposed. The comb generator with simple structure consists of four phase modulators with a single laser as the input, single radio frequency (RF) bias with different amplitudes, and DC bias for each modulator. No RF phase shifter, filter, or fiber loop is needed. Instead of following a classic mathematical model for finding the values of RF amplitudes and DC voltages for generating an optical comb, HS algorithm is implemented, which is an intelligent algorithm inspired from the improvisation of music players and seeks for the most harmonized answers corresponding to flat optical combs. The simulation results of generating two sets of optical combs by HS algorithm with 43 and 53 lines with flatness of 0.51 and 0.59 dB and then after inclusion of power conversion efficiency in the objective function of HS algorithm, two other sets of combs with 47 and 55 lines, flatness of 1.64 and 1.77 dB, and power conversion efficiency of 28% and 32% are presented. Such a device can be used in wavelength-division multiplexing systems and many other applications.

An improved harmony search algorithm for power economic load dispatch

Software testing is the primary phase, which is performed during software development and it is carried by a sequence of instructions of test inputs followed by expected output.The Harmony Search (HS) algorithm is based on the improvisation process of music.In comparison to other algorithms, the HSA has gain popularity and superiority in the field of evolutionary computation.When musicians compose the harmony through different possible combinations of the music, at that time the pitches are stored in the harmony memory and the optimization can be done by adjusting the input pitches and generate the perfect harmony.The test case generation process is used to identify test cases with resources and also identifies critical domain requirements.In this paper, the role of Harmony search meta-heuristic search technique is analyzed in generating random test data and optimized those test data.Test data are generated and optimized by applying in a case study i.e. a withdrawal task in Bank ATM through Harmony search.It is observed that this algorithm generates suitable test cases as well as test data and gives brief details about the Harmony search method.It is used for test data generation and optimization.

This work presents the development of multi-objective harmony search (MOHS) algorithm for optimization problem using self-adaptive improved harmony search (SIHS) algorithm which is a variant of recently developed harmony search algorithm (HS) for single objective optimization. The approach used in this work is decomposing of multiple objectives into several single objective functions which are simultaneously optimized in such a way that a nearly uniform distribution of the solutions along the pareto-front is followed. The algorithm upon testing for standard test functions has shown promising results.KeywordsHarmony SearchMulti-objective optimizationPareto front

Decision-making and optimal design of green energy system based on statistical methods and artificial neural network approaches

This paper presents a new modification of Harmony Search (HS) algorithm for solving global continuous optimization problems. The proposed algorithm is named self-adaptive dynamic Harmony Search (SDHS). In this modification, firstly, harmony memory consideration rate (HMCR), pitch adjusting rate (PAR) and bandwidth distance (BW), are dynamically adjusted simultaneously to keep a good balance between exploration and exploitation in the search process and different search spaces. Secondly, we introduced X best (the best value so far) to produce candidate harmony and adjust of the parameter BW. Experimental results tested on sixteen benchmark functions show that SDHS performs more effectively or at least similar to other approaches on most of test functions.

In this paper, a new variant of harmony search algorithm called self-adaptive differential harmony search (SADHS) algorithm is proposed to solve the combined economic emission dispatch (CEED) problems. The proposed algorithm is tested on 6- and 40 unit test systems to show the effectiveness. The simulation results obtained by the proposed algorithm are compared with the results of differential harmony search (DHS) algorithm. The results obtained by the proposed algorithm are found to be better than DHS algorithm in terms of quality of solution, speed of convergence and CPU time.

Combinatorial test case generation faces a problem on how to reduce the test cases by uncover the unnecessary test cases. So, there is a need for expert applications or strategies that generate the most optimum test cases keeping in mind the most important combinations. Complementing existing work on combinatorial test case generation strategies, also known as t-way testing strategies (i.e., where t represents interaction degree), this paper presents the design and the implementation of a new combinatorial test list generation strategy based on Harmony Search (HS) algorithm, called General T-way Harmony Search-based Strategy (GTHS). HS has been chosen to be the main engine of test generation because it could balance between intensification and diversification. Benchmarking experimental results show that GTHS produces competitive results as compared to other existing well-known optimization-based strategies and provides the support for high combination degrees (i.e., t ≤ 12).

This paper proposes an improved harmony search (HS) algorithm for the solution of the static transmission expansion planning (TEP) problem with security constraints. The modification of this method in comparison to the original harmony search algorithm includes the introduction of a variable bandwidth in the memory consideration and the pitch adjustment phase for the selection of the new harmony vector (NHV) in the improvisation step of the algorithm. In that way, if previous harmonies are considered for the NHV, the algorithm allows only the best harmonies of the harmony memory in respect of objective function value to participate in the improvisation of the NHV. The results from the application of the proposed method on IEEE 24-bus reliability test system demonstrate the potentials and the practicality of the proposed HS algorithm. (6 pages)

In this paper a new method for dynamic parameter adaptation in harmony search (HS) algorithm is proposed. HS is a music inspired metaheuristic optimization algorithm, in particular we refer to jazz improvisation and is applied to solve complex problems. In this paper we propose an improvement to the convergence of the harmony search algorithm using fuzzy logic. Simulation results show that the propose approach improves the performance of HS, and benchmark mathematical functions are used to illustrate the feasibility of the proposed approach.

To solve the selection of multimodal transportation scheme, a multimodal transportation scheme selection model with several software time windows, which considered several time windows in the transportation network, was put forward. And then a Harmony Search( HS) algorithm based on character-encoding was developed. The proposed algorithm adopted a new harmony generation method and a new fine-tuning mode. Finally, numerical examples demonstrate that,compared with greedy algorithm, the HS algorithm can find best transportation scheme with less total cost and less delay time.

A Harmony Search (HS) algorithm is a population based-meta-heuristics approach that is superior in solving diversified and large scale optimization problems. Several studies have pointed out that Harmony Search is an efficient and flexible tool to resolve optimization problems in diverse areas of construction, engineering, robotics, telecommunication, health and energy. Considering its increasing usage in diverse areas, this paper aims to present the historical development of HS, highlighting on its different features, modifications for improvements and limitations. Based on the description of the fundamental concept of HS, recent variations of the extended HS were analyzed focusing on its algorithm’s theory as well as its fundamental and primary concepts. It was found that the enhancements made on the extended HS are mainly on the modification of the parameters, such as the harmony memory consideration rate (HMCR), pitch adjusting rate (PAR) and distance bandwidth (BW). This analysis provides a useful motivation for researchers interested to improve the achievement of the standard HS algorithm and enhance the solution convergence rate and flexibility.

As a meta-heuristic algorithm, Harmony Search (HS) can be used to solve lots of NP-hard problems. The pitch adjustment rate (PAR) in HS algorithm is very important parameter in balancing local exploitation and the global exploration. In this paper, three new PAR adjustment strategies are presented for enhance the global optimality of HS, which follow small PAR values with large BW values in early generations, and large PAR values with small BW values in final generations. Finally, the computational simulations and comparisons are carried out by employing six benchmark problems from related literature. The experimental results indicate that using convex function adjust the PAR could improve the performance of HS algorithm. Conversely, using the concave function adjust the PAR reduce the performance of HS algorithm.