Discrete-Continuous Configuration Optimization Methods for Structures Using the Harmony Search Algorithm

2006 ◽  
Vol 324-325 ◽  
pp. 1293-1296 ◽  
Author(s):  
K.S. Lee ◽  
Chang Sik Choi
Keyword(s):  
Search Algorithm ◽  
Random Search ◽  
Optimization Technique ◽  
Harmony Search ◽  
Optimization Methods ◽  
Harmony Search Algorithm ◽  
Perfect State ◽  
Gradient Search ◽  
Geometric Variables ◽  
Derivative Information

This paper proposes an efficient structural optimization methods based on the harmony search (HS) heuristic algorithm that treat integrated discrete sizing and continuous geometric variables. The recently developed HS algorithm was conceptualized using the musical process of searching for a perfect state of harmony. It uses a stochastic random search instead of a gradient search so derivative information is unnecessary. A benchmark truss example is presented to demonstrate the effectiveness and robustness of the new method, as compared to current optimization methods. The numerical results reveal that the proposed method is a powerful search and design optimization technique for structures with discrete member sizes, and may yield better solutions than those obtained using current methods.

Improved Harmony Search Algorithm with Crossover Operation

2013 ◽  
Vol 415 ◽  
pp. 353-356 ◽  
Author(s):  
Hong Gang Xia ◽  
Qing Liang Wang
Keyword(s):  
Search Algorithm ◽  
Harmony Search ◽  
Optimization Methods ◽  
Optimization Method ◽  
Harmony Search Algorithm ◽  
Perfect State ◽  
Intelligent Optimization ◽  
New Variant ◽  
Improved Harmony Search ◽  
Improved Harmony Search Algorithm

Harmony search (HS) algorithm is a good meta-heuristic intelligent optimization method and it does depend on imitating the music improvisation process to generate a perfect state of harmony. However, intelligent optimization methods is easily trapped into local optimal, HS is no exception. In order to improve the performance of HS, a new variant of harmony search algorithm is proposed in this paper. The variant introduce a new crossover operation into HS, and design a strategy to adjust parameter pitch adjusting rate (PAR) and bandwidth (BW). Several standard benchmarks carried out to be tested. The numerical results demonstrated that the superiority of the proposed method to the HS and recently developed variants (IHS, and GHS).

A Tabu-Gradient Search-Based Optimization Technique for Synthesis of Mechanisms

2004 ◽  
Author(s):  
Ahmad Smaili ◽  
Naji Atallah
Keyword(s):  
Tabu Search ◽  
Global Minimum ◽  
Short Term Memory ◽  
Search Algorithm ◽  
Random Search ◽  
Optimization Technique ◽  
Optimization Methods ◽  
Gradient Search ◽  
Optimum Synthesis ◽  
Timing Task

Mechanism synthesis requires the use of optimization methods to obtain approximate solution whenever the desired number of positions the mechanism is required to traverse exceeds a few (five in a 4R linkage). Deterministic gradient-based methods are usually impractical when used alone because they move in the direction of local minima. Random search methods on the other hand have a better chance of converging to a global minimum. This paper presents a tabu-gradient search based method for optimum synthesis of planar mechanisms. Using recency-based short-term memory strategy, tabu-search is initially used to find a solution near global minimum, followed by a gradient search to move the solution ever closer to the global minimum. A brief review of tabu search method is presented. Then, tabu-gradient search algorithm is applied to synthesize a four-bar mechanism for a 10-point path generation with prescribed timing task. As expected, Tabu-gradient base search resulted in a better solution with less number of iterations and shorter run-time.

A New Variant Harmony Search Algorithm for Unconstrained Numerical Optimization Problems

2013 ◽  
Vol 365-366 ◽  
pp. 174-177
Author(s):  
Hong Gang Xia ◽  
Qing Zhou Wang
Keyword(s):  
Optimization Problems ◽  
Search Algorithm ◽  
Harmony Search ◽  
Optimization Methods ◽  
Optimization Method ◽  
Harmony Search Algorithm ◽  
Perfect State ◽  
Intelligent Optimization ◽  
New Variant ◽  
Key Parameter

Harmony search (HS) algorithm is a good meta-heuristic intelligent optimization method and it does depend on imitating the music improvisation process to generate a perfect state of harmony. However, intelligent optimization methods is easily trapped into local optimal, HS is no exception. In order to modify the optimization performance of HS, a new variant of harmony search algorithm is proposed in this paper. The variant integrate the position updating of the particle swarm optimization algorithm with pitch adjustment operation, and dynamically adjust the key parameter pitch adjusting rate (PAR) and bandwidth (BW). Several standard benchmarks are to be tested. The numerical results demonstrated the superiority of the proposed method to the HS and recently developed variants (IHS, and GHS).

scholarly journals Solution of combined economic and emission dispatch problem using a novel chaotic improved harmony search algorithm

2018 ◽  
Vol 6 (3) ◽  
pp. 447-467 ◽  
Author(s):  
Hamid Rezaie ◽  
M.H. Kazemi-Rahbar ◽  
Behrooz Vahidi ◽  
Hasan Rastegar
Keyword(s):  
Search Algorithm ◽  
Optimization Technique ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Transmission Losses ◽  
Test Systems ◽  
Improved Harmony Search ◽  
Emission Dispatch ◽  
Improved Harmony Search Algorithm ◽  
Economic Emission Dispatch

Abstract This paper presents a new optimization technique developed based on harmony search algorithm (HSA), called chaotic improved harmony search algorithm (CIHSA). In the proposed algorithm, the original HSA is improved using several innovative modifications in the optimization procedure such as using chaotic patterns instead of uniform distribution to generate random numbers, dynamically tuning the algorithm parameters, and employing virtual harmony memories. Also, a novel type of local optimization is introduced and employed in the algorithm procedure. Applying these modifications to HSA has resulted in enhancing the robustness, accuracy and search efficiency of the algorithm, and significantly reducing the iterations number required to achieve the optimal solution. To validate the effectiveness of CIHSA, it is used to solve the combined economic emission dispatch (CEED) problem, which practically is a complex high-dimensional non-convex optimization task with several equality and inequality constraints. Six test systems having 6, 10, 13, 14, 40, and 140 generators are investigated in this study, and the valve-point loading effects, ramp rate limits and power transmission losses are also taken into account. The results obtained by CIHSA are compared with the results reported in a large number of other research works. Furthermore, the statistical data regarding the CIHSA performance in all test systems is presented. The numerical and statistical results confirm the high quality of the solutions found by CIHSA and its superiority compared to other existing techniques employed in solving CEED problems. Highlights An innovative and strong optimization technique based on harmony search is proposed. The proposed algorithm is tested on solving economic emission dispatch problem. It has the potential to be applied to many other engineering optimization problems. Six test systems considering valve point effect and transmission losses are studied. High quality solutions are obtained and compared with a large number of other methods.

A New Variant Harmony Search Algorithm with Random Mutation Strategy

2014 ◽  
Vol 1065-1069 ◽  
pp. 3425-3428
Author(s):  
Xiu Hong Zhao
Keyword(s):  
Search Algorithm ◽  
Harmony Search ◽  
Optimization Methods ◽  
Optimization Method ◽  
Harmony Search Algorithm ◽  
Random Mutation ◽  
Local Optima ◽  
Intelligent Optimization ◽  
New Variant ◽  
Mutation Strategy

Harmony search (HS) algorithm is a good meta-heuristic intelligent optimization method, which has been paid much attention recently. However, intelligent optimization methods are easily trapped into local optima, HS is no exception. In order to improve the performance of HS, a new variant of harmony search algorithm with random mutation strategy (HSRM) is proposed in this paper. The HSRM uses a random mutation strategy to replace the pitch adjusting operation, and dynamically adjust the key parameter pitch adjusting rate (PAR). Experiment results demonstrated that the proposed method is superior to the HS and recently developed variants (IHS, and GHS) and other meta-heuristic algorithm.

scholarly journals A Cooperative Harmony Search Algorithm for Function Optimization

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Gang Li ◽  
Qingzhong Wang
Keyword(s):  
Optimization Problems ◽  
Search Algorithm ◽  
Cooperative Behavior ◽  
Optimization Technique ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Function Optimization ◽  
Solution Vector ◽  
Original Algorithm ◽  
Harmony Memory

Harmony search algorithm (HS) is a new metaheuristic algorithm which is inspired by a process involving musical improvisation. HS is a stochastic optimization technique that is similar to genetic algorithms (GAs) and particle swarm optimizers (PSOs). It has been widely applied in order to solve many complex optimization problems, including continuous and discrete problems, such as structure design, and function optimization. A cooperative harmony search algorithm (CHS) is developed in this paper, with cooperative behavior being employed as a significant improvement to the performance of the original algorithm. Standard HS just uses one harmony memory and all the variables of the object function are improvised within the harmony memory, while the proposed algorithm CHS uses multiple harmony memories, so that each harmony memory can optimize different components of the solution vector. The CHS was then applied to function optimization problems. The results of the experiment show that CHS is capable of finding better solutions when compared to HS and a number of other algorithms, especially in high-dimensional problems.

Harmony Search Algorithm and its Variants

2015 ◽  
Vol 29 (08) ◽  
pp. 1539001 ◽  
Author(s):  
Nazmul Siddique ◽  
Hojjat Adeli
Keyword(s):  
Heuristic Search ◽  
Optimization Problem ◽  
Heuristic Algorithms ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Harmony Search ◽  
Population Based ◽  
Harmony Search Algorithm ◽  
Perfect State ◽  
The Past

In the past three decades nature-inspired and meta-heuristic algorithms have dominated the literature in the broad areas of search and optimization. Harmony search algorithm (HSA) is a music-inspired population-based meta-heuristic search and optimization algorithm. The concept behind the algorithm is to find a perfect state of harmony determined by aesthetic estimation. This paper starts with an overview of the harmonic phenomenon in music and music improvisation used by musicians and how it is applied to the optimization problem. The concept of harmony memory and its mathematical implementation are introduced. A review of HSA and its variants is presented. Guidelines from the literature on the choice of parameters used in HSA for effective solution of optimization problems are summarized.

scholarly journals TRUE POWER LOSS REDUCTION BY HARMONY SEARCH ALGORITHM

2018 ◽  
Vol 6 (9) ◽  
pp. 196-205
Author(s):  
K. Lenin
Keyword(s):  
Power Loss ◽  
Reactive Power ◽  
Search Algorithm ◽  
Harmony Search ◽  
Population Based ◽  
Test System ◽  
Harmony Search Algorithm ◽  
Perfect State ◽  
Real Power ◽  
Power Loss Reduction

This paper presents Harmony Search algorithm (HS) for solving the reactive power problem.  Real power loss minimization is the major objective & also voltage profiles are should be kept within the limits.  This paper introduces a new search model the harmony search (HS) algorithm is a relatively new population-based metaheuristic optimization algorithm. It emulates the music improvisation progression where musicians improvise their instruments’ pitch by searching for a perfect state of harmony. In order to evaluate the efficiency of the proposed algorithm, it has been tested on practical 191 test system & real power loss has been considerably reduced.

Modified Harmony Search Algorithm for Unconstrained Numerical Optimization Problems

2014 ◽  
Vol 989-994 ◽  
pp. 2528-2531
Author(s):  
Hong Gang Xia ◽  
Qing Zhou Wang
Keyword(s):  
Numerical Optimization ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Harmony Search ◽  
Differential Evolution Algorithm ◽  
Optimization Method ◽  
Harmony Search Algorithm ◽  
Local Optimum ◽  
Perfect State ◽  
Evolution Algorithm

Harmony search algorithm is a new meta-heuristic optimization method imitating the music improvisation process where musicians improvise their instruments’ pitches searching for a perfect state of harmony. To enable the harmony search algorithm to transcend its limited capability of local optimum, a modified harmony search algorithm is proposed in this paper. In the modified harmony search algorithm, the mutation operation of differential evolution algorithm is introduced into MHS algorithm, which improves its convergence. Several standard benchmark optimization functions are to be test and compare the performance of the MHS. The results revealed the superiority of the proposed method to the HS and recently developed variants.

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