Standard Harmony Search Algorithm for Structural Design Optimization

2009 ◽  
pp. 1-49 ◽  
Author(s):  
Kang Seok Lee
Keyword(s):  
Design Optimization ◽  
Structural Design ◽  
Search Algorithm ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Structural Design Optimization

Multi Objective Design Optimization of Helical Gear Pair Using Adaptive Parameter Harmony Search Algorithm

2015 ◽  
Vol 813-814 ◽  
pp. 1032-1036
Author(s):  
P. Sabarinath ◽  
M.R. Thansekhar ◽  
R. Jeganathan ◽  
R. Saravanan
Keyword(s):  
Design Optimization ◽  
Search Algorithm ◽  
Harmony Search ◽  
Helical Gear ◽  
Harmony Search Algorithm ◽  
Gear Pair ◽  
Multi Objective ◽  
Gear Design ◽  
Design Variables ◽  
Helical Gear Pair

Mechanical design engineers design products by selecting the best possible materials and geometries that satisfies the specific operational requirements of the design. It involves lot of creativity and aesthetics to make better designs. A gear design makes the designer to compromise many design variables so as to arrive the best performance of a gear set. The best possible way for multi variable, Multiobjective gear design is to try design optimization. For many complex engineering optimization problems multi objective design optimization methods are used to simplify the design problem. In this paper, multiobjective design of helical gear pair transmission with objective functions namely volume of the small and large helical gear and opposite number of overlap ratio is taken into account. The design variables considered are normal module, helix angle, gear width coefficient and teeth number of small helical gear. A recent meta-heuristic algorithm namely parameter adaptive harmony search algorithm is applied to solve this problem using the weighted sum approach. It is evident from the results that the proposed approach is performing better than other algorithms.

scholarly journals Multiobjective Optimization Method Based on Adaptive Parameter Harmony Search Algorithm

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
P. Sabarinath ◽  
M. R. Thansekhar ◽  
R. Saravanan
Keyword(s):  
Optimal Design ◽  
Multiobjective Optimization ◽  
Design Optimization ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Production Costs ◽  
Machining Parameters ◽  
Conflicting Objectives

The present trend in industries is to improve the techniques currently used in design and manufacture of products in order to meet the challenges of the competitive market. The crucial task nowadays is to find the optimal design and machining parameters so as to minimize the production costs. Design optimization involves more numbers of design variables with multiple and conflicting objectives, subjected to complex nonlinear constraints. The complexity of optimal design of machine elements creates the requirement for increasingly effective algorithms. Solving a nonlinear multiobjective optimization problem requires significant computing effort. From the literature it is evident that metaheuristic algorithms are performing better in dealing with multiobjective optimization. In this paper, we extend the recently developed parameter adaptive harmony search algorithm to solve multiobjective design optimization problems using the weighted sum approach. To determine the best weightage set for this analysis, a performance index based on least average error is used to determine the index of each weightage set. The proposed approach is applied to solve a biobjective design optimization of disc brake problem and a newly formulated biobjective design optimization of helical spring problem. The results reveal that the proposed approach is performing better than other algorithms.

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