A Hybridization of Sine Cosine Algorithm with Steady State Genetic Algorithm for Engineering Design Problems

2019 ◽  
pp. 143-155 ◽  
Author(s):  
M. A. El-Shorbagy ◽  
M. A. Farag ◽  
A. A. Mousa ◽  
I. M. El-Desoky
Keyword(s):  
Genetic Algorithm ◽  
Steady State ◽  
Engineering Design ◽  
Design Problems ◽  
Engineering Design Problems ◽  
Sine Cosine Algorithm

Multi-Objective Optimal Design of Automotive Engine Using Genetic Algorithm

1998 ◽  
Author(s):  
Kikuo Fujita ◽  
Noriyasu Hirokawa ◽  
Shinsuke Akagi ◽  
Shinji Kitamura ◽  
Hideaki Yokohata
Keyword(s):  
Genetic Algorithm ◽  
Engineering Design ◽  
Design Problem ◽  
Optimization Method ◽  
Optimization Techniques ◽  
Total Power ◽  
Design Problems ◽  
Automotive Engine ◽  
Multi Objective ◽  
Engineering Design Problems

Abstract A genetic algorithm based optimization method is proposed for a multi-objective design problem of an automotive engine, that includes several difficulties in practical engineering optimization problems. While various optimization techniques have been applied to engineering design problems, a class of realistic engineering design problems face on a mixture of different optimization difficulties, such as the rugged nature of system response, the numbers of design variables and objectives, etc. In order to overcome such a situation, this paper proposes a genetic algorithm based multi-objective optimization method, that introduces Pareto-optimality based fitness function, similarity based selection and direct real number crossover. This optimization method is also applied to the design problem of an automotive engine with the design criteria on a total power train. The computational examples show the ability of the proposed method for finding a relevant set of Pareto optima.

scholarly journals A Hybrid Approach for Solving Constrained Multi-Objective Mixed-Discrete Nonlinear Programming Engineering Problems

2021 ◽  
Author(s):  
Satadru Roy ◽  
William A. Crossley ◽  
Samarth Jain
Keyword(s):  
Genetic Algorithm ◽  
Nonlinear Programming ◽  
Engineering Design ◽  
Hybrid Approach ◽  
Design Problems ◽  
Multi Objective ◽  
Engineering Design Problems ◽  
Search Tool ◽  
Gradient Based ◽  
The Individual

Several complex engineering design problems have multiple, conflicting objectives and constraints that are nonlinear, along with mixed discrete and continuous design variables; these problems are inherently difficult to solve. This chapter presents a novel hybrid approach to find solutions to a constrained multi-objective mixed-discrete nonlinear programming problem that combines a two-branch genetic algorithm as a global search tool with a gradient-based approach for the local search. Hybridizing two algorithms can provide a search approach that outperforms the individual algorithms; however, hybridizing the two algorithms, in the traditional way, often does not offer advantages other than the computational efficiency of the gradient-based algorithms and global exploring capability of the evolutionary-based algorithms. The approach here presents a hybridization approach combining genetic algorithm and a gradient-based approach with improved information sharing between the two algorithms. The hybrid approach is implemented to solve three engineering design problems of different complexities to demonstrate the effectiveness of the approach in solving constrained multi-objective mixed-discrete nonlinear programming problems.

scholarly journals Hybridizing sine cosine algorithm with multi-orthogonal search strategy for engineering design problems

2017 ◽  
Vol 5 (2) ◽  
pp. 249-273 ◽  
Author(s):  
Rizk M. Rizk-Allah
Keyword(s):  
Engineering Design ◽  
Search Strategy ◽  
Optimization Problems ◽  
Benchmark Problems ◽  
Design Problems ◽  
Local Optima ◽  
Manufacturing Optimization ◽  
Engineering Design Problems ◽  
Orthogonal Search ◽  
Sine Cosine Algorithm

Abstract This paper presents a new algorithm based on hybridizing the sine cosine algorithm (SCA) with a multi-orthogonal search strategy (MOSS), named multi-orthogonal sine cosine algorithm (MOSCA), for solving engineering design problems. The proposed MOSCA integrates the advantages of the SCA and MOSS to eliminate SCA's disadvantages, like unbalanced exploitation and the trapping in local optima. The proposed MOSCA works in two stages, firstly, the SCA phase starts the search process to enhance exploration capability. Secondly, the MOSS phase starts its search from SCA found so far to boost the exploitation tendencies. In this regard, MOSS phase can assist SCA phase to search based on deeper exploration/exploitation patterns as an alternative. Therefore, the MOSCA can be more robust, statistically sound, and quickly convergent. The performance of the MOSCA algorithm is investigated by applying it on eighteen benchmark problems and four engineering design problems. The experimental results indicate that MOSCA is a promising algorithm and outperforms the other algorithms in most cases. Highlights MOSCA is presented to solve design and manufacturing optimization problems efficiently. MOSCA is based on two phases namely, sine cosine algorithm (SCA) and multi-orthogonal search strategy (MOSS). The integrated MOSCA enhances exploration tendency and exploitation capability. The MOSCA can be more robust, statistically sound, and quickly convergent. New approach produced successful results compared to the literature studies.

Hybrid genetic algorithm for engineering design problems

2016 ◽  
Vol 20 (1) ◽  
pp. 263-275 ◽  
Author(s):  
Xuesong Yan ◽  
Hanmin Liu ◽  
Zhixin Zhu ◽  
Qinghua Wu
Keyword(s):  
Genetic Algorithm ◽  
Engineering Design ◽  
Hybrid Genetic Algorithm ◽  
Design Problems ◽  
Engineering Design Problems

Standards, Codes of Practice and Expert Systems

1988 ◽  
Vol 21 (1) ◽  
pp. 5-9 ◽  
Author(s):  
E G McCluskey ◽  
S Thompson ◽  
D M G McSherry
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
Engineering Design ◽  
Performance Criteria ◽  
Design Problems ◽  
Codes Of Practice ◽  
Engineering Design Problems ◽  
And Performance

Many engineering design problems require reference to standards or codes of practice to ensure that acceptable safety and performance criteria are met. Extracting relevant data from such documents can, however, be a problem for the unfamiliar user. The use of expert systems to guide the retrieval of information from standards and codes of practice is proposed as a means of alleviating this problem. Following a brief introduction to expert system techniques, a tool developed by the authors for building expert system guides to standards and codes of practice is described. The steps involved in encoding the knowledge contained in an arbitrarily chosen standard are illustrated. Finally, a typical consultation illustrates the use of the expert system guide to the standard.

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