A novel differential evolution algorithm for solving constrained engineering optimization problems

This paper introduces a novel differential evolution (DE) algorithm for solving constrained engineering optimization problems called (NDE). The key idea of the proposed NDE is the use of new triangular mutation rule. It is based on the convex combination vector of the triplet defined by the three ra...

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Bibliographic Details
Published in:Journal of intelligent manufacturing Vol. 29; no. 3; pp. 659 - 692
Main Author: Mohamed, Ali Wagdy
Format: Journal Article
Language:English
Published: New York Springer US 01.03.2018
Springer Nature B.V
Subjects:
Advanced manufacturing technologies
Algorithms
Business and Management
Control
Design engineering
Evolutionary algorithms
Machines
Manufacturing
Mechatronics
Mutation
Nondestructive testing
Operators (mathematics)
Optimization
Processes
Production
Robotics
Robustness (mathematics)
Differential evolution
Triangular mutation
Engineering optimization
Constrained optimization
ISSN:0956-5515, 1572-8145
Online Access:Get full text
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Summary:This paper introduces a novel differential evolution (DE) algorithm for solving constrained engineering optimization problems called (NDE). The key idea of the proposed NDE is the use of new triangular mutation rule. It is based on the convex combination vector of the triplet defined by the three randomly chosen vectors and the difference vectors between the best, better and the worst individuals among the three randomly selected vectors. The main purpose of the new approach to triangular mutation operator is the search for better balance between the global exploration ability and the local exploitation tendency as well as enhancing the convergence rate of the algorithm through the optimization process. In order to evaluate and analyze the performance of NDE, numerical experiments on three sets of test problems with different features, including a comparison with thirty state-of-the-art evolutionary algorithms, are executed where 24 well-known benchmark test functions presented in CEC’2006, five widely used constrained engineering design problems and five constrained mechanical design problems from the literature are utilized. The results show that the proposed algorithm is competitive with, and in some cases superior to, the compared ones in terms of the quality, efficiency and robustness of the obtained final solutions.
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ISSN:0956-5515
1572-8145
DOI:10.1007/s10845-017-1294-6