Hybrid slime mould algorithm with adaptive guided differential evolution algorithm for combinatorial and global optimization problems

2021 ◽  
Vol 174 ◽  
pp. 114689
Author(s):  
Essam H. Houssein ◽  
Mohamed A. Mahdy ◽  
Maude J. Blondin ◽  
Doaa Shebl ◽  
Waleed M. Mohamed
Keyword(s):  
Global Optimization ◽  
Differential Evolution ◽  
Optimization Problems ◽  
Differential Evolution Algorithm ◽  
Slime Mould ◽  
Evolution Algorithm

scholarly journals Global optimization of laminated composite beams using an improved differential evolution algorithm

2020 ◽  
Vol 14 (1) ◽  
pp. 54-64
Author(s):  
Lam Thuan Phat ◽  
Nguyen Nhat Phi Long ◽  
Nguyen Hoai Son ◽  
Ho Huu Vinh ◽  
Le Anh Thang
Keyword(s):  
Global Optimization ◽  
Differential Evolution ◽  
Design Optimization ◽  
Optimization Problems ◽  
Differential Evolution Algorithm ◽  
Laminated Composite ◽  
Roulette Wheel Selection ◽  
Roulette Wheel ◽  
Evolution Algorithm ◽  
Improved Differential Evolution Algorithm

Differential Evolution (DE) is an efficient and effective algorithm recently proposed for solving optimization problems. In this paper, an improved version of Differential Evolution algorithm, called iDE, is introduced to solve design optimization problems of composite laminated beams. The beams used in this research are Timoshenko beam models computed based on analytical formula. The iDE is formed by modifying the mutation and the selection step of the original algorithm. Particularly, individuals involved in mutation were chosen by Roulette wheel selection via acceptant stochastic instead of the random selection. Meanwhile, in selection phase, the elitist operator is used for the selection progress instead of basic selection in the optimization process of the original DE algorithm. The proposed method is then applied to solve two problems of lightweight design optimization of the Timoshenko laminated composite beam with discrete variables. Numerical results obtained have been compared with those of the references and proved the effectiveness and efficiency of the proposed method. Keywords: improved Differential Evolution algorithm; Timoshenko composite laminated beam; elitist operator; Roulette wheel selection; deterministic global optimization.

Differential Evolution Algorithm with Space Reduction for Solving Large-Scale Global Optimization Problems

2017 ◽  
pp. 671-694
Author(s):  
Ahmed Fouad Ali ◽  
Nashwa Nageh Ahmed
Keyword(s):  
Global Optimization ◽  
Differential Evolution ◽  
Large Scale ◽  
Optimization Problems ◽  
Differential Evolution Algorithm ◽  
Search Space ◽  
Evolution Algorithm ◽  
Scale Spaces ◽  
Heuristics Algorithm ◽  
Scale Optimization

Differential evolution algorithm (DE) is one of the most applied meta-heuristics algorithm for solving global optimization problems. However, the contributions of applying DE for large-scale global optimization problems are still limited compared with those problems for low dimensions. In this chapter, a new differential evolution algorithm is proposed in order to solve large-scale optimization problems. The proposed algorithm is called differential evolution with space partitioning (DESP). In DESP algorithm, the search variables are divided into small groups of partitions. Each partition contains a certain number of variables and this partition is manipulated as a subspace in the search process. Searching a limited number of variables in each partition prevents the DESP algorithm from wandering in the search space especially in large-scale spaces. The proposed algorithm is investigated on 15 benchmark functions and compared against three variants DE algorithms. The results show that the proposed algorithm is a cheap algorithm and obtains good results in a reasonable time.

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