Differential Evolution Algorithm with Interval Type-2 Fuzzy Logic for the Optimization of the Mutation Parameter

2018 ◽  
pp. 55-65 ◽  
Author(s):  
Patricia Ochoa ◽  
Oscar Castillo ◽  
José Soria
Keyword(s):  
Fuzzy Logic ◽  
Differential Evolution ◽  
Differential Evolution Algorithm ◽  
Evolution Algorithm ◽  
Interval Type

An integer-coded differential evolution algorithm for simple assembly line balancing problem of type 2

2016 ◽  
Vol 36 (3) ◽  
pp. 246-261 ◽  
Author(s):  
Haijun Zhang ◽  
Qiong Yan ◽  
Yuanpeng Liu ◽  
Zhiqiang Jiang
Keyword(s):  
Differential Evolution ◽  
Assembly Line ◽  
Differential Evolution Algorithm ◽  
Assembly Line Balancing ◽  
Line Balancing ◽  
Content Type ◽  
Evolution Algorithm ◽  
Assembly Line Balancing Problem ◽  
Simple Assembly

Purpose This paper aims to develop a new differential evolution algorithm (DEA) for solving the simple assembly line balancing problem of type 2 (SALBP-2). Design/methodology/approach Novel approaches of mutation operator and crossover operator are presented. A self-adaptive double mutation scheme is implemented and an elitist strategy is used in the selection operator. Findings Test and comparison results show that the proposed IDEA obtains better results for SALBP-2. Originality/value The presented DEA is called the integer-coded differential evolution algorithm (IDEA), which can directly deal with integer variables of SALBP-2 on a discrete space without any posterior conversion. The proposed IDEA will be an alternative in evolutionary algorithms, especially for various integer/discrete-valued optimization problems.

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