Comparison between genetic algorithm and differential evolution algorithm applied to one dimensional bin-packing problem

2016 ◽  
Author(s):  
Shi-Yuan Han ◽  
Xiao-Yu Wan ◽  
Lin Wang ◽  
Jin Zhou ◽  
Xiao-Fang Zhong
Keyword(s):  
Genetic Algorithm ◽  
Differential Evolution ◽  
Bin Packing ◽  
Differential Evolution Algorithm ◽  
Packing Problem ◽  
One Dimensional ◽  
Bin Packing Problem ◽  
Evolution Algorithm

A Genetic Algorithm with Weight-Based Encoding for One-Dimensional Bin Packing Problem

2012 ◽  
Vol 182-183 ◽  
pp. 2100-2104 ◽  
Author(s):  
Yao Tang Lin ◽  
Jia Li Hou
Keyword(s):  
Genetic Algorithm ◽  
Bin Packing ◽  
Packing Problem ◽  
Data Set ◽  
One Dimensional ◽  
Benchmark Data ◽  
Bin Packing Problem ◽  
Benchmark Instances ◽  
Problem Instances ◽  
Better Than

This paper proposes a specialized genetic algorithm (GA) based on an expended relational representation named weight-based encoding for solving one-dimensional bin packing problem (BPP-1). The encoding provides a totally constraint-handling scheme to address general and specific constraints, while naturally eliminates redundancy and infeasibility of previous representations for BPP-1. The current study performs experiments for solving some problem instances from a benchmark data set by our specific coded genetic algorithm with one-point, two-point and grouping crossovers. Experimental results show that the proposed methodology works well for solving BPP-1 and performs well on experimented benchmark instances. In addition, the results also show that two-point and grouping crossovers work better than one-point crossover in our experiments.

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