Paper Info
Title
Optimization of Heterogeneous Container Loading Problem with Adaptive Genetic Algorithm.
Abstract
This paper studies an optimized container loading problem with the goal of maximizing the 3D space utilization. Based on the characteristics of the mathematical loading model, we develop a dedicated placement heuristic integrated with a novel dynamic space division method, which enables the design of the adaptive genetic algorithm in order to maximize the loading space utilization. We use both weakly and strongly heterogeneous loading data to test the proposed algorithm. By choosing 15 classic sets of test data given by Loh and Nee as weakly heterogeneous data, the average space utilization of our algorithm reaching 70.62% outperforms those of 13 algorithms from the related literature. Taking a set of test data given by George and Robinson as strongly heterogeneous data, the space utilization in this paper can be improved by 4.42% in comparison with their heuristic algorithm.
Year
DOI
Venue
2018
10.1155/2018/2024184
COMPLEXITY
Field
DocType
Volume
Mathematical optimization,Heuristic,Heuristic (computer science),Heuristics,Artificial intelligence,Test data,Machine learning,Tabu search,Mathematics,Genetic algorithm
Journal
2018
ISSN
Citations 
PageRank 
1076-2787
0
0.34
References 
Authors
17
4
Name
Order
Citations
PageRank
Xianbo Xiang113611.27
Caoyang Yu2583.40
he xu33622.25
Stuart X. Zhu4816.20