Effects of memory and genetic operators on Artificial Bee Colony algorithm for Single Container Loading problem

2021 ◽  
Vol 108 ◽  
pp. 107462
Author(s):  
Tuğrul Bayraktar ◽  
Filiz Ersöz ◽  
Cemalettin Kubat
Keyword(s):  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Genetic Operators ◽  
Container Loading ◽  
Bee Colony ◽  
Loading Problem ◽  
Container Loading Problem

A novel binary artificial bee colony algorithm based on genetic operators

2015 ◽  
Vol 297 ◽  
pp. 154-170 ◽  
Author(s):  
Celal Ozturk ◽  
Emrah Hancer ◽  
Dervis Karaboga
Keyword(s):  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Genetic Operators ◽  
Bee Colony

Study on Container Loading Problem Based on NSGA-α Algorithm

2013 ◽  
Vol 753-755 ◽  
pp. 2954-2958
Author(s):  
Fei Cao
Keyword(s):  
Three Dimensional ◽  
Packing Problem ◽  
Genetic Operators ◽  
Nsga Ii ◽  
Container Loading ◽  
Novel Approach ◽  
Loading Problem ◽  
Np Complete ◽  
Encoding Method ◽  
Container Loading Problem

Container loading problem with multi-constraints is usually modeled as a three-dimensional packing problem which is known to be NP-complete. This paper presents a novel approach to resolve the container loading problem via multi-objective optimization algorithm (NSGA-II). Specific encoding method and genetic operators are designed based on the mathematics description of the problem. The process also takes several practical constraints into account. Simulation results show that this approach is feasible and effective.

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