scholarly journals A Hybrid Greedy Algorithm and Simulated Annealing for Single Container Loading Problem: A Case Study

2019 ◽  
Vol 20 (2) ◽  
pp. 89
Author(s):  
Gede A Widyadana ◽  
Audrey Tedja Widjaja ◽  
Kun Jen Wang
Keyword(s):  
Greedy Algorithm ◽  
Three Dimensional ◽  
Computation Time ◽  
Computational Time ◽  
Container Loading ◽  
Flexible Packaging ◽  
Loading Problem ◽  
And Performance ◽  
Container Loading Problem

A single container loading problem is a problem to effectively load boxes in a three-dimensional container. There are many researchers in this problem try to find the best solution to solve the problem with feasible computation time and to develop some models to solve real case problem. Heuristics are the most method used to solve this problem since the problem is an NP-hard. In this paper, we introduce a hybrid greedy algorithm and simulate annealing algorithm to solve a real container loading problem in one flexible packaging company in Indonesia. Validation is used to show that the method can be applied practically. We use seven real cases to check the validity and performance of the model. The proposed method outperformed the solution developed by the company in all seven cases with feasible computational time.

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.

scholarly journals Problem solving of container loading using genetic algorithm based on modified random keys

2015 ◽  
Vol 4 (1) ◽  
pp. 190 ◽  
Author(s):  
Mohammad Sadegh Arefi ◽  
Hassan Rezaei
Keyword(s):  
Genetic Algorithm ◽  
Problem Solving ◽  
Evolutionary Algorithms ◽  
Global Optimum ◽  
Container Loading ◽  
Performance Time ◽  
Random Keys ◽  
Loading Problem ◽  
And Performance ◽  
Container Loading Problem

<p>This article presents a solution to the container loading problem. Container loading problem deals with how to put the cube boxes with different sizes in a container. Our proposed method is based on a particular kind of genetic algorithm based on biased random keys. In the proposed algorithm, we will face generations' extinction. Population decreases with time and with the staircase changes in the rate of elitism, the algorithm is guided towards the global optimum. Biased random keys in the proposed method are provided as discrete. The algorithm also provides the chromosomes that store more than one ability. In order to solve container loading using a placement strategy, due to the size of the boxes and containers, the containers are classified as small units and equal unites in size. Finally the algorithm presented in this paper was compared with three other methods that are based on evolutionary algorithms. The results show that the proposed algorithm has better performance in terms of results and performance time in relation to other methods.</p>

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