Solving Stereo Warehouse Storage Location Assignment Problem Based on Genetic Algorithm

2013 ◽  
Vol 307 ◽  
pp. 459-463 ◽  
Author(s):  
Meng Jin ◽  
Xi Hui Mu ◽  
Liang Chun Li ◽  
Feng Po Du
Keyword(s):  
Genetic Algorithm ◽  
Programming Model ◽  
Data Sets ◽  
Improved Genetic Algorithm ◽  
Storage Location ◽  
Genetic Algorithm Method ◽  
Warehouse Storage ◽  
Storage Area ◽  
Location Assignment ◽  
Number Of Classes

Class-based stereo warehouse storage policy distributes products among a number of classes and for each class it reserves a region within the storage area. In this paper, a genetic algorithm method of using the intersectant operation of chromosome repair and mutation operation of two-way movement detection is developed to solve an integer programming model for storage assignment. Computational experience on randomly generated data sets and an industrial case shows that improved genetic algorithm gives superior results than the genetic algorithm without improving for storage location assignment with ordering restriction.

A Genetic Algorithm for Minimizing Relocations at Container Yard in Container Terminal

2014 ◽  
Vol 931-932 ◽  
pp. 1683-1688
Author(s):  
Phatchara Sriphrabu ◽  
Kanchana Sethanan ◽  
Somnuk Theerakulpisut
Keyword(s):  
Genetic Algorithm ◽  
Current Practice ◽  
Container Terminal ◽  
Experimental Result ◽  
Container Ship ◽  
Storage Assignment ◽  
Storage Location ◽  
Location Assignment

This paper focuses on storage location assignment and exported container relocation in container yard of container terminal with the objective of minimizing the number of container lifting. On the lifting steps, the truck with yard crane should be chosen in order to deliver a container from container yard to container ship, and this action can reduce container ship's docking time and increase effectiveness in container terminal service. In this paper, a genetic algorithm (GA) in container storage assignment and a heuristic for the container relocation determination are adopted. Also, the current practice including first-in-first-stored (FIFS) and simple relocation (SR) is used to compare the effectiveness of the GA and the proposed heuristic (RH). The experimental result presented that the proposed method is able to construct the effective solutions of storage location assignment of exported containers, and it reduces the number of relocations of exported container effectively.

Ship Cabin Layout Optimization Design Based on the Improved Genetic Algorithm Method

2013 ◽  
Vol 300-301 ◽  
pp. 146-149 ◽  
Author(s):  
Yun Long Wang ◽  
Chen Wang ◽  
Yan Lin
Keyword(s):  
Genetic Algorithm ◽  
Optimization Design ◽  
Optimal Solution ◽  
Optimization Techniques ◽  
The Other ◽  
Improved Genetic Algorithm ◽  
Local Optimal Solution ◽  
Genetic Algorithm Method ◽  
Np Hard Problem ◽  
The One

Based on the improved genetic algorithm method, a kind of the optimization techniques to solve the problem about the ship cabin layout is presented. The problem about the ship cabin layout is a NP-hard problem. This article has used the genetic algorithm method to solve it .However, for the simple and easy procedure, the basic genetic algorithm is slow and easy to fall into a local optimal solution. Therefore, it must be improved. This article has made the following two improvements: on the one hand using the niche method to solve the multi- peak problem; on the other hand using the climbing method to solve the slow and premature convergence. The simulation tests show that this approach proposed by authors is feasible and valid and the result is satisfied.

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