Genetic algorithms for the Multiple Container Packing Problem

1998 ◽  
pp. 875-884 ◽  
Author(s):  
Günther R. Raidl ◽  
Gabriele Kodydek
Keyword(s):  
Genetic Algorithms ◽  
Packing Problem

THE TWO-DIMENSIONAL PACKING PROBLEM FOR IRREGULAR OBJECTS

2004 ◽  
Vol 13 (03) ◽  
pp. 429-448 ◽  
Author(s):  
PING CHEN ◽  
ZHAOHUI FU ◽  
ANDREW LIM ◽  
BRIAN RODRIGUES
Keyword(s):  
Genetic Algorithms ◽  
Basic Problem ◽  
Piecewise Linear ◽  
Three Dimensional ◽  
Packing Problem ◽  
Two Dimensional ◽  
Linear Representations ◽  
Rectangular Packing ◽  
Work Done ◽  
Cutting Problems

Packing and cutting problems arise in a wide variety of industrial situations. The basic problem is that of determining a good arrangement of objects in a region without any overlap. Much research has been done on two and three dimensional rectangular packing while there has been little work done on irregular packing. In this work, we study the two-dimensional irregular packing problem and provide heuristic solutions which use rectilinear and piecewise-linear representations of objects. These heuristics include Genetic Algorithms and Tabu Search. Experimentation gives good results.

A study on the efficiency of neutral crossover operators in genetic algorithms applied to the bin packing problem

2014 ◽  
Author(s):  
Eneko Osaba ◽  
Fernando Diaz ◽  
Roberto Carballedo ◽  
Idoia de la Iglesia ◽  
Enrique Onieva ◽  
...  
Keyword(s):  
Genetic Algorithms ◽  
Bin Packing ◽  
Packing Problem ◽  
Bin Packing Problem

scholarly journals Genetic algorithms for the scheduling in additive manufacturing

2020 ◽  
Vol 8 (2) ◽  
pp. 59
Author(s):  
S. Castillo-Rivera ◽  
J. De Antón ◽  
R. Del Olmo ◽  
J. Pajares ◽  
A. López-Paredes
Keyword(s):  
Genetic Algorithms ◽  
Additive Manufacturing ◽  
Production Capacity ◽  
Packing Problem ◽  
Combinatorial Auctions ◽  
Operating Costs ◽  
Set Up

<p>Genetic Algorithms (GAs) are introduced to tackle the packing problem. The scheduling in Additive Manufacturing (AM) is also dealt with to set up a managed market, called “Lonja3D”. This will enable to determine an alternative tool through the combinatorial auctions, wherein the customers will be able to purchase the products at the best prices from the manufacturers. Moreover, the manufacturers will be able to optimize the production capacity and to decrease the operating costs in each case.</p>

Using genetic algorithms to solve quality-related bin packing problem

2007 ◽  
Vol 23 (1) ◽  
pp. 71-81 ◽  
Author(s):  
Felix T.S. Chan ◽  
K.C. Au ◽  
L.Y. Chan ◽  
T.L. Lau
Keyword(s):  
Genetic Algorithms ◽  
Bin Packing ◽  
Packing Problem ◽  
Bin Packing Problem

Genetic Algorithms with Adaptive Meta-heuristics for 2D Packing Problem

2003 ◽  
pp. 352-357
Author(s):  
Romuald Jagielski
Keyword(s):  
Genetic Algorithms ◽  
Packing Problem

Hybrid genetic algorithms for the three-dimensional multiple container packing problem

2013 ◽  
Vol 27 (2-3) ◽  
pp. 451-477 ◽  
Author(s):  
Xuehao Feng ◽  
Ilkyeong Moon ◽  
Jeongho Shin
Keyword(s):  
Genetic Algorithms ◽  
Three Dimensional ◽  
Packing Problem ◽  
Hybrid Genetic Algorithms

Two-Dimensional Packing Problems Using Genetic Algorithms

1996 ◽  
Author(s):  
Sakait Jain ◽  
Hae Chang Gea
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Finite Number ◽  
Packing Problem ◽  
Two Dimensional ◽  
Connectivity Analysis ◽  
Packing Problems ◽  
The Creation ◽  
New Feature ◽  
Number Of Cells

Abstract This paper presents a technique for applying genetic algorithms for the two dimensional packing problem. The approach is applicable to not only convex shaped objects, but, can also accommodate any type of concave and complex shaped objects including objects with holes. In this approach, a new concept of a two dimensional genetic chromosome is introduced. The total layout space is divided into a finite number of cells for mapping it into this 2-D genetic algorithm chromosome. The mutation and crossover operators have been modified and are applied in conjunction with connectivity analysis for the objects to reduce the creation of faulty generations. A new feature has been added to the genetic algorithm(GA) in the form of a new operator called compaction. Several examples of GA based layout are presented.

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