Bin-Packing Using Genetic Algorithms

2005 ◽  
Author(s):  
A. Ponce-Perez ◽  
A. Perez-Garcia ◽  
V. Ayala-Ramirez
Keyword(s):  
Genetic Algorithms ◽  
Bin Packing

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

Hybrid algorithms for the earliness–tardiness single-machine multiple orders per job scheduling problem with a common due date

2018 ◽  
Vol 52 (4-5) ◽  
pp. 1329-1350 ◽  
Author(s):  
Jens Rocholl ◽  
Lars Mönch
Keyword(s):  
Genetic Algorithms ◽  
Single Machine ◽  
Bin Packing ◽  
Computing Time ◽  
Mixed Integer ◽  
Process Conditions ◽  
Scheduling Problem ◽  
Due Date ◽  
Semiconductor Wafer ◽  
Common Due Date

In this paper, we study an earliness–tardiness scheduling problem for a single machine that is motivated by process conditions found in semiconductor wafer fabrication facilities (wafer fabs). In modern 300-mm wafer fabs, front opening unified pods (FOUPs) transfer wafers. The number of FOUPs is limited to avoid a congestion of the Automated Material Handling System. Several orders can be grouped in one FOUP. A nonrestrictive common due date for all the orders is assumed. Only orders that belong to the same family can be processed together in a single FOUP at the same time. We present a Mixed Integer Linear Programming (MILP) formulation for this problem. Moreover, we show that this scheduling problem is NP-hard. We propose several simple heuristics based on dispatching rules and assignment strategies from bin packing. Moreover, genetic algorithms are designed that assign the orders to the set of early and tardy orders, respectively. In addition, a random key genetic algorithm (RKGA) is described that proposes order sequences. The different algorithms are hybridized with job formation and sequencing heuristics. A more specialized algorithm that is based on the generalized assignment problem is presented for the special case of a single order family. Results of computational experiments based on randomly generated problem instances are presented. They demonstrate that the genetic algorithms perform well with respect to solution quality and computing time under a broad range of experimental conditions.

Using distributed genetic algorithms in three-dimensional bin packing for rapid prototyping machines

1998 ◽  
Author(s):  
James E. Lewis ◽  
Rammohan K. Ragade ◽  
Anup Kumar ◽  
William E. Biles ◽  
Ilkka T. Ikonen
Keyword(s):  
Genetic Algorithms ◽  
Rapid Prototyping ◽  
Bin Packing ◽  
Three Dimensional ◽  
Distributed Genetic Algorithms
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