Artificial chromosomes embedded in genetic algorithm for a chip resistor scheduling problem in minimizing the makespan

Authors:
Pei-Chann Chang;Jih-Chang Hsieh;Shih-Hsin Chen;Jun-Lin Lin;Wei-Hsiu Huang
Affiliations:
Department of Information Management, Yuan Ze University, 135 Yuan Tung Road, Taoyuan 320, Taiwan, ROC and Department of Information Management, Yuan Ze University, Taoyuan 320, Taiwan, ROC;Department of Finance, Vanung University, Chung-Li, Tao-Yuan, Taiwan, ROC;Department of Electronic Commerce Management, Nanhua University, 32 Chungkeng, Dalin, Chiayi 62248, Taiwan, ROC;Department of Information Management, Yuan Ze University, 135 Yuan Tung Road, Taoyuan 320, Taiwan, ROC;Department of Information Management, Yuan Ze University, Taoyuan 320, Taiwan, ROC
Venue:
Expert Systems with Applications: An International Journal
Year:
2009

Citing 8
Cited 5

A genetic algorithm for flowshop sequencing

Computers and Operations Research - Special issue on genetic algorithms
Genetic algorithms for flowshop scheduling problems

Computers and Industrial Engineering
An Application of Branch and Cut to Open Pit Mine Scheduling

Journal of Global Optimization
Improved genetic algorithm for the permutation flowshop scheduling problem

Computers and Operations Research
Sub-population genetic algorithm with mining gene structures for multiobjective flowshop scheduling problems

Expert Systems with Applications: An International Journal
Mining gene structures to inject artificial chromosomes for genetic algorithm in single machine scheduling problems

Applied Soft Computing
Genetic algorithms, path relinking, and the flowshop sequencing problem

Evolutionary Computation
Two-phase sub population genetic algorithm for parallel machine-scheduling problem

Expert Systems with Applications: An International Journal

Guidelines for developing effective Estimation of Distribution Algorithms in solving single machine scheduling problems

Expert Systems with Applications: An International Journal
Addressing lot sizing and warehousing scheduling problem in manufacturing environment

Expert Systems with Applications: An International Journal
Developing a varietal GA with ESMA strategy for solving the pick and place problem in printed circuit board assembly line

Journal of Intelligent Manufacturing
Hybrid Estimation of Distribution Algorithm for solving Single Row Facility Layout Problem

Computers and Industrial Engineering
Artificial chromosomes with genetic algorithm 2 (ACGA2) for single machine scheduling problems with sequence-dependent setup times

Applied Soft Computing

Quantified Score

Hi-index	12.05

Visualization

Abstract

The manufacturing processes of a chip resistor are very similar to a flowshop scheduling problem only with minor details which can be modeled using some extra constraints; while permutation flowshop scheduling problems (PFSPs) have attracted much attention in the research works. Many approaches like genetic algorithms were dedicated to solve PFSPs effectively and efficiently. In this paper, a novel approach is presented by embedding artificial chromosomes into the genetic algorithm to further improve the solution quality and to accelerate the convergence rate. The artificial chromosome generation mechanism first analyzes the job and position association existed in previous chromosomes and records the information in an association matrix. An association matrix is generated according to the job and position distribution from top 50% chromosomes. Artificial chromosomes are determined by performing a roulette wheel selection according to the marginal probability distribution of each position. Two types of PFSPs are considered for evaluation. One is a three-machine flowshop in the printing operation of a real-world chip resistor factory and the other is the standard benchmark problems retrieved from OR-Library. The result indicates that the proposed method is able to improve the solution quality significantly and accelerate the convergence process.