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A Novel Artificial Immune Algorithm for Solving the Job Shop Scheduling Problem

by Mohsen Afshari, Hedieh Sajedi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 48 - Number 14
Year of Publication: 2012
Authors: Mohsen Afshari, Hedieh Sajedi
10.5120/7420-0464

Mohsen Afshari, Hedieh Sajedi . A Novel Artificial Immune Algorithm for Solving the Job Shop Scheduling Problem. International Journal of Computer Applications. 48, 14 ( June 2012), 46-53. DOI=10.5120/7420-0464

@article{ 10.5120/7420-0464,
author = { Mohsen Afshari, Hedieh Sajedi },
title = { A Novel Artificial Immune Algorithm for Solving the Job Shop Scheduling Problem },
journal = { International Journal of Computer Applications },
issue_date = { June 2012 },
volume = { 48 },
number = { 14 },
month = { June },
year = { 2012 },
issn = { 0975-8887 },
pages = { 46-53 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume48/number14/7420-0464/ },
doi = { 10.5120/7420-0464 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:44:05.739938+05:30
%A Mohsen Afshari
%A Hedieh Sajedi
%T A Novel Artificial Immune Algorithm for Solving the Job Shop Scheduling Problem
%J International Journal of Computer Applications
%@ 0975-8887
%V 48
%N 14
%P 46-53
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Scheduling problems are difficult types of production arrangement problems that enumerated among NP-Complete problems. Some of evolutionary algorithms such as Genetic Algorithm, Ant Colony Optimization etc. have been used to solve this problem. In new years, Artificial Immune Algorithm is used to solve optimization problems such as routing and scheduling. One of complex scheduling problems is Job-shop Scheduling problem. In this article we use immune system concepts of human body, to implement a new artificial immune algorithm for solving Job-shop scheduling problem. A new population generation method was proposed based on G&T algorithm. We use two mutation methods, namely Shift Change method and Inverse method in Job-shop scheduling for first time. Moreover, we describe a vaccination method named MCV, to make maximum advance in solutions, and then achieve to more than one optimal solution concurrently and release from local optimum. Finally, we test our method on the very famous benchmark of JSP, namely FT06, then show experimental results and get some conclusions.

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Index Terms

Computer Science
Information Sciences

Keywords

Artificial Immune System Job-shop Scheduling Problem Mutation Vaccination Receptor Editing Clonal Selection

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