DocumentCode :
253476
Title :
Solving job shop scheduling problem with Ant Colony Optimization
Author :
Turguner, Cansin ; Sahingoz, Ozgur Koray
Author_Institution :
Comput. Eng. Dept., Turkish Air Force Acad., Istanbul, Turkey
fYear :
2014
fDate :
19-21 Nov. 2014
Firstpage :
385
Lastpage :
389
Abstract :
Job Shop Scheduling Problem (JSSP) is one of the important and tough problem in real world, which tries to schedule N jobs to be performed on M machines. In this paper, it is aimed to imply this problem in computer science and also bringing up many related solution models. Although, most of these models try to find an optimal approach, Ant Colony Optimization (ACO) constitutes the optimal solution by using some of the complex ACO scenarios effectively. In this study, it is focused on one of the scenario of the JSSP and explained in which steps are used in the ACO solution. With simulation study, it is aimed to show, how ACO copes with the JSSP clearly.
Keywords :
ant colony optimisation; job shop scheduling; ACO; JSSP; ant colony optimization; computer science; job shop scheduling problem; Ant colony optimization; Equations; Genetic algorithms; Job shop scheduling; Mathematical model; Optimization; Ant Colony Optimization; Job Shop Scheduling Problem; Related Solutions;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Informatics (CINTI), 2014 IEEE 15th International Symposium on
Conference_Location :
Budapest
Type :
conf
DOI :
10.1109/CINTI.2014.7028706
Filename :
7028706
Link To Document :
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