Parallel Robot Scheduling to Minimize Mean Tardiness with Unequal Release Date and Precedence Constraints Using a Hybrid Intelligent System

Parallel Robot Scheduling to Minimize Mean Tardiness with Unequal Release Date and Precedence Constraints Using a Hybrid Intelligent System

This paper considers the problem of scheduling a given number of jobs on a specified number of identical parallel robots with unequal release dates and precedence constraints in order to minimize mean tardiness. This problem is strongly NP-hard. The author proposes a hybrid intelligent solution syst...

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Main Authors: Tarık Çakar, Raşit Köker, Yavuz Sarı
Format: Article
Language:English
Published: SAGE Publishing 2012-12-01
Series:International Journal of Advanced Robotic Systems
Online Access:https://doi.org/10.5772/54381
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spelling doaj-a65b777c625740e69c1373e487fb28262020-11-25T03:09:34ZengSAGE PublishingInternational Journal of Advanced Robotic Systems1729-88142012-12-01910.5772/5438110.5772_54381Parallel Robot Scheduling to Minimize Mean Tardiness with Unequal Release Date and Precedence Constraints Using a Hybrid Intelligent SystemTarık Çakar0Raşit Köker1Yavuz Sarı2 Sakarya University Engineering Faculty, Industrial Engineering Department, Sakarya, Turkey Sakarya University Technical Education Faculty, Department of Electronics and Computer Sciences, Sakarya, Turkey Sakarya University Hendek Vocational High School, Electronics and Automation Department, Sakarya, TurkeyThis paper considers the problem of scheduling a given number of jobs on a specified number of identical parallel robots with unequal release dates and precedence constraints in order to minimize mean tardiness. This problem is strongly NP-hard. The author proposes a hybrid intelligent solution system, which uses Genetic Algorithms and Simulated Annealing (GA+SA). A genetic algorithm, as is well known, is an efficient tool for the solution of combinatorial optimization problems. Solutions for problems of different scales are found using genetic algorithms, simulated annealing and a Hybrid Intelligent Solution System (HISS). Computational results of empirical experiments show that the Hybrid Intelligent Solution System (HISS) is successful with regards to solution quality and computational time.https://doi.org/10.5772/54381
collection DOAJ
language English
format Article
sources DOAJ
author Tarık Çakar
Raşit Köker
Yavuz Sarı
spellingShingle Tarık Çakar
Raşit Köker
Yavuz Sarı
Parallel Robot Scheduling to Minimize Mean Tardiness with Unequal Release Date and Precedence Constraints Using a Hybrid Intelligent System
International Journal of Advanced Robotic Systems
author_facet Tarık Çakar
Raşit Köker
Yavuz Sarı
author_sort Tarık Çakar
title Parallel Robot Scheduling to Minimize Mean Tardiness with Unequal Release Date and Precedence Constraints Using a Hybrid Intelligent System
title_short Parallel Robot Scheduling to Minimize Mean Tardiness with Unequal Release Date and Precedence Constraints Using a Hybrid Intelligent System
title_full Parallel Robot Scheduling to Minimize Mean Tardiness with Unequal Release Date and Precedence Constraints Using a Hybrid Intelligent System
title_fullStr Parallel Robot Scheduling to Minimize Mean Tardiness with Unequal Release Date and Precedence Constraints Using a Hybrid Intelligent System
title_full_unstemmed Parallel Robot Scheduling to Minimize Mean Tardiness with Unequal Release Date and Precedence Constraints Using a Hybrid Intelligent System
title_sort parallel robot scheduling to minimize mean tardiness with unequal release date and precedence constraints using a hybrid intelligent system
publisher SAGE Publishing
series International Journal of Advanced Robotic Systems
issn 1729-8814
publishDate 2012-12-01
description This paper considers the problem of scheduling a given number of jobs on a specified number of identical parallel robots with unequal release dates and precedence constraints in order to minimize mean tardiness. This problem is strongly NP-hard. The author proposes a hybrid intelligent solution system, which uses Genetic Algorithms and Simulated Annealing (GA+SA). A genetic algorithm, as is well known, is an efficient tool for the solution of combinatorial optimization problems. Solutions for problems of different scales are found using genetic algorithms, simulated annealing and a Hybrid Intelligent Solution System (HISS). Computational results of empirical experiments show that the Hybrid Intelligent Solution System (HISS) is successful with regards to solution quality and computational time.
url https://doi.org/10.5772/54381
work_keys_str_mv AT tarıkcakar parallelrobotschedulingtominimizemeantardinesswithunequalreleasedateandprecedenceconstraintsusingahybridintelligentsystem
AT rasitkoker parallelrobotschedulingtominimizemeantardinesswithunequalreleasedateandprecedenceconstraintsusingahybridintelligentsystem
AT yavuzsarı parallelrobotschedulingtominimizemeantardinesswithunequalreleasedateandprecedenceconstraintsusingahybridintelligentsystem
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