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http://dx.doi.org/10.7736/KSPE.2014.31.8.689

Multi-Objective Genetic Algorithm based on Multi-Robot Positions for Scheduling Problems  

Choi, Jong Hoon (Department of Automotive Engineering, Hanyang Univ.)
Kim, Je Seok (Department of Automotive Engineering, Hanyang Univ.)
Jeong, Jin Han (Department of Automotive Engineering, Hanyang Univ.)
Kim, Jung Min (Department of Mechanical Engineering, Ajou Univ.)
Park, Jahng Hyon (Department of Automotive Engineering, Hanyang Univ.)
Publication Information
Journal of the Korean Society for Precision Engineering / v.31, no.8, 2014 , pp. 689-696 More about this Journal
Abstract
This paper presents a scheduling problem for a high-density robotic workcell using multi-objective genetic algorithm. We propose a new algorithm based on NSGA-II(Non-dominated Sorting Algorithm-II) which is the most popular algorithm to solve multi-objective optimization problems. To solve the problem efficiently, the proposed algorithm divides the problem into two processes: clustering and scheduling. In clustering process, we focus on multi-robot positions because they are fixed in manufacturing system and have a great effect on task distribution. We test the algorithm by changing multi-robot positions and compare it to previous work. Test results shows that the proposed algorithm is effective under various conditions.
Keywords
Scheduling Problem; High-Density Robot; Multi-Objective Genetic Algorithm; Multi-Robot Position;
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Times Cited By KSCI : 1  (Citation Analysis)
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