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TitleNew particle swarm optimization algorithm for makespan minimization in permutation flowshop sequencing
CreatorChen, Tingyu;Chen, Chuenlung
陳春龍
Contributor資訊管理學系
Key WordsMakespan; Makespan minimization; New particle swarm optimization; Permutation flow shops; Permutation flowshop scheduling problems; PSO algorithms; Random keys; Scheduling algorithms; Particle swarm optimization (PSO)
Date2009-12
Date Issued1-Jun-2015 17:24:42 (UTC+8)
SummaryParticle Swarm Optimization (PSO) is a new type of heuristic inspired by the flocking behavior of birds. This paper presents a Particle Swarm Optimization (PSO) to solve the permutation flowshop scheduling problem (PFSP) objectives, to minimize the makespan. To this end, we have proposed the use of discrete PSO algorithm for the position of the smallest value (SPV) to use a random key representation of Bean [Baena Bean, Genetic algorithms and random keys sequencing and optimization, Orsa calculated Journal 6 (2) (1994) 154-160]. In the proposed algorithm, the particle and the velocity re-defined and effective way to develop a series of new particles. In addition, we analyzed the characteristics of the elite jobs in the proposed algorithm. The results showed that the idea really follows the approach of PSO. © 2009 IEEE.
Relation2009 4th International Conference on Innovative Computing, Information and Control, ICICIC 2009,868-871
Typeconference
DOI http://dx.doi.org/10.1109/ICICIC.2009.278
dc.contributor 資訊管理學系
dc.creator (作者) Chen, Tingyu;Chen, Chuenlung
dc.creator (作者) 陳春龍zh_TW
dc.date (日期) 2009-12
dc.date.accessioned 1-Jun-2015 17:24:42 (UTC+8)-
dc.date.available 1-Jun-2015 17:24:42 (UTC+8)-
dc.date.issued (上傳時間) 1-Jun-2015 17:24:42 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/75477-
dc.description.abstract (摘要) Particle Swarm Optimization (PSO) is a new type of heuristic inspired by the flocking behavior of birds. This paper presents a Particle Swarm Optimization (PSO) to solve the permutation flowshop scheduling problem (PFSP) objectives, to minimize the makespan. To this end, we have proposed the use of discrete PSO algorithm for the position of the smallest value (SPV) to use a random key representation of Bean [Baena Bean, Genetic algorithms and random keys sequencing and optimization, Orsa calculated Journal 6 (2) (1994) 154-160]. In the proposed algorithm, the particle and the velocity re-defined and effective way to develop a series of new particles. In addition, we analyzed the characteristics of the elite jobs in the proposed algorithm. The results showed that the idea really follows the approach of PSO. © 2009 IEEE.
dc.relation (關聯) 2009 4th International Conference on Innovative Computing, Information and Control, ICICIC 2009,868-871
dc.subject (關鍵詞) Makespan; Makespan minimization; New particle swarm optimization; Permutation flow shops; Permutation flowshop scheduling problems; PSO algorithms; Random keys; Scheduling algorithms; Particle swarm optimization (PSO)
dc.title (題名) New particle swarm optimization algorithm for makespan minimization in permutation flowshop sequencing
dc.type (資料類型) conferenceen
dc.identifier.doi (DOI) 10.1109/ICICIC.2009.278
dc.doi.uri (DOI) http://dx.doi.org/10.1109/ICICIC.2009.278