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Author:

Yao, Baozhen (Yao, Baozhen.) | Yang, Chengyong (Yang, Chengyong.) | Hu, Juanjuan (Hu, Juanjuan.) | Yin, Guodong (Yin, Guodong.) | Yu, Bo (Yu, Bo.)

Indexed by:

CPCI-S EI Scopus

Abstract:

Job shop scheduling problem (JSP) plays a significant role for production management and combinatorial optimization. An improved artificial bee colony (IABC) algorithm with mutation operation is presented to solve JSP in this paper. The results for some benchmark problems reveal that IABC is effective and efficient compared to those of other approaches. IABC seems to be a powerful tool for optimizing job shop scheduling problem.

Keyword:

Artificial bee colony algorithm Job shop scheduling problem Mutation operation

Author Community:

  • [ 1 ] [Yao, Baozhen]Beijing Jiaotong Univ, Sch Civil Engn & Architecture, Beijing 100044, Peoples R China
  • [ 2 ] [Yang, Chengyong]Beijing Jiaotong Univ, Sch Civil Engn & Architecture, Beijing 100044, Peoples R China
  • [ 3 ] [Yin, Guodong]Beijing Jiaotong Univ, Sch Civil Engn & Architecture, Beijing 100044, Peoples R China
  • [ 4 ] [Hu, Juanjuan]Minist Transport Peoples Republ China, Transport Management Inst, Beijing 101601, Peoples R China
  • [ 5 ] [Hu, Juanjuan]Beijing Univ Technol, Coll Architecture & Civil Engn, Beijing 100022, Peoples R China
  • [ 6 ] [Yu, Bo]Dalian Maritime Univ, Transportat Management Coll, Dalian 116026, Peoples R China

Reprint Author's Address:

  • [Yao, Baozhen]Beijing Jiaotong Univ, Sch Civil Engn & Architecture, Beijing 100044, Peoples R China

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Source :

ADVANCED MECHANICAL ENGINEERING, PTS 1 AND 2

ISSN: 1660-9336

Year: 2010

Volume: 26-28

Page: 657-,

Language: English

Cited Count:

WoS CC Cited Count: 15

SCOPUS Cited Count: 24

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 12

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