The raven roosting optimisation algorithm

被引:24
|
作者
Brabazon, Anthony [1 ,2 ]
Cui, Wei [1 ,2 ]
O'Neill, Michael [1 ,2 ]
机构
[1] Univ Coll Dublin, Complex Adapt Syst Lab, Dublin 2, Ireland
[2] Univ Coll Dublin, Sch Business, Dublin 2, Ireland
关键词
Social foraging; Social roosting; Raven roosting; Information centre; Optimisation; SOCIAL INFORMATION; HONEY-BEES; FOOD; RECRUITMENT; CENTERS;
D O I
10.1007/s00500-014-1520-5
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A significant stream of literature which draws inspiration from the foraging activities of various organisms to design optimisation algorithms has emerged over the past decade. The success of these algorithms across a wide variety of application domains has spurred interest in the examination of the foraging behaviours of other organisms to develop novel and powerful, optimisation algorithms. A variety of animals, including some species of birds and bats, engage in social roosting whereby large numbers of conspecifics gather together to roost, either overnight or for longer periods. It has been claimed that these roosts can serve as information centres to spread knowledge concerning the location of food resources in the environment. In this paper we look at the social roosting and foraging behaviour of one species of bird, the common raven, and take inspiration from this to design a novel optimisation algorithm which we call the raven roosting optimisation algorithm. The utility of the algorithm is assessed on a series of benchmark problems and the results are found to be competitive. We also provide a novel taxonomy which classifies foraging-inspired optimisation algorithms based on the underlying social communication mechanism embedded in the algorithms.
引用
收藏
页码:525 / 545
页数:21
相关论文
共 50 条
  • [1] The raven roosting optimisation algorithm
    Anthony Brabazon
    Wei Cui
    Michael O’Neill
    Soft Computing, 2016, 20 : 525 - 545
  • [2] Improved Raven Roosting Optimization algorithm (IRRO)
    Torabi, Shadi
    Safi-Esfahani, Faramarz
    SWARM AND EVOLUTIONARY COMPUTATION, 2018, 40 : 144 - 154
  • [3] A hybrid algorithm based on chicken swarm and improved raven roosting optimization
    Torabi, Shadi
    Safi-Esfahani, Faramarz
    SOFT COMPUTING, 2019, 23 (20) : 10129 - 10171
  • [4] A hybrid algorithm based on chicken swarm and improved raven roosting optimization
    Shadi Torabi
    Faramarz Safi-Esfahani
    Soft Computing, 2019, 23 : 10129 - 10171
  • [5] Hybrid raven roosting intelligence framework for enhancing efficiency in data clustering
    Malik, Saleem
    Patro, S. Gopal Krishna
    Mahanty, Chandrakanta
    Lasisi, Ayodele
    Al-sareji, Osamah J.
    SCIENTIFIC REPORTS, 2024, 14 (01):
  • [6] A dynamic task scheduling framework based on chicken swarm and improved raven roosting optimization methods in cloud computing
    Shadi Torabi
    Faramarz Safi-Esfahani
    The Journal of Supercomputing, 2018, 74 : 2581 - 2626
  • [7] A dynamic task scheduling framework based on chicken swarm and improved raven roosting optimization methods in cloud computing
    Torabi, Shadi
    Safi-Esfahani, Faramarz
    JOURNAL OF SUPERCOMPUTING, 2018, 74 (06): : 2581 - 2626
  • [8] Optimisation of EDM process parameters: by butterfly optimisation algorithm and genetic algorithm
    Jain S.
    Parashar V.
    International Journal of Computational Materials Science and Surface Engineering, 2022, 11 (01) : 21 - 46
  • [9] Portfolio Optimisation Using Ulimisana Optimisation Algorithm
    Maumela, Tshifhiwa
    Nelwamondo, Fulufhelo
    Marwala, Tshilidzi
    2022 8TH INTERNATIONAL CONFERENCE ON CONTROL, DECISION AND INFORMATION TECHNOLOGIES (CODIT'22), 2022, : 1250 - 1254
  • [10] CRYPTOGRAPHIC ALGORITHM OPTIMISATION
    Dhanuka, Suraj K.
    Sachdeva, Priyam
    Shaikh, Sharukh S.
    2015 IEEE INTERNATIONAL ADVANCE COMPUTING CONFERENCE (IACC), 2015, : 1111 - 1116