The Experts below are selected from a list of 5352 Experts worldwide ranked by ideXlab platform
Houbin Song - One of the best experts on this subject based on the ideXlab platform.
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a hybrid discrete water wave optimization algorithm for the no idle flowshop scheduling problem with total tardiness criterion
Expert Systems With Applications, 2020Co-Authors: Fuqing Zhao, Lixin Zhang, Yi Zhang, Chuck Zhang, Houbin SongAbstract:Abstract The no-idle flowshop has attracted enormous attention owing to its widespread application in the manufacturing industry domain. In this paper, a hybrid discrete water wave optimization algorithm, named HWWO, is presented to solve the NIFSP with total tardiness. In order to improve the quality of a population, an Initialize Method based on a new priority rule combined with the modified NEH Method is proposed to generate a population. In the propagation phase, a self-adaption selection neighborhood search structure is introduced to amplify the search range of waves and balance the exploration and exploitation ability of the HWWO. Afterwards, a variable neighborhood search is adopted to strengthen the local search and maintain the diversity of the population in the breaking phase. In the refraction operation, a perturbation sequence is generated and combined with the local optimal solution found by the breaking operation, in order to generate a new solution, and prevent the algorithm from becoming trapped in the local optimum. Furthermore, the control parameters and time complexity are analyzed. The experimental results and comparisons with the other state-of-the-art algorithms evaluated on Taillard's and Ruiz's benchmark sets reveal that the effectiveness and efficiency of the HWWO outperformed the compared algorithms for solving the NIFSP.
Fuqing Zhao - One of the best experts on this subject based on the ideXlab platform.
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a hybrid discrete water wave optimization algorithm for the no idle flowshop scheduling problem with total tardiness criterion
Expert Systems With Applications, 2020Co-Authors: Fuqing Zhao, Lixin Zhang, Yi Zhang, Chuck Zhang, Houbin SongAbstract:Abstract The no-idle flowshop has attracted enormous attention owing to its widespread application in the manufacturing industry domain. In this paper, a hybrid discrete water wave optimization algorithm, named HWWO, is presented to solve the NIFSP with total tardiness. In order to improve the quality of a population, an Initialize Method based on a new priority rule combined with the modified NEH Method is proposed to generate a population. In the propagation phase, a self-adaption selection neighborhood search structure is introduced to amplify the search range of waves and balance the exploration and exploitation ability of the HWWO. Afterwards, a variable neighborhood search is adopted to strengthen the local search and maintain the diversity of the population in the breaking phase. In the refraction operation, a perturbation sequence is generated and combined with the local optimal solution found by the breaking operation, in order to generate a new solution, and prevent the algorithm from becoming trapped in the local optimum. Furthermore, the control parameters and time complexity are analyzed. The experimental results and comparisons with the other state-of-the-art algorithms evaluated on Taillard's and Ruiz's benchmark sets reveal that the effectiveness and efficiency of the HWWO outperformed the compared algorithms for solving the NIFSP.
Lixin Zhang - One of the best experts on this subject based on the ideXlab platform.
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a hybrid discrete water wave optimization algorithm for the no idle flowshop scheduling problem with total tardiness criterion
Expert Systems With Applications, 2020Co-Authors: Fuqing Zhao, Lixin Zhang, Yi Zhang, Chuck Zhang, Houbin SongAbstract:Abstract The no-idle flowshop has attracted enormous attention owing to its widespread application in the manufacturing industry domain. In this paper, a hybrid discrete water wave optimization algorithm, named HWWO, is presented to solve the NIFSP with total tardiness. In order to improve the quality of a population, an Initialize Method based on a new priority rule combined with the modified NEH Method is proposed to generate a population. In the propagation phase, a self-adaption selection neighborhood search structure is introduced to amplify the search range of waves and balance the exploration and exploitation ability of the HWWO. Afterwards, a variable neighborhood search is adopted to strengthen the local search and maintain the diversity of the population in the breaking phase. In the refraction operation, a perturbation sequence is generated and combined with the local optimal solution found by the breaking operation, in order to generate a new solution, and prevent the algorithm from becoming trapped in the local optimum. Furthermore, the control parameters and time complexity are analyzed. The experimental results and comparisons with the other state-of-the-art algorithms evaluated on Taillard's and Ruiz's benchmark sets reveal that the effectiveness and efficiency of the HWWO outperformed the compared algorithms for solving the NIFSP.
Yi Zhang - One of the best experts on this subject based on the ideXlab platform.
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a hybrid discrete water wave optimization algorithm for the no idle flowshop scheduling problem with total tardiness criterion
Expert Systems With Applications, 2020Co-Authors: Fuqing Zhao, Lixin Zhang, Yi Zhang, Chuck Zhang, Houbin SongAbstract:Abstract The no-idle flowshop has attracted enormous attention owing to its widespread application in the manufacturing industry domain. In this paper, a hybrid discrete water wave optimization algorithm, named HWWO, is presented to solve the NIFSP with total tardiness. In order to improve the quality of a population, an Initialize Method based on a new priority rule combined with the modified NEH Method is proposed to generate a population. In the propagation phase, a self-adaption selection neighborhood search structure is introduced to amplify the search range of waves and balance the exploration and exploitation ability of the HWWO. Afterwards, a variable neighborhood search is adopted to strengthen the local search and maintain the diversity of the population in the breaking phase. In the refraction operation, a perturbation sequence is generated and combined with the local optimal solution found by the breaking operation, in order to generate a new solution, and prevent the algorithm from becoming trapped in the local optimum. Furthermore, the control parameters and time complexity are analyzed. The experimental results and comparisons with the other state-of-the-art algorithms evaluated on Taillard's and Ruiz's benchmark sets reveal that the effectiveness and efficiency of the HWWO outperformed the compared algorithms for solving the NIFSP.
Chuck Zhang - One of the best experts on this subject based on the ideXlab platform.
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a hybrid discrete water wave optimization algorithm for the no idle flowshop scheduling problem with total tardiness criterion
Expert Systems With Applications, 2020Co-Authors: Fuqing Zhao, Lixin Zhang, Yi Zhang, Chuck Zhang, Houbin SongAbstract:Abstract The no-idle flowshop has attracted enormous attention owing to its widespread application in the manufacturing industry domain. In this paper, a hybrid discrete water wave optimization algorithm, named HWWO, is presented to solve the NIFSP with total tardiness. In order to improve the quality of a population, an Initialize Method based on a new priority rule combined with the modified NEH Method is proposed to generate a population. In the propagation phase, a self-adaption selection neighborhood search structure is introduced to amplify the search range of waves and balance the exploration and exploitation ability of the HWWO. Afterwards, a variable neighborhood search is adopted to strengthen the local search and maintain the diversity of the population in the breaking phase. In the refraction operation, a perturbation sequence is generated and combined with the local optimal solution found by the breaking operation, in order to generate a new solution, and prevent the algorithm from becoming trapped in the local optimum. Furthermore, the control parameters and time complexity are analyzed. The experimental results and comparisons with the other state-of-the-art algorithms evaluated on Taillard's and Ruiz's benchmark sets reveal that the effectiveness and efficiency of the HWWO outperformed the compared algorithms for solving the NIFSP.