The Experts below are selected from a list of 95214 Experts worldwide ranked by ideXlab platform

Mario Vanhoucke - One of the best experts on this subject based on the ideXlab platform.

  • a hybrid electromagnetism like mechanism tabu Search Procedure for the single machine scheduling problem with a maximum lateness objective
    Computers & Industrial Engineering, 2014
    Co-Authors: Veronique Sels, Mario Vanhoucke
    Abstract:

    This paper presents a hybrid meta-heuristic Search Procedure to solve the well-known single machine scheduling problem to minimize the maximum lateness over all jobs, where precedence relations may exist between some of the jobs. The hybridization consists of a well-designed balance between the principles borrowed from an Electromagnetism-like Mechanism algorithm and the characteristics used in a tabu Search Procedure. The Electromagnetism-like Mechanism (EM) algorithm follows a Search pattern based on the theory of physics to simulate attraction and repulsion of solutions in order to move towards more promising solutions. The well-known tabu Search enhances the performance of a local Search method by using memory structures by prohibiting visited solutions during a certain time of the Search process. The hybridization of both algorithms results in an important trade-off between intensification and diversification strategies. These strategies will be discussed in detail. To that purpose, a new set of data instances is used to compare different elements of the hybrid Search Procedure and to validate the performance of the algorithm.

  • A hybrid Electromagnetism-like Mechanism/tabu Search Procedure for the single machine scheduling problem with a maximum lateness objective
    Computers & Industrial Engineering, 2013
    Co-Authors: Veronique Sels, Mario Vanhoucke
    Abstract:

    This paper presents a hybrid meta-heuristic Search Procedure to solve the well-known single machine scheduling problem to minimize the maximum lateness over all jobs, where precedence relations may exist between some of the jobs. The hybridization consists of a well-designed balance between the principles borrowed from an Electromagnetism-like Mechanism algorithm and the characteristics used in a tabu Search Procedure. The Electromagnetism-like Mechanism (EM) algorithm follows a Search pattern based on the theory of physics to simulate attraction and repulsion of solutions in order to move towards more promising solutions. The well-known tabu Search enhances the performance of a local Search method by using memory structures by prohibiting visited solutions during a certain time of the Search process. The hybridization of both algorithms results in an important trade-off between intensification and diversification strategies. These strategies will be discussed in detail. To that purpose, a new set of data instances is used to compare different elements of the hybrid Search Procedure and to validate the performance of the algorithm.

  • a hybrid single and dual population Search Procedure for the job shop scheduling problem
    European Journal of Operational Research, 2011
    Co-Authors: Veronique Sels, Mario Vanhoucke, Kjeld Craeymeersch
    Abstract:

    This paper presents a genetic algorithm and a scatter Search Procedure to solve the well-known job shop scheduling problem. In contrast to the single population Search performed by the genetic algorithm, the scatter Search algorithm splits the population of solutions in a diverse and high-quality set to exchange information between individuals in a controlled way. The extension from a single to a dual population, by taking problem specific characteristics into account, can be seen as a stimulator to add diversity in the Search process. This has a positive influence on the important balance between intensification and diversification. Computational experiments verify the benefit of this diversity on the effectiveness of the meta-heuristic Search process. Various algorithmic parameters from literature are embedded in both Procedures and a detailed comparison is made. A set of standard instances is used to compare the different approaches and the best obtained results are benchmarked against heuristic solutions found in literature.

J R Wilson - One of the best experts on this subject based on the ideXlab platform.

  • a revised simplex Search Procedure for stochastic simulation response surface optimization
    Informs Journal on Computing, 2000
    Co-Authors: David G Humphrey, J R Wilson
    Abstract:

    We develop a variant of the Nelder-Mead (NM) simplex Search Procedure for stochastic simulation optimization that is designed to avoid many of the weaknesses encumbering similar direct-Search methods--in particular, excessive sensitivity to starting values, premature termination at a local optimum, lack of robustness against noisy responses, and computational inefficiency. The Revised Simplex Search (RSS) Procedure consists of a three-phase application of the NM method in which: (a) the ending values for one phase become the starting values for the next phase; (b) the step size for the initial simplex (respectively, the shrink coefficient) decreases geometrically (respectively, increases linearly) over successive phases; and (c) the final estimated optimum is the best of the ending values for the three phases. To compare RSS versus NM and Procedure RS+S9 due to Barton and Ivey, we summarize a simulation study based on four selected performance measures computed for six test problems that include additive white-noise error, with three levels of problem dimensionality and noise variability used in each problem. In the selected test problems, RSS yielded significantly more accurate estimates of the optimum than NM or RS+S9, and both RSS and RS+S9 required roughly four times as many function evaluations as NM.

  • a revised simplex Search Procedure for stochastic simulation response surface optimization
    Winter Simulation Conference, 1998
    Co-Authors: David G Humphrey, J R Wilson
    Abstract:

    We develop a variant of the Nelder-Mead (NM) simplex Search Procedure for stochastic simulation optimization that is designed to avoid many of the weaknesses encumbering such direct-Search methods-in particular, excessive sensitivity to starting values, premature termination at a local optimum, lack of robustness against noisy responses, and lack of computational efficiency. The revised simplex Search (RSS) Procedure consists of a three-phase application of the NM method in which: (a) the ending values for one phase become the starting values for the next phase; (b) the size of the initial simplex (respectively, the shrink coefficient) decreases geometrically (respectively, increases linearly) over successive phases; and (c) the final estimated optimum is the best of the ending values for the three phases. To compare RSS versus the NM Procedure and RS9 (a simplex Search Procedure recently proposed by Barton and Ivey (1996)), we summarize a simulation study based on separate factorial experiments and follow-up multiple comparisons tests for four selected performance measures computed on each of six test problems, with three levels of problem dimensionality and noise variability used in each problem. The experimental results provide substantial evidence of RSS's improved performance with only marginally higher computational effort.

Veronique Sels - One of the best experts on this subject based on the ideXlab platform.

  • a hybrid electromagnetism like mechanism tabu Search Procedure for the single machine scheduling problem with a maximum lateness objective
    Computers & Industrial Engineering, 2014
    Co-Authors: Veronique Sels, Mario Vanhoucke
    Abstract:

    This paper presents a hybrid meta-heuristic Search Procedure to solve the well-known single machine scheduling problem to minimize the maximum lateness over all jobs, where precedence relations may exist between some of the jobs. The hybridization consists of a well-designed balance between the principles borrowed from an Electromagnetism-like Mechanism algorithm and the characteristics used in a tabu Search Procedure. The Electromagnetism-like Mechanism (EM) algorithm follows a Search pattern based on the theory of physics to simulate attraction and repulsion of solutions in order to move towards more promising solutions. The well-known tabu Search enhances the performance of a local Search method by using memory structures by prohibiting visited solutions during a certain time of the Search process. The hybridization of both algorithms results in an important trade-off between intensification and diversification strategies. These strategies will be discussed in detail. To that purpose, a new set of data instances is used to compare different elements of the hybrid Search Procedure and to validate the performance of the algorithm.

  • A hybrid Electromagnetism-like Mechanism/tabu Search Procedure for the single machine scheduling problem with a maximum lateness objective
    Computers & Industrial Engineering, 2013
    Co-Authors: Veronique Sels, Mario Vanhoucke
    Abstract:

    This paper presents a hybrid meta-heuristic Search Procedure to solve the well-known single machine scheduling problem to minimize the maximum lateness over all jobs, where precedence relations may exist between some of the jobs. The hybridization consists of a well-designed balance between the principles borrowed from an Electromagnetism-like Mechanism algorithm and the characteristics used in a tabu Search Procedure. The Electromagnetism-like Mechanism (EM) algorithm follows a Search pattern based on the theory of physics to simulate attraction and repulsion of solutions in order to move towards more promising solutions. The well-known tabu Search enhances the performance of a local Search method by using memory structures by prohibiting visited solutions during a certain time of the Search process. The hybridization of both algorithms results in an important trade-off between intensification and diversification strategies. These strategies will be discussed in detail. To that purpose, a new set of data instances is used to compare different elements of the hybrid Search Procedure and to validate the performance of the algorithm.

  • a hybrid single and dual population Search Procedure for the job shop scheduling problem
    European Journal of Operational Research, 2011
    Co-Authors: Veronique Sels, Mario Vanhoucke, Kjeld Craeymeersch
    Abstract:

    This paper presents a genetic algorithm and a scatter Search Procedure to solve the well-known job shop scheduling problem. In contrast to the single population Search performed by the genetic algorithm, the scatter Search algorithm splits the population of solutions in a diverse and high-quality set to exchange information between individuals in a controlled way. The extension from a single to a dual population, by taking problem specific characteristics into account, can be seen as a stimulator to add diversity in the Search process. This has a positive influence on the important balance between intensification and diversification. Computational experiments verify the benefit of this diversity on the effectiveness of the meta-heuristic Search process. Various algorithmic parameters from literature are embedded in both Procedures and a detailed comparison is made. A set of standard instances is used to compare the different approaches and the best obtained results are benchmarked against heuristic solutions found in literature.

David G Humphrey - One of the best experts on this subject based on the ideXlab platform.

  • a revised simplex Search Procedure for stochastic simulation response surface optimization
    Informs Journal on Computing, 2000
    Co-Authors: David G Humphrey, J R Wilson
    Abstract:

    We develop a variant of the Nelder-Mead (NM) simplex Search Procedure for stochastic simulation optimization that is designed to avoid many of the weaknesses encumbering similar direct-Search methods--in particular, excessive sensitivity to starting values, premature termination at a local optimum, lack of robustness against noisy responses, and computational inefficiency. The Revised Simplex Search (RSS) Procedure consists of a three-phase application of the NM method in which: (a) the ending values for one phase become the starting values for the next phase; (b) the step size for the initial simplex (respectively, the shrink coefficient) decreases geometrically (respectively, increases linearly) over successive phases; and (c) the final estimated optimum is the best of the ending values for the three phases. To compare RSS versus NM and Procedure RS+S9 due to Barton and Ivey, we summarize a simulation study based on four selected performance measures computed for six test problems that include additive white-noise error, with three levels of problem dimensionality and noise variability used in each problem. In the selected test problems, RSS yielded significantly more accurate estimates of the optimum than NM or RS+S9, and both RSS and RS+S9 required roughly four times as many function evaluations as NM.

  • a revised simplex Search Procedure for stochastic simulation response surface optimization
    Winter Simulation Conference, 1998
    Co-Authors: David G Humphrey, J R Wilson
    Abstract:

    We develop a variant of the Nelder-Mead (NM) simplex Search Procedure for stochastic simulation optimization that is designed to avoid many of the weaknesses encumbering such direct-Search methods-in particular, excessive sensitivity to starting values, premature termination at a local optimum, lack of robustness against noisy responses, and lack of computational efficiency. The revised simplex Search (RSS) Procedure consists of a three-phase application of the NM method in which: (a) the ending values for one phase become the starting values for the next phase; (b) the size of the initial simplex (respectively, the shrink coefficient) decreases geometrically (respectively, increases linearly) over successive phases; and (c) the final estimated optimum is the best of the ending values for the three phases. To compare RSS versus the NM Procedure and RS9 (a simplex Search Procedure recently proposed by Barton and Ivey (1996)), we summarize a simulation study based on separate factorial experiments and follow-up multiple comparisons tests for four selected performance measures computed on each of six test problems, with three levels of problem dimensionality and noise variability used in each problem. The experimental results provide substantial evidence of RSS's improved performance with only marginally higher computational effort.

Arthur J Swersey - One of the best experts on this subject based on the ideXlab platform.