The Experts below are selected from a list of 4194 Experts worldwide ranked by ideXlab platform

Jatinder N D Gupta - One of the best experts on this subject based on the ideXlab platform.

  • Flowshop Scheduling with artificial neural networks
    Journal of the Operational Research Society, 2019
    Co-Authors: Jatinder N D Gupta, Arindam Majumder, Dipak Laha
    Abstract:

    AbstractFor effective modelling of Flowshop Scheduling problems, artificial neural networks (ANNs), due to their robustness, parallelism and predictive ability have been successfully used by resear...

  • a review of Flowshop Scheduling research with setup times
    Production and Operations Management, 2009
    Co-Authors: Jatinder N D Gupta, T Edwin C Cheng, Guoqing Wang
    Abstract:

    Flowshop Scheduling problems with setup times arise naturally in many practical situations. This paper provides a review of static and deterministic Flowshop Scheduling research involving machine setup times. The literature is classified into four broad categories, namely sequence independent job setup times, sequence dependent job setup times, sequence independent family setup times, and sequence dependent family setup times. Using the suggested classification scheme, this paper organizes the Flowshop Scheduling literature involving setup and/or removal times and summarizes the existing research for different Flowshop problem types. This review reveals that, while a considerable body of literature on this subject has been created, there still exist several potential areas worthy of further research.

  • Flowshop Scheduling research after five decades
    European Journal of Operational Research, 2006
    Co-Authors: Jatinder N D Gupta, Edward F Stafford
    Abstract:

    Abstract Since Johnson’s seminal paper in 1954, Flowshop Scheduling problems have received considerable research attention over the last fifty years. As a result, several optimization and heuristic solution procedures are available to solve a variety of Flowshop Scheduling problems. This paper provides a brief glimpse into the evolution of Flowshop Scheduling problems and possible approaches for their solution over the last fifty years. It briefly introduces the current Flowshop problems being solved and the approaches being taken to solve (optimally or approximately) them. The paper concludes with some fruitful directions for future research.

  • An improved lexicographic search algorithm for the Flowshop Scheduling problem
    Computers & Operations Research, 2003
    Co-Authors: Jatinder N D Gupta
    Abstract:

    Abstract This paper describes an improved lexicographic search algorithm for the solution of the n -job, M -machine Flowshop Scheduling problem. The proposed improved algorithm is capable of generating all optimal schedules for any monotonically non-decreasing optimality criterion and is computationally more efficient than the basic lexicographic search algorithm. A numerical example is solved to illustrate the decrease in the computational effort by the proposed algorithm.

  • Flowshop Scheduling with set-up, processing and removal times separated
    International Journal of Production Research, 1991
    Co-Authors: C. Proust, Jatinder N D Gupta, V. Deschamps
    Abstract:

    Algorithms are developed for finding an optimal or near-optimal permutation schedule for the static Flowshop Scheduling problem where set-up, processing, and removal times are separable. Computational experience with the proposed heuristic algorithms indicates that they are quite effective in minimizing the makespan for a given problem.

Xin She Yang - One of the best experts on this subject based on the ideXlab platform.

  • A Discrete Firefly Algorithm for the Multi-Objective Hybrid Flowshop Scheduling Problems
    IEEE Transactions on Evolutionary Computation, 2014
    Co-Authors: Mariappan Kadarkarainadar Marichelvam, Thirumoorthy Prabaharan, Xin She Yang
    Abstract:

    Hybrid Flowshop Scheduling problems include the generalization of Flowshops with parallel machines in some stages. Hybrid Flowshop Scheduling problems are known to be NP-hard. Hence, researchers have proposed many heuristics and metaheuristic algorithms to tackle such challenging tasks. In this letter, a recently developed discrete firefly algorithm is extended to solve hybrid Flowshop Scheduling problems with two objectives. Makespan and mean flow time are the objective functions considered. Computational experiments are carried out to evaluate the performance of the proposed algorithm. The results show that the proposed algorithm outperforms many other metaheuristics in the literature.

Mariappan Kadarkarainadar Marichelvam - One of the best experts on this subject based on the ideXlab platform.

  • A Discrete Firefly Algorithm for the Multi-Objective Hybrid Flowshop Scheduling Problems
    IEEE Transactions on Evolutionary Computation, 2014
    Co-Authors: Mariappan Kadarkarainadar Marichelvam, Thirumoorthy Prabaharan, Xin She Yang
    Abstract:

    Hybrid Flowshop Scheduling problems include the generalization of Flowshops with parallel machines in some stages. Hybrid Flowshop Scheduling problems are known to be NP-hard. Hence, researchers have proposed many heuristics and metaheuristic algorithms to tackle such challenging tasks. In this letter, a recently developed discrete firefly algorithm is extended to solve hybrid Flowshop Scheduling problems with two objectives. Makespan and mean flow time are the objective functions considered. Computational experiments are carried out to evaluate the performance of the proposed algorithm. The results show that the proposed algorithm outperforms many other metaheuristics in the literature.

Vinicius Amaral Armentano - One of the best experts on this subject based on the ideXlab platform.

  • genetic local search for multi objective Flowshop Scheduling problems
    European Journal of Operational Research, 2005
    Co-Authors: Jose Elias Claudio Arroyo, Vinicius Amaral Armentano
    Abstract:

    This paper addresses Flowshop Scheduling problems with multiple performance criteria in such a way as to provide the decision maker with approximate Pareto optimal solutions. Genetic algorithms have attracted the attention of researchers in the nineties as a promising technique for solving multi-objective combinatorial optimization problems. We propose a genetic local search algorithm with features such as preservation of dispersion in the population, elitism, and use of a parallel multi-objective local search so as intensify the search in distinct regions. The concept of Pareto dominance is used to assign fitness to the solutions and in the local search procedure. The algorithm is applied to the Flowshop Scheduling problem for the following two pairs of objectives: (i) makespan and maximum tardiness; (ii) makespan and total tardiness. For instances involving two machines, the algorithm is compared with Branch-and-Bound algorithms proposed in the literature. For such instances and larger ones, involving up to 80 jobs and 20 machines, the performance of the algorithm is compared with two multi-objective genetic local search algorithms proposed in the literature. Computational results show that the proposed algorithm yields a reasonable approximation of the Pareto optimal set.

Guoqing Wang - One of the best experts on this subject based on the ideXlab platform.

  • a review of Flowshop Scheduling research with setup times
    Production and Operations Management, 2009
    Co-Authors: Jatinder N D Gupta, T Edwin C Cheng, Guoqing Wang
    Abstract:

    Flowshop Scheduling problems with setup times arise naturally in many practical situations. This paper provides a review of static and deterministic Flowshop Scheduling research involving machine setup times. The literature is classified into four broad categories, namely sequence independent job setup times, sequence dependent job setup times, sequence independent family setup times, and sequence dependent family setup times. Using the suggested classification scheme, this paper organizes the Flowshop Scheduling literature involving setup and/or removal times and summarizes the existing research for different Flowshop problem types. This review reveals that, while a considerable body of literature on this subject has been created, there still exist several potential areas worthy of further research.