A hybrid heuristic algorithm for flowshop inverse scheduling problem under a dynamic environment

Mou, Jianhui; Gao, Liang; Guo, Qianjian; Mu, Jiancai

doi:10.1007/s10586-017-0734-6

Cited by 11 publications

(4 citation statements)

References 22 publications

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“…Ag = MTTR (MTTR+MTBF) denotes the breakdown level of parallel machine, which is the percentage of time the machine has failures. The simulation of machine breakdown follows the steps detailed in [58].…”

Section: Machine Breakdownmentioning

confidence: 99%

Transitive Reduction Approach to Large-Scale Parallel Machine Rescheduling Problem With Controllable Processing Times, Precedence Constraints and Random Machine Breakdown

et al. 2023

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This paper studied a novel parallel machine rescheduling problem with controllable processing times under machine breakdown and precedence constraints. This problem is strongly N P-hard, and we modeled it as a mixed-integer problem (MIP). The primal problem is decomposed into the discrete subproblem and the continuous one. We treat the discrete with the dispatching rule and analyze the continuous in the terms of mathematical programming. Pros and cons from the analysis lead us to implement the commercial solver. The proposed method is capable of efficiency and nonzero initial state. We introduce transitive reduction to cull the redundant constraints out of its directed acyclic graph (DAG) representation. Transitive reduction extends the efficiency from the dispatching rule to the solver. The proposed method can do the predictive scheduling and pick up the partial solution left by the machine breakdown in the reactive session. As a result, the complete method solves the rescheduling problem with efficiency, and allows for large cases. At last, the computational results showed that this technique significantly brought down the time and RAM consumption in using the solver. This technique allows the scheduler to solve big instances with computational economy and efficiency.INDEX TERMS Controllable processing times, large-scale, precedence constraints, random machine breakdown, transitive reduction.

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Section: Machine Breakdownmentioning

confidence: 99%

Transitive Reduction Approach to Large-Scale Parallel Machine Rescheduling Problem With Controllable Processing Times, Precedence Constraints and Random Machine Breakdown

et al. 2023

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“…Lee and Chung [26] consider a permutation flowshop scheduling problem with learning effects where the objective is to minimize the total tardiness. Other recent studies are the work of Kia et al [27] and Mou et al [28].…”

Section: Review Of Related Workmentioning

confidence: 99%

Improving Performance of GAs by Use of Selective Breading Evolutionary Process

Ghassemi-Tari

Meshkinfam

2017

BJMCS

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In this paper, the use of selective breading evolutionary process for improving the performance of GAs is evaluated. To accomplish this evaluation, the generalized tardiness flow shop scheduling (GTFS) problem is designated. A natural evolutionary GA and two selective breeding Gas are developed for evaluating their performances in solving the proposed problem. An extensive numerical experiment on total of 2250 randomly generated scenarios is conducted to compare the effects of selective breeding mechanism. The effects of the varieties factors on the solution of the algorithms are analyzed by the factorial ANOVA. The computational results reveal that a significant improvement can be obtained if one employs an initial population with better genes.

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“…The trend of exploiting the potential of bio/nature-inspired soft computing techniques is growing in the research community due to their extensive use in optimization problems arising in engineering, science and technology [1][2][3][4][5]. For instance, heat transfer model [6], magnetohydrodynamics [7], nonlinear system identification [8], atomic physics [9], nonlinear optics [10], plasma physics [11], and scheduling problem [12,13]. Recently, a new meta-heuristic name as flower pollination algorithm (FPA) is introduced by Yang [14] for efficiently solving nonlinear, constrained, single/multi-objective optimization problems [15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Flower Pollination Heuristics for Nonlinear Active Noise Control Systems

Khan¹,

He²,

Raja³

et al. 2021

Computers, Materials &Amp; Continua

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In this paper, a novel design of the flower pollination algorithm is presented for model identification problems in nonlinear active noise control systems. The recently introduced flower pollination based heuristics is implemented to minimize the mean squared error based merit/cost function representing the scenarios of active noise control system with linear/nonlinear and primary/secondary paths based on the sinusoidal signal, random and complex random signals as noise interferences. The flower pollination heuristics based active noise controllers are formulated through exploitation of nonlinear filtering with Volterra series. The comparative study on statistical observations in terms of accuracy, convergence and complexity measures demonstrates that the proposed meta-heuristic of flower pollination algorithm is reliable, accurate, stable as well as robust for active noise control system. The accuracy of the proposed nature inspired computing of flower pollination is in good agreement with the state of the art counterpart solvers based on variants of genetic algorithms, particle swarm optimization, backtracking search optimization algorithm, fireworks optimization algorithm along with their memetic combination with local search methodologies. Moreover, the central tendency and variation based statistical indices further validate the consistency and reliability of the proposed scheme mimic the mathematical model for the process of flower pollination systems.

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A hybrid heuristic algorithm for flowshop inverse scheduling problem under a dynamic environment

Cited by 11 publications

References 22 publications

Transitive Reduction Approach to Large-Scale Parallel Machine Rescheduling Problem With Controllable Processing Times, Precedence Constraints and Random Machine Breakdown

Transitive Reduction Approach to Large-Scale Parallel Machine Rescheduling Problem With Controllable Processing Times, Precedence Constraints and Random Machine Breakdown

Improving Performance of GAs by Use of Selective Breading Evolutionary Process

Flower Pollination Heuristics for Nonlinear Active Noise Control Systems

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