A genetic algorithm for flowshop sequencing

By C. Reeves. 1995

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Citations in the corpus

Genetic CNN (2017, positive): “It is commonly used to generate high-quality solutions to optimization and search problems [14][30][2][4] by performing bio-inspired operators such as mutation, crossover and selection.”
No-wait flowshop with separate setup times to minimize maximum lateness (2007, background): “Some examples are Reeves [19] or more recently Ruiz et al.”
COVID-19 Outbreak Prediction with Machine Learning (2020, background): “The degree of "goodness" of an answer is usually measured by the population of the current candidate's answers [55] [56] [57] [58] [59] .”
A genetic algorithm for task scheduling on heterogeneous computing systems using multiple priority queues (2014, background): “[50,51] report that a high-quality solution obtained from another heuristic technique can help a GA find better solutions more quickly than it can from a random start.”
A performance evaluation of permutation vs. non-permutation schedules in a flowshop (2006, methodology): “From the metaheuristics tested, Stützle’s (1998) Iterated Local Search (ILS) and the genetic algorithm (GA) of Reeves (1995) are better than the other algorithms evaluated.”
Flowshop-scheduling problems with makespan criterion: a review (2005, methodology): “Several TS-based approaches have been proposed by different researchers for a flowshop problem, including Taillard (1990), Reeves (1993), Mocellin (1995),”
A particle swarm optimization algorithm for makespan and total flowtime minimization in the permutation flowshop sequencing problem (2007, methodology): “To achieve a better solution quality, modern metaheuristics have been presented for the PFSP with makespan minimization such as simulated annealing in [30,28], tabu search in [38,27,54,14], genetic algorithms in [39,40], ant colony optimization in [45,37], and iterated local search in [44].”
TWO NEW ROBUST GENETIC ALGORITHMS FOR THE FLOWSHOP SCHEDULING PROBLEM (2006, methodology): “The initialization proposed by Reeves [38] (using a NEH generated member) results in a much more effective algorithm.”
The distributed permutation flowshop scheduling problem (2010, methodology): “Algorithms are presented in Reeves (1995) and in Ruiz, Maroto and Alcaraz (2006).”
An Effective PSO-Based Memetic Algorithm for Flow Shop Scheduling (2007, background): “The other 21 problems are called rec01, rec03 through rec41 by Reeves [ 11 ], who used them to compare the performances of some metaheuristics and found these problems to be particularly difficult.”
Stochastic Optimization: a Review (2002, methodology): “ Reeves (1995a) proposed an exchange mutation, in which two randomly chosen elements are interchanged (a two-bit swap).”
A simple and effective iterated greedy algorithm for the permutation flowshop scheduling problem (2007, methodology): “Keywords: Iterated Greedy, Flowshop Scheduling, Metaheuristics.”