Yazar "Kellegoz, Talip" seçeneğine göre listele

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    Elite guided steady-state genetic algorithm for minimizing total tardiness in flowshops
    (Pergamon-Elsevier Science Ltd, 2010) Kellegoz, Talip; Toklu, Bilal; Wilson, John
    In this research, a detailed study of the permutation flowshop scheduling problem with the objective of minimizing total tardiness is presented and a steady-state genetic algorithm solution procedure is developed for such problems. Also, using problem-specific knowledge, a very efficient elite guided solution improvement scheme and an appropriate crossover operator have been developed and integrated into the proposed method. Using benchmark problems, the algorithm has been compared with heuristic algorithms having the best performance in the literature. The performance of the developed algorithm is shown to be superior using a simulation study. (C) 2009 Elsevier Ltd. All rights reserved.
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    A genetic algorithm for the stochastic mixed-model U-line balancing and sequencing problem
    (Taylor & Francis Ltd, 2011) Ozcan, Ugur; Kellegoz, Talip; Toklu, Bilal
    Mixed-model assembly lines are widely used to improve the flexibility to adapt to the changes in market demand, and U-lines have become popular in recent years as an important component of just-in-time production systems. As a consequence of adaptation of just-in-time production principles into the manufacturing environment, mixed-model production is performed on U-lines. This type of a production line is called a mixed-model U-line. In mixed-model U-lines, there are two interrelated problems called line balancing and model sequencing. In real life applications, especially in manual assembly lines, the tasks may have varying execution times defined as a probability distribution. In this paper, the mixed-model U-line balancing and sequencing problem with stochastic task times is considered. For this purpose, a genetic algorithm is developed to solve the problem. To assess the effectiveness of the proposed algorithm, a computational study is conducted for both deterministic and stochastic versions of the problem.