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- MakaleYalnız künye2019Scopus SJRQ2An efficient algorithm for U-type assembly line re-balancing problem with stochastic task times
Serin, Faruk; Mete, Süleyman; Çelik, Erkan
Purpose: Changing the product characteristics and demand quantity resulting from the variability of the modern market leads to re-assigned tasks and changing the cycle time on the production line. Therefore, companies need re-balancing of their assembly line instead of balancing. The purpose of this paper is to propose an efficient algorithm approach for U-type assembly line re-balancing problem using stochastic task times. Design/methodology/approach: In this paper, a genetic algorithm is proposed to solve approach for U-type assembly line re-balancing problem using stochastic task times. Findings: The performance of the genetic algorithm is tested on a wide variety of data sets from literature. The task times are assumed normal distribution. The objective is to minimize total re-balancing cost, which consists of workstation cost, operating cost and task transposition cost. The test results show that proposed genetic algorithm approach for U-type assembly line re-balancing problem performs well in terms of minimizing total re-balancing cost. Practical implications: Demand variation is considered for stochastic U-type re balancing problem. Demand change also affects cycle time of the line. Hence, the stochastic U-type re-balancing problem under four different cycle times are analyzed to present practical case. Originality/value: As per the authors’ knowledge, it is the first time that genetic algorithm is applied to stochastic U-type re balancing problem. The large size data set is generated to analyze performance of genetic algorithm. The results of proposed algorithm are compared with ant colony optimization algorithm.
AtıfScopus19WoS17OpenAlex20
İncele - BildiriYalnız künye2017An efficient heuristic algorithm for solving robotic assembly line balancing problem
Çil, Zeynel Abidin; Mete, Süleyman; Özceylan, Eren
In the assembly system, robots provide to increase flexibility of the system and automation. The balancing robotic assembly line (RALB) problem consists two main works, which are not only assigning task to station, but also allocation robots in stations. Because each robots can perform different performance on the same tasks due to their capabilities. In this study, iterative beam search algorithm is developed to minimize cycle time. The performance of the algorithm outperforms other algorithm in the literature.
AtıfScopus2OpenAlex1İncele - BildiriYalnız künye2017A heuristic algorithm for assembly line balancing with stochastic sequence-dependent setup times
Çil, Zeynel Abidin; Mete, Süleyman; Özceylan, Eren; Diri Kenger, Zülal; Çil, Hande
Having analyzed studies on the assembly line balancing problem considering setup times, a few papers are observed. However, researches show that setup time plays an important role in total production time. Besides, in these studies, the setup times are assumed to be deterministic. Considering setup times to be deterministic decreases proximity of problem to real life application. Because the operation and setup times may vary in real applications due to human factors, machine breakdowns, lack of equipment and environmental factors. Therefore, in this study, assembly line balancing problem is investigated considering the sequence-dependent stochastic setup times. A heuristic approach based on COMSOAL is presented for the problem and it is seen that algorithm is effective for the problem.
AtıfScopus2İncele