• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.2
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• pp.105-116
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• 2018

In this study, we consider the assembly line balancing (ALB) problem which is known as an very important decision dealing with the optimal design of assembly lines. We consider ALB problems with soft constraints which are expected to be fulfilled, however they are not necessarily to be satisfied always and they are difficult to be presented in exact quantitative forms. In previous studies, most researches have dealt with hard constraints which should be satisfied at all time in ALB problems. In this study, we modify the mixed integer programming model of the problem introduced in the existing study where the problem was first considered. Based on the modified model, we propose a new algorithm using the genetic algorithm (GA). In the algorithm, new features like, a mixed initial population selection method composed of the random selection method and the elite solutions of the simple ALB problem, a fitness evaluation method based on achievement ratio are applied. In addition, we select the genetic operators and parameters which are appropriate for the soft assignment constraints through the preliminary tests. From the results of the computational experiments, it is shown that the proposed algorithm generated the solutions with the high achievement ratio of the soft constraints.

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.1
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• pp.55-65
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• 1992

There are takes performed on only one side (right side or left side) of the assembly line, and task groups in which the tasks are more related to one another like a subassembly. In the Assembly Line Balancing (ALB) of the large-sized product such as bus and truck, the side on which tasks are performed and the related task groups should be considered to improve work methods and to appropriately lay out parts and facilities in the line. In this paper, presented are the 0-1 programming formulations for the ALB with the constraints of assigning the same side tasks to the station. The objective of minimizing the number of stations is combined with the objective that the total number of the related task groups handled by all the stations is minimized. Also, proposed are the methods of reducing the number of variables and constraints, and of determining the station to which subassembly tasks are assigned.

• Journal of the Korea Safety Management & Science
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• v.7 no.3
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• pp.85-96
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• 2005

This paper is concerned with the integrated problem of line balancing and model sequencing in mixed model assembly lines(MMALBS), which is important to efficient utilization of the lines. In the problem, we deal with the objective of minimizing the overall line length To apply the GAs to MMALBS problems, we suggest a GA representation which suitable for its problems, an efficient decoding technique for the objective, and genetic operators which produce feasible offsprings. Extensive experiments are carried out to analyze the performance of the proposed algorithm. The computational results show that our algorithm is promising in solution quality.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.8 no.12
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• pp.7-12
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• 1985

Line balancing algorithm can be classified by two class, the analytical method and the heuristic method. In this thesis the study was focused on the determinstic line balancing model of the single model production assembly line balancing which is one of the heuristic method. The algorithm of Tonge, Kilbridge & Wester, Helgeson & Birnie which is using the analytical method was examined with one example. And then the algorithms were compared with using line balancing-efficiency, number of work station, standard deviation and range. The result showed that Helgeson & Birnie algorithm is the most convenient in use. A computer program was run in order to use Helgeson & algorithm more conveniently.

• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.2
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• pp.217-228
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• 1994

This paper presents a new integer formulation (Type III ALB) for a single model assembly line balancing problem. The objective of the formulation is to minimize the total idle time, which is defined as the product of the number of work stations and the cycle times minus the total work content. This formulation considers currently existing Type I (minimizing the number of work stations for a given cycle time) and type II (minimizing the cycle time for a given number of work stations) formulations as its special cases and provides the global minimum solutions of the cycle time and the number of work stations. This information would be of great value to line designers involved in designing new assembly lines and rebalancing old lines under flexible conditions. Solution methods based on combination of Type I and Type II approaches are also suggested and compared.

• Journal of the Korea Safety Management & Science
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• v.19 no.1
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• pp.203-210
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• 2017

Companies are pursuing the management of small quantity batch production or JIT(Just-in-time) system for improving the delivery response and LOB(Line Balancing) in order to satisfy consumers' increasing demands in the current global economic recession. And in order to improve the growth of production for reducing manufacturing cost, improvements of the Load Balancing have become an important reformation factor. Thus this paper is aimed at warehouse which procures materials on the assembly line in procurement logistics of automotive logistics and proceed with research on heuristic algorithm development which can increase the Load Balancing of workers. As a result of this study, when applied the primary target value, it was verified that the whole workers decreased from 28 to 24. Furthermore, when specified the secondary target value and applied algorithm once more, it was verified that the Load Balance Ratio was improved from 44.96% to 91.7%.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.737-740
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• 1996

This paper suggests a boltzman machine neural network model to determine model input sequences in line balancing process of mixed model assembly line. We first present a proper energy function, next determine the value of parameters using simulation process.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.1
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• pp.95-101
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• 2022

The two-sided assembly line balancing problem is a kind of NP-hard problem. This problem primarily can be solved metaheuristic method. This paper suggests parallel clustering algorithm that each left and right-sided workstation assigned by operations with T_i = c^* ± α < c, c^* = ${\lceil}$W/m^*${\rceil}$ such that M^* = ${\lceil}$W/c${\rceil}$ for precedence diagram of two-sided assembly line with total complete time W and cycle time c. This clustering performs forward direction from left to right or reverse direction from right to left. For the 4 experimental data with 17 cycle times, the proposed algorithm can be obtain the minimum number of workstations m^* and can be reduce the cycle time to T_max < c then metaheuristic methods. Also, proposed clustering algorithm maximizes the line efficiency and minimizes the variance between workers operation times.

• Journal of the Korea Society of Computer and Information
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• v.19 no.5
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• pp.89-98
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• 2014

This paper suggests heuristic algorithm for single-model simple assembly line balancing problem that is a kind of NP-hard problem. This problem primarily can be solved metaheuristic method. This heuristic algorithm set the main-path that has a most number of operations from start to end-product. Then the clustering algorithm can be assigns operations to each workstation within cycle time follow main-path. This algorithm decides minimum number of workstations and can be reduces the cycle time. This algorithm can be better performance then metaheuristic methods.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.3
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• pp.417-429
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• 1998

This paper considers two-sided (left and right side) assembly lines which are often used, especially in assembling large-sized products such as trucks and buses. A large number of exact algorithms and heuristics have been proposed to balance one-sided lines. However, little attention has been paid to balancing two-sided assembly lines. We present an efficient algorithm based on a branch and bound for balancing two-sided assembly lines. The algorithm involves a procedure for generating an enumeration tree. To efficiently search for the near optimal solutions to the problem, assignment rules are used in the method. New and existing bound strategies and dominance rules are else employed. The proposed algorithm can find a near optimal solution by enumerating feasible solutions partially. Extensive computational experiments are carried out to make the performance comparison between the proposed algorithm and existing ones. The computational results show that our algorithm is promising and robust in solution quality.