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.

According to a simple survey on the current status of the assembly line design, it was found that trial and error methods on the basis of experiences have been used mainly in domestic manufacturing industries, even though there exist a lot of excellent line balancing studies. It seems that more practical researches should be carried out to develop user-oriented line balancing tools especially for small and medium-sized enterprises. This study presents a design of the line balancing tool which can support the line balancing tasks of nonspecialists. The proposed design tool is composed of three major modules: pre-process, line balancing, and post-process. In particular, pre-process and post-process are newly proposed to increase its ease of use. We applied the proposed design to a test problem and test result showed that our practical method may contribute to enhance the efficiency of production operations management.

In this thesis, we surveyed the current status of production operations management to find how to improve the operations efficiency. From the survey research, we have found that practical software tools should be developed to increase the efficiency of production operations management, especially for small and mediumsized enterprises. Although there exist a lot of excellent line balancing researches, the results of our survey represent that trial and error methods on the basis of experiences have been used mainly used in the domestic manufacturing industry. It seems that more practical researches should be carried out to develop user-oriented line balancing tools. As a part of the development of those tools, this thesis proposed a design of the line balancing tool which can support the line balancing tasks of nonspecialists. The proposed design is composed of three major phases: redundancy check of the precedence diagram, line balancing, and modification of the line balancing results. The first phase is to check the precedence diagram of work elements and remove the redundancy. The redundancy may affect the quality of solutions and computational time. Although it is important to prepare a neat and proper precedence data, it is not easy to develop a tidy precedence diagram for laymen. The first phase automatically removes the overlapped data. The next phase is the line balancing algorithm. The proposed algorithm is based on COMSOAL and can solve minimization of the number of work stations given the target production cycle time and minimization of the production cycle time given the number of work stations. Additionally, our suggested method can accommodate the predetermined location constraints. The third phase is to modify the solution suggested by the second phase. Frequently, users may want to change the result to reflect some constraints which were not easy to be included into the line balancing algorithm. So, a practical line balancing tool should provide mechanisms to modify the solution and they should check the precedence violation while a user tries to change the work station of an element. This research suggested a simple mechanism to check the precedence violation. We applied the proposed design to some test problems and test results showed that it performed successfully. Therefore, our method may contribute to enhance the efficiency of production operations management.

  In this paper, we consider a line balancing problem in hybrid flowshops where each workstation has identical parallel machines. The number of machines in each workstation is determined in ways of satisfying pre-specified throughput rate of the system. T

The assembly line balancing problem has been focused by many research works because the efficient management of the assembly line might influence not only the quality of the products but also the working conditions for the workers. This paper deals with U

In this thesis presents line balancing problems of two-sided and mixed model assembly line widely used in practical fields using genetic algorithm for reducing throughput time, cost of tools and fixtures and improving flexibility of assembly lines. Two-sided and mixed model assembly line is a special type of production line where variety of product similar in product characteristics are assembled in both sides. This thesis proposes the genetic algorithm adequate to each step in tow-sided and mixed model assembly line with suitable presentation, individual, evaluation function, selection and genetic parameter. To confirm proposed genetic algorithm, we apply to increase the number of tasks in case study. And for evaluation the performance of proposed genetic algorithm, we compare to existing algorithm of one-sided and mixed model assembly line. The results show that the algorithm is outstanding in the problems with a larger number of stations or larger number of tasks.

In this thesis presents line balancing problems of two-sided and mixed model assembly line widely used in practical fields using genetic algorithm for reducing throughput time, cost of tools and fixtures and improving flexibility of assembly lines. Two-sided and mixed model assembly line is a special type of production line where variety of product similar in product characteristics are assembled in both sides. This thesis proposes the genetic algorithm adequate to each step in tow-sided and mixed model assembly line with suitable presentation, individual, evaluation function, selection and genetic parameter. To confirm proposed genetic algorithm, we apply to increase the number of tasks in case study. And for evaluation the performance of proposed genetic algorithm, we compare to existing algorithm of one-sided and mixed model assembly line. The results show that the algorithm is outstanding in the problems with a larger number of stations or larger number of tasks.

Multiple U-typed production lines are increasingly accepted in modern manufacturing system for the flexibility to adjust to changes in demand. This paper considers multiple U line balancing with the objective of minimizing cycle time considering of moving time of workforce given the number of workstation. Like the traditional line balancing problem this problem is NP-hard. In this paper, we show how genetic algorithm can be used to solve multiple U line balancing. For this, an encoding and a decoding method suitable to the problem are presented. Proper genetic operators are also employed. Extensive computational experiments are carried out to show the performance of the proposed algorithm. The computational results show that the algorithm is promising in solution quality.