• International Journal of Computer Science & Network Security
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• v.24 no.9
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• pp.105-110
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• 2024

Nowadays, permutation problems with large state spaces and the path to solution is irrelevant such as N-Queens problem has the same general property for many important applications such as integrated-circuit design, factory-floor layout, job-shop scheduling, automatic programming, telecommunications network optimization, vehicle routing, and portfolio management. Therefore, methods which are able to find a solution are very important. Genetic algorithm (GA) is one the most well-known methods for solving N-Queens problem and applicable to a wide range of permutation problems. In the absence of specialized solution for a particular problem, genetic algorithm would be efficient. But holism and random choices cause problem for genetic algorithm in searching large state spaces. So, the efficiency of this algorithm would be demoted when the size of state space of the problem grows exponentially. In this paper, the new method presented based on genetic algorithm to cover this weakness. This new method is trying to provide partial view for genetic algorithm by locally searching the state space. This may cause genetic algorithm to take shorter steps toward the solution. To find the first solution and other solutions in N-Queens problem using proposed method: dividing N-Queens problem into subproblems, which configuring initial population of genetic algorithm. The proposed method is evaluated and compares it with two similar methods that indicate the amount of performance improvement.

• Journal of the Korea Society for Simulation
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• v.29 no.1
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• pp.57-69
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• 2020

Many researchers have recommended that DBR scheduling would be an efficient method to maintain the balance of their workload among many processes in the general flow shop. However, as product variety has increased in recent years, the process has become more complex and requires the re-entrance of raw materials and work in process. The re-entrant line has known for the complex manufacturing process that raw materials are repeatedly processed on the same machine. This study reviews the applicability of DBR against the re-entrant manufacturing line due to the distinguishing characteristics and the higher complexity caused by multiple visits of a job into the identical process. In order to apply the DBR method to the re-entrant process, the main idea is to reconstruct re-entrant process into a virtual flow process(loop) that has a single bottleneck. This study discusses the following two questions. First, DBR is also superior to traditional scheduling methods against re-entrant manufacturing line. And how we structure and detect the system bottleneck (or sub-bottleneck) through drum-buffer-rope concepts. To answer the above questions, we experimented and analyzed the effects of the applicability of DBR under the general re-entrant process model(TRC, Technology Research Center). As a result, we have identified a balance between loops for cycle time and work in process.