• Journal of Korean Association for Spatial Structures
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• v.3 no.1 s.7
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• pp.35-46
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• 2003

Conventional analysis and design of steel structures are performed using the assumption of a either fully rigid or pinned. However, every steel connection lies in between fully rigid and pinned connection. So, It is important to consider the connection for steel structure design. In this paper Computer-based second-order elastic analysis is used to calculate one story two bay and two story three bay for steel structures with semi-rigid connection. Genetic Algorithms(GAs) and Sequential Unconstrained Minized Technique(SUMT) dynamic programming is used to the method for optimum design of steel structures. The efficiency and validity of the developed continuous and discrete optimum design algorithm was verified by applying the algorithm to optimum design examples.

• Journal of Korean Institute of Industrial Engineers
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• v.29 no.4
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• pp.304-311
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• 2003

This paper considers a new variation of scheduling problems where jobs are dispatched in batches. The variation is the case where the batch sequence is fixed. The objective is to minimize the sum of the completion times of the batches. This simple environment has a variety of real world applications such as part kitting and customer order scheduling. We show that this problem is binary NP-complete when there exist two machines. For the same problem, we develop an optimal dynamic programming (DP) algorithm which runs in pseudo-polynomial time. We finally prove the optimality of the DP algorithm.

• Journal of Korean Port Research
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• v.14 no.1
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• pp.37-45
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• 2000

Centralized safety stock in a periodic replenishment system which consists of one central warehouse and m regional warehouse can reduce backorders allocating the centralized safety stocks to regional warehouse in a certain instant of each replenishment cycle. If the central warehouse can not monitoring inventories in the regional warehouse, then we have to predetermine the instant of allocation according to demand distribution and this instant must be same for all different replenishment cycle. However, transition of inventory level in each cycle need not to be same, and therefore different instant of the allocation may results reduced shortage compare to the predetermined instant of allocation. In this research, we construct a dynamic model based on the assumption of monitoring inventories in the regional warehouse everyday, and develop an algorithm minimize shortage in each replenishment cycle using dynamic programming approach.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1999.10a
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• pp.83-90
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• 1999

Centralized safety stock in a periodic replenishment system which consists of one central warehouse and m regional warehouse can reduce backorders allocation the centralized safety stocks to regional warehouse in a certain instant of each replenishment cycle. If the central warehouse can not monitoring inventories in the regional warehouse, then we have to predetermine the instant of allocation according to demand distribution and this instant must be same for all different replenishment cycle. However, transition of inventory level in each cycle need not to be same, and therefore different instant of the allocation may results reduced shortage compare to the predetermined instant of allocation. In this research, we construct a dynamic model based on the assumption of monitoring inventories inventories in the regional warehouse everyday, and develop an algorithm minimize shortage in each replenishment cycle using dynamic programming approach.

• Journal of Korea Multimedia Society
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• v.11 no.6
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• pp.807-815
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• 2008

A simple efficient method of spotting and recognizing hand gestures in video is presented using a network of hidden Markov models and dynamic programming search algorithm. The description starts from designing a set of isolated trajectory models which are stochastic and robust enough to characterize highly variable patterns like human motion, handwriting, and speech. Those models are interconnected to form a single big network termed a spotting network or a spotter that models a continuous stream of gestures and non-gestures as well. The inference over the model is based on dynamic programming. The proposed model is highly efficient and can readily be extended to a variety of recurrent pattern recognition tasks. The test result without any engineering has shown the potential for practical application. At the end of the paper we add some related experimental result that has been obtained using a different model - dynamic Bayesian network - which is also a type of stochastic model.

• Journal of Digital Contents Society
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• v.17 no.4
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• pp.257-263
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• 2016

Cable drum schedule is the final step for the electrical equipment of the power plant, and is assigned cables to efficiently cable drum. In this paper, we have implemented an automated program which cables are scheduled in accordance with the capacity of the cable drum for each cable code. Proposed cable drum schedule was applied to the dynamic programming algorithm to effectively solve the optimization problem, and the implemented program is conducted so as to verify the proposed model. The experiment results show that implemented program eliminates the errors that can occur existing method, so we were able to reduce the design time of cable drum schedule. Cables for the electrical equipment of the power plant is designed to at least 2 million units or more. Thus the automation program to provide applies, it is considered that the design time of the cable drum schedule can be greatly reduced without serious error.

• Journal of the Korean Society of Hazard Mitigation
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• v.6 no.2 s.21
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• pp.51-60
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• 2006

The objective of this research is to develop a least cost system design method for branched storm sewer systems while satisfying all the design constraints using heuristic techniques such as genetic algorithm and harmony search. Two sewer system models have been developed in this study. The SEWERGA and SEWERHS both determine the optimal discrete pipe installation depths as decision variables. Two models also determine the optimal diameter of sewer pipes using the discrete installation depths of the pipes while satisfying the discharge and velocity requirement constraints at each pipe. Two models are applied to the example that was originally solved by Mays and Yen (1975) using their dynamic programming(DP). The optimal costs obtained from SEWERGA and SEWERHS are about 4% lower than that of the DP approach.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.33
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• pp.111-118
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• 1995

This paper suggests a hybrid genetic algorithm for asymmetric traveling salesman problem(TSP). The TSP was proved to be NP-complete, so it is difficult to find optimal solution in reasonable time. Therefore it is important to develope an algorithm satisfying robustness. The algorithm applies dynamic programming to find initial solution. The genetic operator is uniform order crossover and scramble sublist mutation. And experiment of parameterization has been performed.

• Journal of Korean Society of Transportation
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• v.26 no.1
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• pp.127-135
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• 2008

Generally, optimum shortest path algorithms adopt single attribute objective among several attributes such as travel time, travel cost, travel fare and travel distance. On the other hand, multi-objective shortest path algorithms find the shortest paths in consideration with multi-objectives. Up to recently, the most of all researches about multi-objective shortest paths are proceeded only in single transportation mode networks. Although, there are some papers about multi-objective shortest paths with multi-modal transportation networks, they did not consider transfer problems in the optimal solution level. In particular, dynamic programming method was not dealt in multi-objective shortest path problems in multi-modal transportation networks. In this study, we propose a multi-objective shortest path algorithm including dynamic programming in order to find optimal solution in multi-modal transportation networks. That algorithm is based on two-objective node-based label correcting algorithm proposed by Skriver and Andersen in 2000 and transfer can be reflected without network expansion in this paper. In addition, we use non-dominated paths and tree sets as labels in order to improve effectiveness of searching non-dominated paths. We also classifies path finding attributes into transfer and link travel attribute in limited transit networks. Lastly, the calculation process of proposed algorithm is checked by computer programming in a small-scaled multi-modal transportation network.

• Journal of the military operations research society of Korea
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• v.18 no.2
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• pp.66-95
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• 1992

Shortest paths are one of the simplest and most widely used concepts in deterministic networks. A decison of troops movement route can be analyzed in the network with a shortest path algorithm. But in reality, the value of arcs can not be determined in the network by crisp numbers due to imprecision or fuzziness in parameters. To account for this reason, a fuzzy network should be considered. A fuzzy shortest path can be modeled by general fuzzy mathematical programming and solved by fuzzy dynamic programming. It can be formulated by the fuzzy network with lingustic variables and solved by the Klein algorithm. This paper focuses on a revised fuzzy shortest path algorithm and an application is discussed.