• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.8 no.4
• /
• pp.259-267
• /
• 2018

The subset-sum problem is to find out whether or not the element sum of a subset within a finite set of numbers is equal to a given value. The problem is a well-known NP-complete problem, which is difficult to solve within a polynomial time. Genetic algorithm is a method for finding the optimal solution of a given problem through operations such as selection, crossover, and mutation. Dynamic programming is a method of solving a given problem from one or several subproblems. In this paper, we design and implement a genetic algorithm that solves the subset-sum problem, and experimentally compared the time performance to find the answer with the case of dynamic programming method. We selected a total of 17 test cases considering the difficulty in a set with 63 elements of positive number, and compared the performance of the two algorithms. The presented genetic algorithms showed time performance improved by 84% on 13 of 17 problems when compared with dynamic programming.

• Journal of Institute of Control, Robotics and Systems
• /
• v.5 no.4
• /
• pp.403-410
• /
• 1999

In this study, a parallel algorithm has been developed that can quickly solve the optiaml control problem of large-scale dynamic systems. The algorithm adopts the sequential quadratic programming methods and achieves domain decomposition-type parallelism in computing sensitivities for search direction computation. A silicon wafer thermal process problem has been solved using the algorithm, and a parallel efficiency of 45% has been achieved with 16 processors. Practical methods have also been investigated in this study as a way to further speed up the computation time.

• 전기의세계
• /
• v.23 no.3
• /
• pp.53-59
• /
• 1974

The purpose of this paper is to use hydraulic sources optimally on the hydro-thermal power coordination in power system of Korea by means of Multiple Dynamic Programming. Four principal hydraulic power plans of Korea; Whachon, Chunchon, Uiam and Chong-pyong which are located on Han river side are treated in this research. For the illustrative purpose, a case study was made on the year round monthy optimal water control under the given load distribution and constraints.

• Journal of Navigation and Port Research
• /
• v.30 no.9
• /
• pp.773-777
• /
• 2006

Significant increase of container flows in the marine terminals requires more efficient port equipments such as logistic and transfer systems. This paper presents collision avoidance and routing approach based on dynamic programming (DP) algorithm for a linear motor based shuttle car which is considered as a new transfer system in the port terminals. Most of routing problems are focused on automatic guided vehicle (AGV) systems, but its solutions are hardly utilized for LM based shuttle cars since both are mechanically different. Our proposed DP is implemented for real-time searching of an optimal path for each shuttle car in the Agile port terminal located at California in USA.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.811-814
• /
• 1997

In this paper, the torque optimization of a kinematically redundant manipulator for minimizing the torque demands is discussed. The minimum torque solution based on a local optimization has been known to encounter the instability problem and then the global torque optimization was suggested as one of the alternatives. Herein, by adopting the infinity-norm rather than the 2-norm for the magnitude of torques, we are to propose a new cost function more advantageous to the avoidance of torque limits. By the way, a solution to the global torque optimization formulated with the new cost function can not be obtained by the previous methods due to their difficulties such as inability to treat discontinuous cost functions and various constraints on the joint variables. Thus, to overcome those deficiencies, we are developing a new approach using the dynamic programming. The effectiveness of the proposed method is shown through simulation examples for a 3-link planar redundant manipulator.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.41 no.3
• /
• pp.121-127
• /
• 2004

This paper presents a new vertex selection scheme for shape approximation. In the proposed method, final vertex points are determined by "two-step procedure". In the first step, initial vertices are simply selected on the contour, which constitute a subset of the original contour, using conventional methods such as an iterated refinement method (IRM) or a progressive vertex selection (PVS) method In the second step, a vertex adjustment Process is incorporated to generate final vertices which are no more confined to the contour and optimal in the view of the given distortion measure. For the optimality of the final vertices, the dynamic programming (DP)-based solution for the adjustment of vertices is proposed. There are two main contributions of this work First, we show that DP can be successfully applied to vertex adjustment. Second, by using DP, the global optimality in the vertex selection can be achieved without iterative processes. Experimental results are presented to show the superiority of our method over the traditional methods.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2003.09a
• /
• pp.264-267
• /
• 2003

Multiple sequence alignment is a useful tool to identify the relationships among protein sequences. Dynamic programming is the most widely used algorithm to obtain multiple sequence alignment with optimal cost. However dynamic programming cannot be applied to certain cost function due its drawback and to produce optimal multiple sequence alignment. We proposed sub-alignment refinement algorithm to overcome the problem of dynamic programming and impelmented this algorithm as a module of our MS Windows-based sequence alignment program.

• Journal of applied mathematics & informatics
• /
• v.26 no.1_2
• /
• pp.61-73
• /
• 2008

In this paper common fixed point theorems dealing with compatible mappings of type (P) are established. As a application, the existence and uniqueness of common solution for a system of functional equations arising in dynamic programming is given. The results presented in this paper improve, generalize and unify the corresponding results in this field.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.408-410
• /
• 2003

In this paper, an improved gradient direction assisted linking algorithm is proposed. This algorithm begins with initial seeds satisfying some local criteria. Then it will search along the direction provided by the initial point. A window will be generated in the gradient direction of the current point. Instead of the conventional method which only considers the value of the local salient structure, an improved mathematical model is proposed to describe the desired linear features. This model not only considers the value of the salient structure but also the direction of it. Furthermore, the linking problem under this model can be efficiently solved by dynamic programming method. This algorithm is tested for linear features detection in IKONOS images. The result demonstrates this algorithm is quite promising.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2006.05a
• /
• pp.354-359
• /
• 2006

The analysis of large-scale water resources systems is often complicated by the presence of multiple reservoirs and diversions, the uncertainty of unregulated inflows and demands, and conflicting objectives. Reinforcement learning is presented herein as a new approach to solving the challenging problem of stochastic optimization of multi-reservoir systems. The Q-Learning method, one of the reinforcement learning algorithms, is used for generating integrated monthly operation rules for the Keum River basin in Korea. The Q-Learning model is evaluated by comparing with implicit stochastic dynamic programming and sampling stochastic dynamic programming approaches. Evaluation of the stochastic basin-wide operational models considered several options relating to the choice of hydrologic state and discount factors as well as various stochastic dynamic programming models. The performance of Q-Learning model outperforms the other models in handling of uncertainty of inflows.