• IE interfaces
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• v.24 no.2
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• pp.112-118
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• 2011

This paper introduces one type of prize collecting travelling salesman problem with time windows (PCTSPTW), proposes a mixed integer programming model for the problem, and shows that the problem can be reduced to the elementary shortest path problem with time windows and capacity constraints (ESPPTC). Then, a new dynamic programming algorithm is proposed to solve ESPPTC quickly. Computational results show the effectiveness of the proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.6
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• pp.514-523
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• 2002

Feeder arrangement is an important element of process planning for printed circuit board assembly systems. This paper newly proposes a feeder arrangement method for multihead-gantry chip mounters. The multihead-gantry chip mounters are very popular in printed circuit board assembly system, but the research has been mainly focused on single-head-gantry chip mounters. We present an integer programming formulation for optimization problem of multihead-gantry chip mounters, and propose a heuristic method to solve the large NP-complete problem in reasonable time. Dynamic programming method is then applied to feeder arrangement optimization to reduce the overall assembly time. Comparative simulation results are finally presented to verify the usefulness of the proposed method.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.6
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• pp.11-20
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• 1997

This paper proposes a modified dynamic programming for finding the correspondence between right and left images. A dynamic programming is based on the intensity of images for stereo matching. But htis method is intended to mismatch at uniformed intensity region. To reduce thd mismatching, the stereo images are segmented to various regions with respective uniform intensity, and the different cost function has applied to the segmented region during the dynamci programming. Cost function costains jump cost. And jump cost included two parameter .alpha. and .beta. which have influence on minimum cost path. Experimental results show that the 3D shape of some stereo pairs cna be finely obtained by this proposed algorithm.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.4
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• pp.414-424
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• 2008

Disassembly scheduling is the problem of determining the quantity and timing of disassembling used or end-of-life products while satisfying the demand of their parts or components over a given planning horizon. This paper considers the two-level disassembly structure that describes a direct relationship between the used product and its parts or components. To formulate the problem mathematically, we first suggest an integer programming model, and then reformulate it to a dynamic programming model after characterizing properties of optimal solutions. Based on the dynamic programming model, we develop a polynomial exact algorithm and illustrate it with an example problem.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.415-422
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• 2014

This paper presents a new approach to solve the multi area unit commitment problem (MAUCP) using an evolutionary programming based particle swarm optimization (EPPSO) method. The objective of this paper is to determine the optimal or near optimal commitment schedule for generating units located in multiple areas that are interconnected via tie lines. The evolutionary programming based particle swarm optimization method is used to solve multi area unit commitment problem, allocated generation for each area and find the operating cost of generation for each hour. Joint operation of generation resources can result in significant operational cost savings. Power transfer between the areas through the tie lines depends upon the operating cost of generation at each hour and tie line transfer limits. Case study of four areas with different load pattern each containing 7 units (NTPS) and 26 units connected via tie lines have been taken for analysis. Numerical results showed comparing the operating cost using evolutionary programming-based particle swarm optimization method with conventional dynamic programming (DP), evolutionary programming (EP), and particle swarm optimization (PSO) method. Experimental results show that the application of this evolutionary programming based particle swarm optimization method has the potential to solve multi area unit commitment problem with lesser computation time.

• Journal of Internet Computing and Services
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• v.8 no.5
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• pp.35-43
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• 2007

Semantics-based notations need to be used for specification of static and dynamic semantics to specify and implement new programming language. If the semantics is practically defined, we easily gain a translator according to the implementation of the semantics. In this paper, we describe the static and dynamic semantics to get a translator easily. We present practical semantics-based Action Equations, an extension and transformation of Attribute Grammar(AGs) suitable for specifying the static and dynamic semantics of a object oriented programming language. Compare with the existing descriptions, Action Equations is superior, modernized, and accurate.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.9
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• pp.540-546
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• 2003

A fast pattern classification algorithm with Cellular Nonlinear Network-based dynamic programming is proposed. The Cellular Nonlinear Networks is an analog parallel processing architecture and the dynamic programing is an efficient computation algorithm for optimization problem. Combining merits of these two technologies, fast pattern classification with optimization is formed. On such CNN-based dynamic programming, if exemplars and test patterns are presented as the goals and the start positions, respectively, the optimal paths from test patterns to their closest exemplars are found. Such paths are utilized as aggregating keys for the classification. The algorithm is similar to the conventional neural network-based method in the use of the exemplar patterns but quite different in the use of the most likely path finding of the dynamic programming. The pattern classification is performed well regardless of degree of the nonlinearity in class borders.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.53-60
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• 2010

We propose a motion planning method for autonomous mobile robots. In order to minimize traveling time, a smooth path and a time optimal velocity profile should be generated under kinematic and dynamic constraints. In this paper, we develop an effective and practical method to generate a good solution with lower computation time. The initial path is obtained from voronoi diagram by Dijkstra's algorithm. Then the path is improved by changing the graph and path simultaneously. We apply the dynamic programming algorithm into the stage of improvement. Simulation results are presented to verify the performance of the proposed method.

• Journal of the Chungcheong Mathematical Society
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• v.25 no.2
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• pp.277-281
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• 2012

I study an optimal consumption and portfolio selection problem with regime-switching using a dynamic programming method. With constant relative risk aversion (CRRA) utility I obtain optimal solutions in closed-form.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.2
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• pp.57-63
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• 2012

Software release planning model of software product lines was formulated as a precedence-constrained multiple 0-1 knapsack problem. The purpose of the model was to maximize the total profit of an entire set of selected features in a software product line over a multi-release planning horizon. The solution approach is a dynamic programming procedure. Feasible solutions at each stage in dynamic programming are determined by using backward dynamic programming approach while dynamic programming for multi-release planning is forward approach. The pre-processing procedure with a heuristic and reduction algorithm was applied to the single-release problems corresponding to each stage in multi-release dynamic programming in order to reduce the problem size. The heuristic algorithm is used to find a lower bound to the problem. The reduction method makes use of the lower bound to fix a number of variables at either 0 or 1. Then the reduced problem can be solved easily by the dynamic programming approaches. These procedures keep on going until release t = T. A numerical example was developed to show how well the solution procedures in this research works on it. Future work in this area could include the development of a heuristic to obtain lower bounds closer to the optimal solution to the model in this article, as well as computational test of the heuristic algorithm and the exact solution approach developed in this paper. Also, more constraints reflecting the characteristics of software product lines may be added to the model. For instance, other resources such as multiple teams, each developing one product or a platform in a software product line could be added to the model.