• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.08a
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• pp.87-90
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• 2008

Dynamic Heuristic(DH) is not fixed data and is dynamically modified using transferred real time road data from server In this paper, we propose path-finding algorithm with Maximum Speed Dynamic Heuristic (DH-MAX) and do an experiment. The DH-MAX is to be used the highest speed as DH, in real map divided by same sire. And proposed algorithm searches path using the priority searching only of the fixed data, but also the highest speed with real time information. In the performance test, the quality of path is enhanced but the cost of searching is increased than $A^*$ algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.8
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• pp.1825-1842
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• 2013

Rapid growth of the IT industry has led to significant energy consumption in the last decade. Data centers swallow an enormous amount of electrical energy and have high operating costs and carbon dioxide excretions. In response to this, the dynamic consolidation of virtual machines (VMs) allows for efficient resource management and reduces power consumption through the live migration of VMs in the hosts. Moreover, each client typically has a service level agreement (SLA), this leads to stipulations in dealing with energy-performance trade-offs, as aggressive consolidation may lead to performance degradation beyond the negotiation. In this paper we propose a heuristic based resource allocation of VM selection and a VM allocation approach that aims to minimize the total energy consumption and operating costs while meeting the client-level SLA. Our experiment results demonstrate significant enhancements in cloud providers' profit and energy savings while improving the SLA at a certain level.

• 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.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.11
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• pp.84-92
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• 1993

Calibration of Engine models is a painstaking process but very important for successful application to automotive industry problems. A combined heuristic and machine learning approach has therefore been adopted to improve the efficiency of model calibration. We developed an intelligent calibration program called ICALIB. It has been used on a daily basis for engine model applications, and has reduced the time required for model calibrations from many hours to a few minutes on average. In this paper, we describe the heuristic control strategies employed in ICALIB such as a hill-climbing search based on a state distance estimation function, incremental problem solution refinement by using a dynamic tolerance window, and calibration target parameter ordering for guiding the search. In addition, we present the application of amachine learning program called GID3*for automatic acquisition of heuristic rules for ordering target parameters.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.8
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• pp.623-631
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• 2003

We have fabricated the two-dimensional inverted pendulum system and designed its controller. The two-dimensional inverted pendulum system, which is composed of X-Y table, is actuated through timing belt by each of two geared DC motors. And the control goal is that the rod is always kept to a vertical position to any distrubance and is quickly moved to the desired position. Because this system has generally nonlinear dynamic characteristics and X-axis and Y-axis move together, it is very difficult to find its exact mathematical model and to design its controller. Therefore, we have designed the PID controller with simple structure and excellent performance. Genetic algorithm(GA), which is blown as one of probabilistic searching methods, and human's heuristic control strategy are introduced to design an optimal PID controller. The usefulness of the proposed GA based PID coefficient searching technique is verified through the experiments and computer simulations.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.5
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• pp.283-289
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• 2003

This paper proposes an expert system which can determine automatically the shunting routes corresponding to the given shunting works by considering totally the train operating environments in the station. The expert system proposes the multiple shunting routes with priority of selection based on heuristic search strategy. Accordingly, system operator can select a shunting route with the safety and efficiency among the those shunting routes. The expert system consists of a main inference engine and a sub inference engine. The main inference engine determines the shunting routes with selection priority using the segment routes obtained from the sub inference engine. The heuristic rules are extracted from operating knowledges of the veteran route operator and station topology. It is implemented in C computer language for the purpose of the implementation of the inference engine using the dynamic memory allocation technique. And, the validity of the builted expert system is proved by a test case for the model station.

• IE interfaces
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• v.22 no.1
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• pp.63-72
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• 2009

This paper considers a transporter scheduling problem under dynamic block transportation environment in shipbuilding. In dynamic situations, there exist the addition, cancellation or change of block transportation requirements, sudden breakdowns and maintenance of transporters. The transportation of the blocks in the shipyard has some distinct characteristics. Some blocks are available to be picked up at a specific time during the planning horizon while some other blocks need to be delivered before a specific time. These requirements cause two penalty times: 1) delay times incurred when a block is picked up after a required start time, and 2) tardy times incurred when a block shipment is completed after the required delivery time. The blocks are located at different areas in the shipyard and transported by transporters. The objective of this paper is to propose a heuristic algorithm based on a network flow model which minimize the weighted sum of empty transporter travel times, delay times, and tardy times. Also, a rolling-horizon scheduling method is proposed for dynamic block transportation environment. The performance of the proposed heuristic algorithms are evaluated through a simulation experiment.

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.329-337
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• 2016

With the increasing deployment of distributed generators in the distribution system, a very large search space is required when dynamic programming (DP) is applied for the optimized dispatch schedules of voltage and reactive power controllers such as on-load tap changers, distributed generators, and shunt capacitors. This study proposes a new optimal voltage and reactive power scheduling method based on dynamic programming with a heuristic searching space reduction approach to reduce the computational burden. This algorithm is designed to determine optimum dispatch schedules based on power system day-ahead scheduling, with new control objectives that consider the reduction of active power losses and maintain the receiving power factor. In this work, to reduce the computational burden, an advanced voltage sensitivity index (AVSI) is adopted to reduce the number of load-flow calculations by estimating bus voltages. Moreover, the accumulated switching operation number up to the current stage is applied prior to the load-flow calculation module. The computational burden can be greatly reduced by using dynamic programming. Case studies were conducted using the IEEE 30-bus test systems and the simulation results indicate that the proposed method is more effective in terms of saving electric charges and improving the voltage profile than loss minimization.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.179-182
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• 2008

It needs to consider of turns during a path-finding on real road network. Because a car is delayed by waiting a traffic signal and decreasing speed when drived in a turn road such as cross road and slip road. If a straightness of a path is increased, a real cost of traveling should be able to decrease. An older method, the algorithm with Turn Heuristic, considered of this case. The algorithm, that differently gave weights to left, right and U-turns, improved a straightness of a path, but increased a cost of exploring. In this paper, we propose a improved Turn Heuristic Algorithm. Proposed algorithm uses Dynamic Turn Heuristic. It is able to more decrease a cost of exploring than older method by using the Turn Heuristic in a part of path-finding.

• The Transactions of the Korea Information Processing Society
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• v.4 no.10
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• pp.2470-2476
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• 1997

We propose a new real-time search algorithm and provide experimental evaluation and comparison of the new algorithm with mini-min lookahead algorithm. Many other real-time heuristic-search approached often divide the problem space to several sub-problems. In this paper, the proposed algorithm guarantees not only the sub-problem deadline but also total deadline. Several heuristic real-time search algorithms such as $RTA^{\ast}$, SARTS and DYNORA have been proposed. The performance of such algorithms depend on the quality of their heuristic functions, because such algorithms estimate the search time based on the heuristic function. In real-world problem, however, we often fail to get an effective heuristic function beforehand. Therefore, we propose a new real-time algorithm that determines the sub-problem deadline based on the status of search space during sub-problem search process. That uses the cut-off method that is a dynamic stopping-criterion-strategy to search the sub-problem.