• Title/Summary/Keyword: Meta-Heuristic

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Elite Ant System for Solving Multicast Routing Problem (멀티캐스트 라우팅 문제 해결을 위한 엘리트 개미 시스템)

  • Lee, Seung-Gwan
    • Journal of the Korea Society of Computer and Information
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    • v.13 no.3
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    • pp.147-152
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    • 2008
  • Ant System(AS) is new meta heuristic for hard combinatorial optimization problem. It is a population based approach that uses exploitation of positive feedback as well as greedy search. It was first proposed for tackling the well known Traveling Salesman Problem. In this paper, AS is applied to the Multicast Routing Problem. Multicast Routing is modeled as the NP-complete Steiner tree problem. This is the shortest path from source node to all destination nodes. We proposed new AS to resolve this problem. The proposed method selects the neighborhood node to consider all costs of the edge and the next node in state transition rule. Also, The edges which are selected elite agents are updated to additional pheromone. Simulation results of our proposed method show fast convergence and give lower total cost than original AS and $AS_{elite}$.

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A Study on Identification using Particle Swarm Optimization for 3-DOF Helicopter System (3-자유도 헬리콥터 시스템의 입자군집최적화 기법을 이용한 시스템 식별)

  • Lee, Ho-Woon;Kim, Tae-Woo;Kim, Tae-Hyoung
    • Journal of the Korean Institute of Intelligent Systems
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    • v.25 no.2
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    • pp.105-110
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    • 2015
  • This study proposes the more improved mathematical model than conventional that for the 3-DOF Helicopter System in Quanser Inc., and checks the validity about the proposed model by performance comparison between the controller based on the conventional model and that based on the proposed model. Research process is next : First, analyze the dynamics for the 3-DOF helicopter system and establish the linear mathematical model. Second, check the eliminated nonlinear-elements in linearization process for establishing the linear mathematical model. And establish the improved mathematical model including the parameters corresponding to the eliminated nonlinear-elements. At that time, it is used for modeling that Particle Swarm Optimization algorithm the meta-heuristic global optimization method. Finally, design the controller based on the proposed model, and verify the validity of the proposed model by comparison about the experimental results between the designed controller and the controller based on the conventional model.

A Study on the Restoration System for Distribution Networks Using Dynamic Division Method (동적분할 기법을 이용한 배전망의 정전복구 시스템에 관한 연구)

  • 임찬호
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.17 no.3
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    • pp.64-72
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    • 2003
  • Comparing with transmission networks, the faults in distribution networks more often occurs because of the complicated structure and the adjacency to customers. Moreover the faults give direct damage to customers. So fault diagnosis and blackout restoration in distribution networks are very important elements to reduce the damage of customers and to maintain the stability. The restoration problem of distribution networks is subject to time. Minimizing the switching numbers in restoration process is the crucial element. In other words. the best restoration is to restore all blackout area through just one switching, if not the restoration has to be accomplished through several switching. This paper proposes the efficient restoration system in distribution networks to minimize the switching numbers. The proposed system uses the dynamic division method of hierarchical structure which consists of heuristic searching method and meta algorithm. The proposed system is applied to the sample networks, and the results showed a promising possibility.

Optimization of Unit Commitment Schedule using Parallel Tabu Search (병렬 타부 탐색을 이용한 발전기 기동정지계획의 최적화)

  • Lee, yong-Hwan;Hwang, Jun-ha;Ryu, Kwang-Ryel;Park, Jun-Ho
    • Journal of KIISE:Software and Applications
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    • v.29 no.9
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    • pp.645-653
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    • 2002
  • The unit commitment problem in a power system involves determining the start-up and shut-down schedules of many dynamos for a day or a week while satisfying the power demands and diverse constraints of the individual units in the system. It is very difficult to derive an economically optimal schedule due to its huge search space when the number of dynamos involved is large. Tabu search is a popular solution method used for various optimization problems because it is equipped with effective means of searching beyond local optima and also it can naturally incorporate and exploit domain knowledge specific to the target problem. When given a large-scaled problem with a number of complicated constraints, however, tabu search cannot easily find a good solution within a reasonable time. This paper shows that a large- scaled optimization problem such as the unit commitment problem can be solved efficiently by using a parallel tabu search. The parallel tabu search not only reduces the search time significantly but also finds a solution of better quality.

Task Sequence Optimization for 6-DOF Manipulator in Press Forming Process (프레스 공정에서 6자유도 로봇의 작업 시퀀스 최적화)

  • Yoon, Hyun Joong;Chung, Seong Youb
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.2
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    • pp.704-710
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    • 2017
  • Our research team is developing a 6-DOF manipulator that is adequate for the narrow workspace of press forming processes. This paper addresses the task sequence optimization methods for the manipulator to minimize the task-finishing time. First, a kinematic model of the manipulator is presented, and the anticipated times for moving among the task locations are computed. Then, a mathematical model of the task sequence optimization problem is presented, followed by a comparison of three meta-heuristic methods to solve the optimization problem: an ant colony system, simulated annealing, and a genetic algorithm. The simulation shows that the genetic algorithm is robust to the parameter settings and has the best performance in both minimizing the task-finishing time and the computing time compared to the other methods. Finally, the algorithms were implemented and validated through a simulation using Mathworks' Matlab and Coppelia Robotics' V-REP (virtual robot experimentation platform).

Gray Wolf Optimizer for the Optimal Coordination of Directional Overcurrent Relay

  • Kim, Chang-Hwan;Khurshaid, Tahir;Wadood, Abdul;Farkoush, Saeid Gholami;Rhee, Sang-Bong
    • Journal of Electrical Engineering and Technology
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    • v.13 no.3
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    • pp.1043-1051
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    • 2018
  • The coordination of directional overcurrent relay (DOCR) is employed in this work, considering gray wolf optimizer (GWO), a recently designed optimizer that employs the hunting and leadership attitude of gray wolves for searching a global optimum. In power system protection coordination problem, the objective function to be optimized is the sum of operating time of all the main relays. The coordination of directional overcurrent relays is formulated as a linear programming problem. The proposed optimization technique aims to minimize the time dial settings (TDS) of the relays. The calculation of the Time Dial Setting (TDS) setting of the relays is the core of the coordination study. In this article two case studies of IEEE 6-bus system and IEEE 30-bus system are utilized to see the efficiency of this algorithm and the results had been compared with the other algorithms available in the reference and it was observed that the proposed scheme is quite competent for dealing with such problems. From analyzing the obtained results, it has been found that the GWO approach provides the most globally optimum solution at a faster convergence speed. GWO has achieved a lot of relaxation due to its easy implementation, modesty and robustness. MATLAB computer programming has been applied to see the effectiveness of this algorithm.

Simulation Analysis to Optimize the Management of Military Maintenance Facility (군 정비시설 운용 최적화를 위한 시뮬레이션 분석 연구)

  • Kim, Kyung-Rok;Rhee, Jong-Moon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.15 no.5
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    • pp.2724-2731
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    • 2014
  • As the future national defense plan of government focus on advanced weapon system, military maintenance facility becomes more important. However, military maintenance facility has been managed by director's experience and simple mathematical calculation until now. Thus, the optimization for the management of military maintenance facility is suggested by more scientistic and logical methods in this study. The study follows the procedure below. First, simulation is designed according to the analysis of military maintenance facility. Second, independent variable and dependent variable are defined for optimization. Independent Variable includes the number of maintenance machine, transportation machine, worker in the details of military maintenance facility operation, and dependent variable involves total maintenance time affected by independent variable. Third, warmup analysis is performed to get warmup period, based on the simulation model. Fourth, the optimal combination is computed with evolution strategy, meta-heuristic, to enhance military maintenance management. By the optimal combination, the management of military maintenance facility can gain the biggest effect against the limited cost. In the future, the multipurpose study, to analyze the military maintenance facility covering various weapon system equipments, will be performed.

An Energy- Efficient Optimal multi-dimensional location, Key and Trust Management Based Secure Routing Protocol for Wireless Sensor Network

  • Mercy, S.Sudha;Mathana, J.M.;Jasmine, J.S.Leena
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.10
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    • pp.3834-3857
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    • 2021
  • The design of cluster-based routing protocols is necessary for Wireless Sensor Networks (WSN). But, due to the lack of features, the traditional methods face issues, especially on unbalanced energy consumption of routing protocol. This work focuses on enhancing the security and energy efficiency of the system by proposing Energy Efficient Based Secure Routing Protocol (EESRP) which integrates trust management, optimization algorithm and key management. Initially, the locations of the deployed nodes are calculated along with their trust values. Here, packet transfer is maintained securely by compiling a Digital Signature Algorithm (DSA) and Elliptic Curve Cryptography (ECC) approach. Finally, trust, key, location and energy parameters are incorporated in Particle Swarm Optimization (PSO) and meta-heuristic based Harmony Search (HS) method to find the secure shortest path. Our results show that the energy consumption of the proposed approach is 1.06mJ during the transmission mode, and 8.69 mJ during the receive mode which is lower than the existing approaches. The average throughput and the average PDR for the attacks are also high with 72 and 62.5 respectively. The significance of the research is its ability to improve the performance metrics of existing work by combining the advantages of different approaches. After simulating the model, the results have been validated with conventional methods with respect to the number of live nodes, energy efficiency, network lifetime, packet loss rate, scalability, and energy consumption of routing protocol.

Optimization Algorithm for Minimizing Network Energy Consumption with Traffic Redundancy Elimination (트래픽 중복 제거로 네트워크 에너지 소비를 최소화하기 위한 최적화 알고리즘)

  • Jang, Kil-Woong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.7
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    • pp.930-939
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    • 2021
  • In recent years, the use of broadband bandwidth and redundant links for stable transmission in networks has resulted in excessive energy consumption and reduced transmission efficiency. In this paper, we propose an optimization algorithm that reduces the number of transmission links and minimizes transmission energy by removing redundant traffic in networks where traffic redundancy is allowed. The optimization algorithm proposed in this paper uses the meta-heuristic method using Tabu search algorithm. The proposed optimization algorithm minimizes transmission energy by designing a neighborhood generation method that efficiently routes overlapping traffic. The performance evaluation of the proposed optimization algorithm was performed in terms of the number of links used to transmit all traffic generated in the network and the transmission energy consumed. From the performance evaluation results, it was confirmed that the proposed algorithm is superior to other algorithms previously proposed.

Optimal Design of a Hybrid Structural Control System using a Self-Adaptive Harmony Search Algorithm (자가적응 화음탐색 알고리즘을 이용한 복합형 최적 구조제어 시스템 설계)

  • Park, Wonsuk
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.31 no.6
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    • pp.301-308
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    • 2018
  • This paper presents an optimal design method of a hybrid structural control system considering multi-hazard. Unlike a typical structural control system in which one system is designed for one specific type of hazard, a simultaneous optimal design method for both active and passive control systems is proposed for the mitigation of seismic and wind induced vibration responses of structures. As a numerical example, an optimal design problem is illustrated for a hybrid mass damper(HMD) and 30 viscous dampers which are installed on a 30 story building structure. In order to solve the optimization problem, a self-adaptive Harmony Search(HS) algorithm is adopted. Harmony Search algorithm is one of the meta-heuristic evolutionary methods for the global optimization, which mimics the human player's tuning process of musical instruments. A self-adaptive, dynamic parameter adjustment algorithm is also utilized for the purpose of broad search and fast convergence. The optimization results shows that the performance and effectiveness of the proposed system is superior with respect to a reference hybrid system in which the active and passive systems are independently optimized.