• Title/Summary/Keyword: 개미 시스템

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Ant Colony Intelligence in Cognitive Agents for Autonomous Shop Floor Control (자율적 제조 공정 관리를 위한 인지 에이전트의 개미 군집 지능)

  • Park, Hong-Seok;Park, Jin-Woo;Hien, Tran Ngoc
    • Journal of Institute of Control, Robotics and Systems
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    • v.17 no.8
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    • pp.760-767
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    • 2011
  • The flexibility and evolvability are critical characteristics of modern manufacturing to adapt to changes from products and disturbances in the shop floor. The technologies inspired from biology and nature enable to equip the manufacturing systems with these characteristics. This paper proposes an ant colony inspired autonomous manufacturing system in which the resources on the shop floor are considered as the autonomous entities. Each entity overcomes the disturbance by itself or negotiates with the others. The swarm of cognitive agents with the ant-like pheromone based negotiation mechanism is proposed for controlling the shop floor. The functionality of the developed system is proven on the test bed.

A Two-stage Meta-heuristic Algorithm for Container Load Sequencing (Meta-heuristic 기법을 이용한 2단계 컨테이너 적하계획 알고리즘)

  • 김갑환;류광렬;박영만;강진수;이용환
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2000.04a
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    • pp.9-12
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    • 2000
  • 컨테이너 터미널에서 효율적인 적하작업 계획을 자동으로 생성하는 알고리즘을 연구하였다. 실제 터미널에서 계획자들이 적하작업 계획시에 고려하는 제약소건 및 효율적인 계획을 위한 고려사항을 조사하였다. 이를 바탕으로 1단계에서는 개미시스템(ant system)이라는 인공지능기법을 적용하여 제약조건을 만족시키면서 원활한 적하작업이 진행될 수 있도록 컨테이너 크레인과 트랜스퍼 크레인의 이동순서와 위치를 결정하고, 2단계에서는 1단계에서의 결과를 바탕으로 빔탐색법(beam search)을 사용하여 컨테이너 개개의 작업순서를 결정하는 알고리즘을 개발하였다. 또한 개발된 시스템의 성능을 검증하기 위하여 최근의 대형선반에 대한 실제 현장자료를 바탕으로 실험을 수행하였다.

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Growth of Minuartia laricina, Arenaria juncea, and Corydalis speciose in Field with Various Soil Water Contents (토양 수분 함량에 따른 너도개미자리, 벼룩이울타리, 산괴불주머니의 노지 생육)

  • Gil, Min;Kwon, Hyuck Hwan;Kwon, Young Hyun;Jung, Mi Jin;Kim, Sang Yong;Rhie, Yong Ha
    • Journal of Bio-Environment Control
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    • v.29 no.4
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    • pp.344-353
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    • 2020
  • Plants native in Korea have not only ornamental values but also have excellent environmental adaptability, so they can be used as garden plants. Studies on proper volumetric water content (VWC) of substrates have been reported, but many have been conducted in glasshouse conditions where environmental factors were controlled. When considering garden planting, it is necessary to perform the automated irrigation system in outdoor conditions where rainfall occurs at frequent intervals. This research aimed to investigate the VWC suitable for the growth of Minuartia laricina, Arenaria juncea, and Corydalis speciosa in open filed. Sandy soil which consisted of particles of weathered rock was used, and the VWC of 0.15, 0.20, 0.25, and 0.30 ㎥·m-3 was maintained using an automated irrigation system with capacitance soil moisture sensors and a data logger. No significant differences in growth and antioxidant enzymes activity of A. juncea were observed among VWC treatments. However, the survival rate was low at VWC 0.30 ㎥·m-3 treatment, which was the highest soil moisture content. Even considering the efficiency of water use, we recommended that VWC 0.15-0.20 ㎥·m-3 is suitable for the cultivation of A. juncea. Minuartia laricina showed better growth with lower VWC. Because of frequent rainfall in open field, plant volume and survival rate was high even in VWC 0.15 ㎥·m-3 treatment. In C. speciosa, the plant height, number of shoots and lateral shoots, and fresh and dry weight were higher in plants grown in VWC 0.25 ㎥·m-3 as compared with that in the plants grown at 0.15, 0.20, and 0.30 ㎥·m-3. Based on these results, M. laricina needed less water in open filed, and A. juncea and C. speciosa required higher VWC, but excessive water should be avoided.

A Multi-objective Ant Colony Optimization Algorithm for Real Time Intrusion Detection Routing in Sensor Network (센서 네트워크에서 실시간 침입탐지 라우팅을 위한 다목적 개미 군집 최적화 알고리즘)

  • Kang, Seung-Ho
    • KIPS Transactions on Computer and Communication Systems
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    • v.2 no.5
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    • pp.191-198
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    • 2013
  • It is required to transmit data through shorter path between sensor and base node for real time intrusion detection in wireless sensor networks (WSN) with a mobile base node. Because minimum Wiener index spanning tree (MWST) based routing approach guarantees lower average hop count than that of minimum spanning tree (MST) based routing method in WSN, it is known that MWST based routing is appropriate for real time intrusion detection. However, the minimum Wiener index spanning tree problem which aims to find a spanning tree which has the minimum Wiener index from a given weighted graph was proved to be a NP-hard. And owing to its high dependency on certain nodes, minimum Wiener index tree based routing method has a shorter network lifetime than that of minimum spanning tree based routing method. In this paper, we propose a multi-objective ant colony optimization algorithm to tackle these problems, so that it can be used to detect intrusion in real time in wireless sensor networks with a mobile base node. And we compare the results of our proposed method with MST based routing and MWST based routing in respect to average hop count, network energy consumption and network lifetime by simulation.

A Study on User Experience on Ant Insurance Claims China's Mobile Insurance Platform -Focused on Alipay- (중국 모바일 보험 플랫폼 개미 보험청구에 관한 사용자 경험 연구 -알리페이 중심으로-)

  • Son, Young-Ho;Kim, Seung-In
    • Journal of Digital Convergence
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    • v.19 no.9
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    • pp.317-322
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    • 2021
  • This study focuses on user experience of Ant Insurance Platform(insurance product of Alibaba) and provides insights and improvement advises based on the survey conducted. Given that insurance claim is the most controversial part during the whole process, it is essential to conduct corresponding research from users' prospective. Some Chinese users between their 20's and 40's, who are major users of mobile insurance platforms, were selected as a sample group. Questionaire survey, which was made based on measurement items from Information systems success model, as well as in-depth interview was conducted within the group. According to the result, health, among all kinds, is the most difficult insurance to claim, which was mainly cause by security and information concerns. In order to enhance security, more options should be given to users. As for information, complains should be delt carefully and transparently. This study is expected to be used as referential material for mobile insurance platforms and user experience of insurance claims.

Learning of Adaptive Behavior of artificial Ant Using Classifier System (분류자 시스템을 이용한 인공개미의 적응행동의 학습)

  • 정치선;심귀보
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.10a
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    • pp.361-367
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    • 1998
  • The main two applications of the Genetic Algorithms(GA) are the optimization and the machine learning. Machine Learning has two objectives that make the complex system learn its environment and produce the proper output of a system. The machine learning using the Genetic Algorithms is called GA machine learning or genetic-based machine learning (GBML). The machine learning is different from the optimization problems in finding the rule set. In optimization problems, the population of GA should converge into the best individual because optimization problems, the population of GA should converge into the best individual because their objective is the production of the individual near the optimal solution. On the contrary, the machine learning systems need to find the set of cooperative rules. There are two methods in GBML, Michigan method and Pittsburgh method. The former is that each rule is expressed with a string, the latter is that the set of rules is coded into a string. Th classifier system of Holland is the representative model of the Michigan method. The classifier systems arrange the strength of classifiers of classifier list using the message list. In this method, the real time process and on-line learning is possible because a set of rule is adjusted on-line. A classifier system has three major components: Performance system, apportionment of credit system, rule discovery system. In this paper, we solve the food search problem with the learning and evolution of an artificial ant using the learning classifier system.

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Ant-based Routing in Wireless Sensor Networks (개미 시스템을 이용한 무선 센서 네트워크 라우팅 알고리즘 개발)

  • Ok, Chang-Soo
    • Journal of the Korean Operations Research and Management Science Society
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    • v.35 no.2
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    • pp.53-69
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    • 2010
  • This paper proposes an ant-based routing algorithm, Ant System-Routing in wireless Senor Networks(AS-RSN), for wireless sensor networks. Using a transition rule in Ant System, sensors can spread data traffic over the whole network to achieve energy balance, and consequently, maximize the lifetime of sensor networks. The transition rule advances one of the original Ant System by re-defining link cost which is a metric devised to consider energy-sufficiency as well as energy-efficiency. This metric gives rise to the design of the AS-RSN algorithm devised to balance the data traffic of sensor networks in a decentralized manner and consequently prolong the lifetime of the networks. Therefore, AS-RSN is scalable in the number of sensors and also robust to the variations in the dynamics of event generation. We demonstrate the effectiveness of the proposed algorithm by comparing three existing routing algorithms: Direct Communication Approach, Minimum Transmission Energy, and Self-Organized Routing and find that energy balance should be considered to extend lifetime of sensor network and increase robustness of sensor network for diverse event generation patterns.

Ant Colony System for Vehicle Routing Problem with Time Window (시간제약이 있는 차량경로문제에 대한 개미군집 시스템 해법)

  • Lee, Sang-Heon;Lee, Seung-Won
    • Journal of the Korean Operations Research and Management Science Society
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    • v.34 no.1
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    • pp.153-165
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    • 2009
  • This paper apollos an ant colony system (ACS) for the vehicle routing problem with time window (VRPTW). The VRPTW is a generalization of the VRP where the service of a customer can begin within the time windows defined by the earliest and latest times when the customer will permit the start of service. The ACS has been applied effectively in geographical environment such as TSP or VRP by meta-heuristic that imitate an ant's biologic special duality in route construction, 3 saving based ACS (SB-ACS) is introduced and its solution is improved by local search. Through iterative precesses, the SB-ACS is shown to drive the best solution. The algorithm has been tested on 56 Solomon benchmarking problems and compared to the best-known solutions on literature. Experimental results shows that SB-ACS algorithm could obtain food solution in total travel distance minimization.

Optimal Design of Reporting Cell Location Management System using Ranking Ant Colony System (랭킹개미군전략을 이용한 리포팅셀 위치관리시스템 최적 설계)

  • Kim, Sung-Soo;Kim, Geun-Bae
    • IE interfaces
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    • v.19 no.2
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    • pp.168-173
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    • 2006
  • In the Reporting Cell Location Management (RCLM) system, a subset of cells in the network is designated as the reporting cells. Each mobile terminal performs location update only when it enters one of these reporting cells. When a call arrives, the paging is confined to the reporting cell the user last reported and the neighboring bounded non-reporting cells. Frequent location update may result in degradation of quality of service due to interference. Miss on the location of a mobile terminal will necessitate a search operation on the network when a call comes in. We must decide the number of reporting cells and which cell should be reporting cell to balance the registration (location update) and search (paging) operations to minimize the cost of RCLM system. This paper proposes a ranking ant colony system (RACS) for optimization of RCLM system.

Ant Colony System for Vehicle Routing Problem with Simultaneous Delivery and Pick-up under Time Windows (시간제약하 배달과 수거를 동시에 수행하는 차량경로문제를 위한 개미군집시스템)

  • Lee, Sang-Heon;Kim, Yong-Dae
    • Journal of Korean Institute of Industrial Engineers
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    • v.35 no.2
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    • pp.160-170
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    • 2009
  • This paper studies a vehicle routing problem variant which considers customers to require simultaneous delivery and pick-up under time windows(VRPSDP-TW). The objective of this paper is to minimize the total travel distance of routes that satisfy both the delivery and pick-up demand. We propose a heuristic algorithm for solving the VRPSDP-TW, based on the ant colony system(ACS). In route construction, an insertion algorithm based ACS is applied and the interim solution is improved by local search. Through iterative processes, the heuristic algorithm drives the best solution. Experiments are implemented to evaluate a performance of the algorithm on some test instances from literature.