• IE interfaces
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• v.19 no.1
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• pp.1-8
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• 2006

The mobile communication network has to offer good quality of services (QoS), high capacity, and more coverage at a lower cost. However, with the increase of cellular user, the shortage of capacity due to unbalanced call distribution and lack of QoS are common. This paper deals with dynamic sectorization for efficient resource management to solve load unbalancing among microcells in CDMA (Code Division Multiple Access) microcellular system. Dynamic load balancing can be effected by grouping micro-cells properly and grouping can be developed through a routing mechanism. Therefore, we use ants and their routes to choose the optimum grouping of micro-cells into sectors using Multiple Ant Colony System (MACS)in this paper.

• Journal of Korean Institute of Industrial Engineers
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• v.35 no.4
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• pp.218-225
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• 2009

This paper considers a parallel-machine scheduling problem with job release times and sequence-dependent setup times. The objective of this problem is to determine the allocation policy of jobs and the scheduling policy of machines so as to minimize the weighted sum of setup times, delay times, and tardy times. A mathematical model for optimal solution is derived and a meta heuristic algorithm based on the improved ant colony system is proposed in this paper. The performance of the meta heuristic algorithm is evaluated through compare with optimal solutions using randomly generated several examples.

• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.751-756
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• 2003

Ant Colony Optimization (ACO) is new meta heuristics method to solve hard combinatorial optimization problem. It is a population based approach that uses exploitation of positive feedback as well as greedy search. It was firstly proposed for tackling the well known Traveling Salesman Problem (TSP) . In this paper, we introduce Multi Colony Ant Model that achieve positive interaction and negative interaction through Intensification and Diversification to improve original ACS performance. This algorithm is a method to solve problem through interaction between ACS groups that consist of some agent colonies to solve TSP problem. In this paper, we apply this proposed method to TSP problem and evaluates previous method and comparison for the performance and we wish to certify that qualitative level of problem solution is excellent.

• 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.

• Journal of applied mathematics & informatics
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• v.16 no.1_2
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• pp.337-354
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• 2004

SA, TS, GA and ACS are four of the main algorithms for solving challenging problems of intelligent systems. In this paper we consider Examination Timetabling Problem that is a common problem for all universities and institutions of higher education. There are many methods to solve this problem, In this paper we use Simulated Annealing, Tabu Search, Genetic Algorithm and Ant Colony System in their basic frameworks for solving this problem and compare results of them with each other.

• The KIPS Transactions:PartA
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• v.16A no.2
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• pp.135-142
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• 2009

With the development of ubiquitous computing technology, the number of HCI applications is increasing, where they utilize various contexts to provide adaptive services to users according to the change of contexts, and also, technologies for collecting various sensor data and generating integrated contexts get more important. However, the research on the collection and integration of multi-sensor data is not sufficient when we consider the various utilization areas of the integrated contexts. In particular, they have some problems to be solved such as duplication of the context data and the high system load. In this paper, we propose an integrated context generation scheme based on Ant Colony System. Proposed scheme generates the context data as a form of XML and avoids the generation of unnecessary context information by detecting the repeated sensor information based on the ant colony system. As a result of detections, we reduce wasted resources and repositories when the integrated context is created. We also reduce the overhead for reasoning.

• The KIPS Transactions:PartB
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• v.12B no.7 s.103
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• pp.823-828
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• 2005

Ant Colony System (ACS) applied to the traveling salesman problem (TSP) has demonstrated a good performance on the small TSP. However, in case of the large TSP. ACS does not yield the optimum solution. In order to overcome the drawback of the An for the large TSP, the present study employs the idea of subpath to give more irormation to ants by computing the distance of subpath with length u. in dealing with the large TSP, the experimental results indicate that the proposed algorithm gives the solution much closer to the optimal solution than does the original ACS. In comparison with the original ACS, the present algorithm has substantially improved the performance. By utilizing the proposed algorithm, the solution performance has been enhanced up to $70\%$ for some graphs and around at $30\%$ for averaging over all graphs.

• The KIPS Transactions:PartB
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• v.15B no.3
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• pp.245-252
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• 2008

We present a classification algorithm based on ant colony system(ACS) for classifying digital images. The ACS has been recently emerged as a useful tool for the pattern recognition, image extraction, and edge detection. The classification algorithm of digital images is very important in the application areas of digital image coding, image analysis, and image recognition because it significantly influences the quality of images. The conventional procedures usually classify digital images with the fixed value for the associated parameters and it requires postprocessing. However, the proposed algorithm utilizing randomness of ants yields the stable and enhanced images even for processing the rapidly changing images. It is also expected that, due to this stability and flexibility of the present procedure, the digital images are stably classified for processing images with various noises and error signals arising from processing of the drastically fast moving images could be automatically compensated and minimized.

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.9-15
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• 2009

Ant Colony System is new meta heuristic for hard combinatorial optimization problem. The original ant colony system accomplishes a pheromone updating about only the global optimal path using global updating rule. But, If the global optimal path is not searched until the end condition is satisfied, only pheromone evaporation happens to no matter how a lot of iteration accomplishment. In this paper, the length of the global optimal path does not improved within the limited iterations, we evaluates this state that fall into the local optimum and selects the next node using changed parameters in the state transition rule. This method has effectiveness of the search for a path through diversifications is enhanced by decreasing the value of parameter of the state transition rules for the select of next node, and escape from the local optima is possible. Finally, the performance of Best and Average_Best of proposed algorithm outperforms original ACS.

• 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.