• 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 Communications and Networks
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• v.7 no.4
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• pp.499-508
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• 2005

In this paper, we address the problem of efficient routing and wavelength assignment (RWA) in multi-fiber wavelength division multiplexing (WDM) networks without wavelength translation, under dynamic traffic. We couple Dijkstra's shortest path algorithm with a suitable weight function which chooses optical paths based both on wavelength availability and multi-fiber segments. We compare our approach with other RWA schemes both for regular and irregular WDM multi-fiber network topologies in terms of blocking probability and overall link utilization.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.3
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• pp.263-267
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• 2007

This study proposes a new methodology to estimate the traffic capacity of a personal rapid transit(PRT) system. The proposed method comprises three steps. The first step models the guideway network(GN) of PRT as a digraph, where its node and link represent a station and a one-way guideway link between two stations, respectively. Given local vehicle control strategies, the second step formulates the local traffic capacities through the nodes and links of the GN model. The third step estimates the worst-case local traffic demands based on a shortest-path routing algorithm and an empty vehicle allocation algorithm. By comparing the traffic estimates to the local traffic capacities, we can determine the feasibility of the given GN in traffic capacity.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.59-59
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• 2000

In this paper, we present a framework for modeling and control of multiple mobile robots which cowork within a bounded workspace and limited resources. To achieve this goal, we adopt a formalism of discrete event system and supervisory control theory based on Petri nets. We can divide our whole story into two parts: first, we search the shortest path using the distance vector algorithm, and then we construct the control scheme from which a number of mobile robots can work within a bounded workspace without any collision. The use of Petri net modeling allows us In synthesize a controller which achieves a control specification for the desired closed-loop behavior efficiently. Finally, the usefulness of the proposed Petri net formalism is illustrated by a simulation study.

• Journal of Korean Institute of Industrial Engineers
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• v.26 no.4
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• pp.421-430
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• 2000

This paper presents a new approach which uses $A^*$ search and genetic algorithms for solving large scale multi-objective shortest path problem. The focus of this paper is motivated by the problem of finding Pareto optimal paths for an advanced traveler information system(ATIS) in the context of intelligent transportation system(ITS) application. The individual description, the decoding rule, the selection strategy and the operations of crossover and mutation are proposed for this problem. The keynote points of the algorithm are how to represent individuals and how to calculate the fitness of each individual. The high performance of the proposed algorithm is demonstrated by computer simulations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.599-602
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• 2014

Proposal algorithm in this thesis introduced cells, units of router group, for distributed processing of previous genetic algorithm. This thesis presented ways to reduce search delay time of overall network through cell-based genetic algorithm. With regard to procedures of proposal algorithm, duplicated agents were transferred to the point, where the second, third, and fourth cells were created in order, after the first cell was made, and the agents were engineered to search the shortest path to each cell, and then find the most efficient element through competition.

• Journal of Korea Multimedia Society
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• v.12 no.9
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• pp.1333-1341
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• 2009

Tactical path-finding in computer games is path-finding where a path is selected by considering not only basic elements such as the shortest distance or the minimum time spend but also tactical information of surroundings when deciding character's moving trajectory. One way to include tactical information in path-finding is to represent a heuristic function as a sum of tactical quality multiplied by a weighting factor which is.. determined based on the degree of its importance. The choice of weighting factors for tactics is very important because it controls search performance and the characteristic of paths found. In this paper. we propose a method for improving a heuristic function by adjusting weights based on the difference between paths on examples given by a level designer and paths found during the search process based on the CUITent weighting factors. The proposed method includes the search algorithm modified to detect search errors and learn heuristics and the perceptron-like weight updating formular. Through simulations it is demonstrated how different paths found by tactical path-finding are from those by traditional path-finding. We analyze the factors that affect the performance of learning and show the example applied to the real game environments.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5D
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• pp.649-654
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• 2008

In the definition of non additive path, the sum of travel costs of links making up the path is not equal to the path cost. There are a variety of cases that non-additivity assumption does not hold in transportation fields. Nonetheless, traffic equilibrium models are generally built up on the fundamental hypothesis of additivity assumption. In this case traffic equilibrium models are only applicable within restrictive conditions of the path cost being linear functions of link cost. Area-wide road pricing is known as an example of realistic transportation situations, which violates such additivity assumption. Because travel fare is charged at the moment of driver's passing by exit gate while identified at entry gate, it may not be added linearly proportional to link costs. This research proposes a novel Wordrop type of traffic equilibrium model in terms of area-wide road pricing schemes. It introduces binary indicator variable for the sake of transforming non-additive path cost to additive. Since conventional shortest path and Frank-Wolfe algorithm can be applied without route enumeration and network representation is not required, it can be recognized more generalized model compared to the pre-proposed approaches. Theoretical proofs and case studies are demonstrated.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.132-133
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• 2023

The safe evacuation of people during disasters is of utmost importance. Various life safety evacuation simulation tools have been developed and implemented, with most relying on algorithms that analyze maps to extract the shortest path and guide agents along predetermined routes. While effective in predicting evacuation routes in stable disaster conditions and short timeframes, this approach falls short in dynamic situations where disaster scenarios constantly change. Existing algorithms struggle to respond to such scenarios, prompting the need for a more adaptive evacuation route algorithm that can respond to changing disasters. Artificial intelligence technology based on reinforcement learning holds the potential to develop such an algorithm. As a fundamental step in algorithm development, this study aims to evaluate whether an evacuation algorithm developed by reinforcement learning satisfies the performance conditions of the evacuation simulation tool required by IMO MSC.1/Circ1533.

• The KIPS Transactions:PartC
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• v.15C no.6
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• pp.531-538
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• 2008

With the dynamic and mobile nature of ad hoc networks, links may fail due to topology changes. So, a major challenge in ad hoc network is dynamically to search paths from a source to destination with an efficient routing method, which is an important issue for delay-sensitive real-time application. The main concerns of graph theory in communications are finding connectivity and searching paths using given nodes. A topology of the nodes in ad hoc networks can be modeled as an adjacency matrix. In this paper, based on this adjacency matrix, we propose new path search algorithms using a sequence of matrix calculation. The proposed algorithms can search paths from a destination to a source using connectivity matrix. Two matrix-based algorithms for two different purposes are proposed. Matrix-Based Backward Path Search(MBBS) algorithm is designed for shortest path discovery and Matrix-Based Backward Multipath Search(MBBMS) algorithm is for multipath search.