• Smart Structures and Systems
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• v.31 no.3
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• pp.247-257
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• 2023

In structural health monitoring of large-scale structures, optimal sensor placement plays an important role because of the high cost of sensors and their supporting instruments, as well as the burden of data transmission and storage. In this study, a vibration sensor placement algorithm based on deep reinforcement learning (DRL) is proposed, which can effectively solve non-convex, high-dimensional, and discrete combinatorial sensor placement optimization problems. An objective function is constructed to estimate the quality of a specific vibration sensor placement scheme according to the modal assurance criterion (MAC). Using this objective function, a DRL-based algorithm is presented to determine the optimal vibration sensor placement scheme. Subsequently, we transform the sensor optimal placement process into a Markov decision process and employ a DRL-based optimization algorithm to maximize the objective function for optimal sensor placement. To illustrate the applicability of the proposed method, two examples are presented: a 10-story braced frame and a sea-crossing bridge model. A comparison study is also performed with a genetic algorithm and particle swarm algorithm. The proposed DRL-based algorithm can effectively solve the discrete combinatorial optimization problem for vibration sensor placements and can produce superior performance compared with the other two existing methods.

• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.3
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• pp.187-201
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• 1994

This paper introduces an effective hybridization of the usual simplex method and an interior point method in the convergent framework of Dembo and Sahi. We formulate a specific and detailed algorithm (HYBRID) and report the results of some preliminary testing on small dense problems for its viability. By piercing through the feasible region, the newly developed hybrid algorithm avoids the combinatorial structure of linear programs, and several other interesting and important characteristics of this algorithm are also discussed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.7
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• pp.1340-1345
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• 2001

In this paper, we proposed the method computing the optimal solution of Optical Flow(OF) representing the moving information of moving object and improving the operating speed. In order to do that, we computed the optimal solution of OF using the Combinatorial Hough Transform(CHT) and Voting accumulation and simply searched the moving object compared to conventional method.

• ETRI Journal
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• v.24 no.3
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• pp.251-254
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• 2002

We developed a method for optimal superframe design in the multi-frequency time division multiple access (MF-TDMA) return-link of a satellite multimedia interactive network called a digital video broadcasting return channel over satellite (DVB-RCS) sub-network. To find the optimal superframe pattern with the maximum data throughput, we formulated the design problem as a non-linear combinatorial optimization problem. We also devised the proposed simple method so that it would have field applicability for improving radio resource utilization in the MF-TDMA return link.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.5
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• pp.1149-1160
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• 2005

Generally, the network topology design problem, which is difficult to solve with the classical method because it has exponentially increasing complexity with the augmented network size, is characterized as a kind of NP-hard combinatorial optimization problem. The problem of this research is to design the highly reliable network topology considering the connection cost and all-terminal network reliability, which can be defined as the probability that every pair of nodes can communicate with each other. In order to solve the highly reliable network topology design problem minimizing the construction cost subject to network reliability, we proposes an efficient two phase approach to design reliable network topology, i.e., the first phase employs, a genetic algorithm (GA) which uses $Pr\ddot{u}fer$ number for encoding method and backtracking Algorithm for network reliability calculation, to find the spanning tree; the second phase is a greedy method which searches the optimal network topology based on the spanning ree obtained in the first phase, with considering 2-connectivity. finally, we show some experiments to demonstrate the effectiveness and efficiency of our two phase approach.

• Journal of Electrical Engineering and Technology
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• v.6 no.2
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• pp.174-181
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• 2011

This paper proposes a novel binary ant colony optimization (NBACO) method. The proposed NBACO is based on the concept and principles of ant colony optimization (ACO), and developed to solve the binary and combinatorial optimization problems. The concept of conventional ACO is similar to Heuristic Dynamic Programming. Thereby ACO has the merit that it can consider all possible solution sets, but also has the demerit that it may need a big memory space and a long execution time to solve a large problem. To reduce this demerit, the NBACO adopts the state probability matrix and the pheromone intensity matrix. And the NBACO presents new updating rule for local and global search. The proposed NBACO is applied to test power systems of up to 100-unit along with 24-hour load demands.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.6
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• pp.83-95
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• 2003

In this study, a new concept in a paddy consolidation project is introduced in that curved parallel terracing with contour-lined layout is adopted in sloping areas instead of conventional rectangular terracing. The contoured layout reduces earth-moving considerably compared to rectangular methods in consolidation projects. The objective of the paper is to develop a combinatorial optimization model using the network theory for the design of contour-lined plots which minimizes the volume of earth moving. The results showed that as the length of short side of plot is longer or the land slope is steeper, the volume of earth moving for land leveling increases. The developed optimization model is applied for three consolidated districts and the resulting optimal earth moving is compared with the volume of earth from the conventional method. The shorter is the minimum length of short side of a polt with increases the number of plots, the less is the volume of earth. As the minimum length of short side is 20 m for efficient field works by farm machinery, the volume of earth moving of optimal plot is less by 21.0∼27.1 % than that of the conventional consolidated plots.

• Journal of Korean Society of Water and Wastewater
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• v.28 no.1
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• pp.103-110
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• 2014

In this study, the evaluation criteria of performance and applicability is developed to rank the combinatorial technologies for SWG (Smart Water Grid) system using AHP (Analytic Hierarchy Process) method. Security, safety, solution, suitability and sustainability which are goals of SWG technology, are used as upper level hierarchy elements. And three detailed elements for each upper level hierarchy are adopted as the lower level hierarchy. The weighted value which represents the importance of each element, could be determined through questionnaires accomplished by groups of specialists who are engaged in relevant waster industry and research area. To assess the accuracy of the evaluation criteria developed in this study, a simulation on four decision alternatives for smart water grid was carried out as an evaluation. Consequently which showed 90 % of accuracy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.1C
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• pp.1-5
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• 2008

Optical code division multiple access(OCDMA) systems make the active users to share the bandwidth by simply assigning distinct optical orthogonal codeword to each active user. An optical orthogonal code(OOC) is a collection of binary sequences with good correlation properties which are important factors of determining the capacity of OCDMA systems. Recently, 2-D OOC construction method is frequently researched which is able to support more users than 1-D OOC. In this paper, a combinatorial construction of simple multi-weight 2-D OOC with autocorrelation 0 and crosscorrelation 1 is proposed and the bound on the size of these codes is derived.

• Industrial Engineering and Management Systems
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• v.11 no.4
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• pp.310-330
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• 2012

Scheduling is an important tool for a manufacturing system, where it can have a major impact on the productivity of a production process. In manufacturing systems, the purpose of scheduling is to minimize the production time and costs, by assigning a production facility when to make, with which staff, and on which equipment. Production scheduling aims to maximize the efficiency of the operation and reduce the costs. In order to find an optimal solution to manufacturing scheduling problems, it attempts to solve complex combinatorial optimization problems. Unfortunately, most of them fall into the class of NP-hard combinatorial problems. Genetic algorithm (GA) is one of the generic population-based metaheuristic optimization algorithms and the best one for finding a satisfactory solution in an acceptable time for the NP-hard scheduling problems. GA is the most popular type of evolutionary algorithm. In this survey paper, we address firstly multiobjective hybrid GA combined with adaptive fuzzy logic controller which gives fitness assignment mechanism and performance measures for solving multiple objective optimization problems, and four crucial issues in the manufacturing scheduling including a mathematical model, GA-based solution method and case study in flexible job-shop scheduling problem (fJSP), automatic guided vehicle (AGV) dispatching models in flexible manufacturing system (FMS) combined with priority-based GA, recent advanced planning and scheduling (APS) models and integrated systems for manufacturing.