• Structural Engineering and Mechanics
• /
• v.39 no.1
• /
• pp.147-168
• /
• 2011

To ensure safety and long term performance, structural control has rapidly matured over the past decade into a viable means of limiting structural responses to strong winds and earthquakes. Nonlinear response history analysis requires rigorous procedure to compute seismic demands. Therefore the simplified nonlinear analysis procedures are useful to determine performance of the structure. In this investigation, application of improved capacity demand diagram method in the control of structural system is presented for the first time. Developed pole assignment method (DPAM) in structural systems control is introduced. Genetic algorithm (GA) is employed as an optimization tool for minimizing a target function that defines values of coefficient matrices providing the placement of actuators and optimal control forces. The ground acceleration is modified under induced control forces. Due to this, performance of structure based on improved nonlinear demand diagram is selected to threshold of nonlinear behavior of structure. With small energy consumption characteristics, semi-active devices are especially attractive solutions for limiting earthquake effects. To illustrate the efficiency of DPAM, a 30-story steel moment frame structure employing the semi-active control devices is applied. In comparison to the widely used linear quadratic regulation (LQR), the DPAM controller was shown to be just as effective and better in the reduction of structural responses during large earthquakes.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.47 no.2
• /
• pp.190-197
• /
• 2024

By the recent fast growth of e-commerce markets, it has been stimulated to study order picking systems to improve their efficiency in distribution centers. Many companies and researchers have been developed various types of order picking systems and pursued the corresponding optimal operation policies. However, the performances of the systems with the optimal policies often depend on the structures of the centers and the operation environments. Based on a simulation model that mimics a unique zone picking system operated by a real company in the Republic of Korea, this study compares several operation policies and finds the most appropriate order selection rule and worker assignment policy for the system. Under all scenarios considered in this study, simulation results show that it is recommendable to assign more efficient workers to the zones with heavier workload. It also shows that selecting the order with the maximum number of non-repeatedly visited zones from the order list provides the most consistent and stable performances with respect to flow time, makespan, and utilization of the system even under the scenario with the breakdown zones. On the other hand, selecting the order with the minimum ratio of penalty to the number of zones performs the worst in all scenarios considered.

• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.3
• /
• pp.209-218
• /
• 2013

Military surveillance systems with electro-optical sensors can be used to track a number of targets efficiently and reliably. In MTT (Multi-Target Tracking), joint events in which different tracks share the same measurements may occur. Measurement-to-track assignment are computationally challenging because of the number of operations increases exponentially with number of tracks and number of measurements. IHPDA (Integrated Highest Probability Data Association) based on a 2D-Assignment technique can find an optimal solution for measurement to track one-to-one assignments for complex environments. In this paper, LM-IHPDA (Linear Multi-Target IHPDA) which does not need to form all feasible joint events of association and thus the computational load is linear in the number of tracks and the number of measurements. Simulation studies illustrate the effectiveness of this approach in an infrared image environment.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.41 no.3
• /
• pp.23-36
• /
• 2016

We consider a model that minimizes the total cost incurred by assigning available weapons to existing targets in order to reduce enemy threats, which is called the weapon target assignment problem (WTAP). This study addresses the stochastic versions of WTAP, in which data, such as the probability of destroying a target, are given randomly (i.e., data are identified with certain probability distributions). For each type of random data or parameter, we provide a stochastic optimization model on the basis of the expected value or scenario enumeration. In particular, when the probabilities of destroying targets depending on weapons are stochastic, we present a stochastic programming formulation with a simple recourse. We show that the stochastic model can be transformed into a deterministic equivalent mixed integer programming model under a certain discrete probability distribution of randomness. We solve the stochastic model to obtain an optimal solution via the mixed integer programming model and compare this solution with that of the deterministic model.

• Journal of the Korean Society for information Management
• /
• v.29 no.2
• /
• pp.225-246
• /
• 2012

This study purported to investigate the possibility of automatic descriptor assignment using the reclassification of author keywords in domestic scholarly databases. In the first stage, we selected optimal classifiers and parameters for the reclassification by comparing the characteristics of machine learning classifiers. In the next stage, learning the author keywords that were assigned to the selected articles on readings, the author keywords were automatically added to another set of relevant articles. We examined whether the author keyword reclassifications had the effect of vocabulary control just as descriptors collocate the documents on the same topic. The results showed the author keyword reclassification had the capability of the automatic descriptor assignment.

• Journal of the Korea Society of Computer and Information
• /
• v.19 no.4
• /
• pp.91-99
• /
• 2014

TThis paper suggests an heuristic polynomial time algorithm to solve the optimal solution for QAP (quadratic assignment problem). While Hungarian algorithm is most commonly used for a linear assignment, there is no polynomial time algorithm for the QAP. The proposed algorithm derives a grid type layout among unit distances of a distance matrix. And, we apply max-flow/min-distance approach to assign this grid type layout in such a descending order way that the largest flow is matched to the smallest unit distance from flow matrix. Evidences from implementation results of the proposed algorithm on various numerical grid type QAP examples show that a solution to the QAP could be obtained by a polynomial algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.19 no.9
• /
• pp.1658-1667
• /
• 1994

In a cellular mobile communication control system, assignment channel for a call in a cell so as to achieve high spectral efficience is an important problem within limited frequence bandwidth. The spectral efficiency is related to the coloring problem of graph theory in a cellular mobile communication control system. In this paper, we propose channel offset scheme using a graph theory of cellular mobile communication control system and formulate chromatic bandwidth of channel offset system which is related graph coloring problem. From formulated channel assignment problem, we investgate an optimal channel offset scheme of more efficent frequence spectrum and cell design according to channel constitution and give and upper and lower bound for overall srectral bandwidth.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.11
• /
• pp.5455-5475
• /
• 2016

In this article, we model the distributed relay assignment network as a many-to-one matching market with peer effects. We discuss two scenarios for throughput optimization of relay networks: the scenario of aggregate throughput optimization and the scenario of fairness performance optimization. For the first scenario, we propose a Mutual Benefit-based Deferred Acceptance (MBDA) algorithm to increase the aggregate network throughput. For the second scenario, instead of using the alternative matching scheme, a non-substitution matching algorithm (NSA) is designed to solve the fairness problem. The NSA improves the fairness performance. We prove that both two algorithms converge to a globally stable matching, and discuss the practical implementation. Simulation results show that the performance of MBDA algorithm outperforms existing schemes and is almost the same with the optimal solution in terms of aggregate throughput. Meanwhile, the proposed NSA improves fairness as the scale of the relay network expands.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.23 no.4
• /
• pp.337-345
• /
• 2020

The Weapon-Target Assignment(WTA) problem can be formulated as an optimization problem that minimize the threat of targets. Existing methods consider the trade-off between optimality and execution time to meet the various mission objectives. We propose a multi-agent reinforcement learning algorithm for WTA based on mean field game to solve the problem in real-time with nearly optimal accuracy. Mean field game is a recent method introduced to relieve the curse of dimensionality in multi-agent learning algorithm. In addition, previous reinforcement learning models for WTA generally do not consider weapon interference, which may be critical in real world operations. Therefore, we modify the reward function to discourage the crossing of weapon trajectories. The feasibility of the proposed method was verified through simulation of a WTA problem with multiple targets in realtime and the proposed algorithm can assign the weapons to all targets without crossing trajectories of weapons.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.21 no.4
• /
• pp.171-176
• /
• 2021

This paper deals with bid evaluation problem that chooses the vendors and quantity with minimum purchasing cost for bid information of setup cost and unit price. For this problem, the branch-and-bound(BB) and branch-and-cut(BC) methods are well-known. But these methods can be fail to obtain the optimal solution. This paper gets the initial feasible solution with procuring quantity assignment principle in accordance with the unit price or setup cost rank-first. Then procuring quantity moving optimization(vendor change) is execute take account of unit price or setup cost rank. As a result of experimentation, the propose algorithm is significantly lower compared to BB and BC.