• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.632-650
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• 2013

The paper considers a spectrum sharing cognitive radio (CR) network coexisting with a primary network under the average interference power constraint. In particular, the secondary user (SU) is assumed to carry delay-sensitive services and thus shall satisfy a given delay quality-of-service (QoS) constraint. The secondary receiver is also assumed to be equipped with multiple antennas to perform maximal ratio combining (MRC) to enhance SU performance. We investigate the effective capacity of the SU with MRC diversity under aforementioned constraints in Nakagami fading environments. Particularly, we derive the optimal power allocation to achieve the maximum effective capacity of the SU, and further derive the effective capacity in closed-form. In addition, we further obtain the closed-form expressions for the effective capacities under three widely used power and rate adaptive transmission schemes, namely, optimal simultaneous power and rate adaptation (opra), truncated channel inversion with fixed rate (tifr) and channel inversion with fixed rate without truncation (cifr). Numerical results supported by simulations are presented to consolidate our studies. The impacts on the effective capacity of various system parameters such as the number of antennas, the average interference power constraint and the delay QoS constraint are investigated in detail. It is shown that MRC diversity can significantly improve the effective capacity of the SU especially for cifr transmission scheme.

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.417-427
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• 2017

Power allocation is an important factor for cognitive radio networks to achieve higher communication capacity and faster equilibrium. This paper considers power allocation problem to each cognitive user to maximize capacity of the cognitive systems subject to the constraints on the total power of each cognitive user and the interference levels of the primary user. Since this power control problem can be formulated as a mixed-integer nonlinear programming (NP) equivalent to variational inequality (VI) problem in convex polyhedron which can be transformed into complementary problem (CP), we utilize modified projection method to solve this CP problem instead of finding NP solution and give a power control allocation algorithm with a subcarrier allocation scheme. Simulation results show that the proposed algorithm performs well and effectively reduces the system power consumption with almost maximum capacity while achieve Nash equilibrium.

• Korean System Dynamics Review
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• v.8 no.2
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• pp.51-82
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• 2007

The purpose of this paper is exploring changes in land use pattern when considering environmental carrying capacity. A sustainable development requires a society to define sustainability constraints, environmental carrying capacity. Environmental carrying capacity can be defined as a level of human activity a region can sustain at a desired level of quality of environment. This concept of environmental carrying capacity can be applied to land use to explore sustainable land use pattern. Since land use pattern can affect environment in an important way, exploring sustainable land use pattern within the limit of environmental carrying capacity can suggest useful implications for a sustainable regional management and planning. For this purpose, this paper built the environmental carrying capacity land use model and applied it to the Metropolitan Area, Korea. System dynamics modeling methods was used to build the model. The model developed in this paper consisted of 6sectors; population, housing, industry, land, environment, and traffic sector. The model limits its main focus on the NO2 level as an indicator of quality of environment in Metropolitan Area. Box model was translated into system dynamics model and combined to urban dynamics model to estimate NO2 level, the maximum number of population, industry structure, housing and maximum amount of land use for industrial, housing, and green space that can sustain desirable NO2 level. Metropolitan area was divided into 16 areas and the model was applied to each area. Since NO2 is flowing in and out from each area, model was built to allow this transboundering nature of air pollutants. Based on the model estimation, several policy implications for a sustainable land use pattern was discussed.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.476-480
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• 2002

The theory of constraints (TOC) has become a valuable system in modern operations management. Using the ideas and methods of the TOC, companies can achieve a large reduction of work-in-process and finished-goods inventories, significant improvement in scheduling performance, and substantial earnings increase. The purpose of this paper is to calculate the optimal size of the time buffer which is used to accommodate disruptions in production processes and provide maximum productivity of capacity constrained resources. After the problem formulation in terms of single server queueing model, we observed the system behavior by sensitivity analyses.

• Journal of Satellite, Information and Communications
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• v.12 no.2
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• pp.51-55
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• 2017

This paper aims to maximize the energy harvesting rate and channel capacity in RF-energy harvesting networks (RF-EHNs) under the constraints of maximum transmit power and minimum quality of service (QoS) in terms of rate capacity for each user. We study a multi-user RF-EHN with frequency division multiple access (FDMA) in a Rayleigh channel. An access point (AP) simultaneously transmitting wireless information and power in the RF-EHN serves a subset of active users which have a power-splitting antenna. To gauge the network performance, we define energy efficiency (EE) and propose an optimization solution for maximizing EE with Lagrangian dual decomposition theory. In simulation results, we confirm that the EE is effectively maximized by the proposed solution with satisfying the given constraints.

• Geomechanics and Engineering
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• v.20 no.6
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• pp.527-536
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• 2020

The paper represents an optimization algorithm for reinforced concrete retaining wall design. The proposed method, called Rao-3 optimization algorithm, is a recently developed algorithm. The total weight of the steel and concrete, which are used for constructing the retaining wall, were chosen as the objective function. Building Code Requirements for Structural Concrete (ACI 318-05) and Rankine's theory for lateral earth pressure were considered for structural and geotechnical design, respectively. Number of the design variables are 12. Eight of those express the geometrical dimensions of the wall and four of those express the steel reinforcement of the wall. The safety against overturning, sliding and bearing capacity failure were regarded as the geotechnical constraints. The safety against bending and shear failure, minimum and maximum areas of reinforcement, development lengths of steel reinforcement were regarded as structural constraints. The performance of proposed algorithm was evaluated with two design examples.

• IE interfaces
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• v.16 no.spc
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• pp.93-98
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• 2003

This paper addresses an AGV dispatching problem in semiconductor clean-room bays where AGVs move cassettes of wafers between machines or machines and a central buffer. Since each machine in a bay has a local buffer of limited capacity, material flow should be controlled in a careful way to maintain high system performance. It is regarded that two most important performance measures in a semiconductor bay are throughput rate and lead-time. The throughput rate is determined by a bottleneck resource and the lead-time depends on smooth material flow in the system. This paper presents an AGV dispatching procedure based on the concept of theory of constraints (TOC), by which dispatching decisions are made to utilize the bottleneck resource at the maximum level and to smooth the flow of material. The new dispatching procedure is compared with existing dispatching rules through simulation experiments.

• Structural Engineering and Mechanics
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• v.57 no.4
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• pp.763-783
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• 2016

A methodology based on Teaching Learning-Based Optimization (TLBO) algorithm is proposed for optimum design of reinforced concrete retaining walls. The objective function is to minimize total material cost including concrete and steel per unit length of the retaining walls. The requirements of the American Concrete Institute (ACI 318-05-Building code requirements for structural concrete) are considered for reinforced concrete (RC) design. During the optimization process, totally twenty-nine design constraints composed from stability, flexural moment capacity, shear strength capacity and RC design requirements such as minimum and maximum reinforcement ratio, development length of reinforcement are checked. Comparing to other nature-inspired algorithm, TLBO is a simple algorithm without parameters entered by users and self-adjusting ranges without intervention of users. In numerical examples, a retaining wall taken from the documented researches is optimized and the several effects (backfill slope angle, internal friction angle of retaining soil and surcharge load) on the optimum results are also investigated in the study. As a conclusion, TLBO based methods are feasible.

• International Journal of Naval Architecture and Ocean Engineering
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• v.5 no.3
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• pp.454-467
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• 2013

A practical Ship Inner Shell Optimization Method (SISOM), the purpose of which is to improve the safety of the seagoing transport ship by decreasing the maximum Still Water Bending Moment (SWBM) of the hull girder under all typical loading conditions, is presented in this paper. The objective of SISOM is to make the maximum SWBM minimum, and the section areas of the inner shell are taken as optimization variables. The main requirements of the ship performances, such as cargo hold capacity, propeller and rudder immersion, bridge visibility, damage stability and prevention of pollution etc., are taken as constraints. The penalty function method is used in SISOM to change the above nonlinear constraint problem into an unconstrained one, which is then solved by applying the steepest descent method. After optimization, the optimal section area distribution of the inner shell is obtained, and the shape of inner shell is adjusted according to the optimal section area. SISOM is applied to a product oil tanker and a bulk carrier, and the maximum SWBM of the two ships is significantly decreased by changing the shape of inner shell plate slightly. The two examples prove that SISOM is highly efficient and valuable to engineering practice.

• Industrial Engineering and Management Systems
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• v.9 no.3
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• pp.227-241
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• 2010

A memory module industry's supply chain usually consists of multiple manufacturing sites and multiple distribution centers. In order to fulfill the variety of demands from downstream customers, production planners need not only to decide the order allocation among multiple manufacturing sites but also to consider memory module industrial characteristics and supply chain constraints, such as multiple material substitution relationships, capacity, and transportation lead time, fluctuation of component purchasing prices and available supply quantities of critical materials (e.g., DRAM, chip), based on human experience. In this research, a directed graph-based supply network planning (DGSNP) model is developed for memory module industry. In addition to multi-site order allocation, the DGSNP model explicitly considers production planning for each manufacturing site, and purchasing planning from each supplier. First, the research formulates the supply network's structure and constraints in a directed-graph form. Then, a proposed genetic algorithm (GA) solves the matrix form which is transformed from the directed-graph model. Finally, the final matrix, with a calculated maximum profit, can be transformed back to a directed-graph based supply network plan as a reference for planners. The results of the illustrative experiments show that the DGSNP model, compared to current memory module industry practices, determines a convincing supply network planning solution, as measured by total profit.