• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.5
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• pp.151-158
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• 2023

The researchers entirely focused on meta-heuristic method for generalized assignment problem(GAP) that is known as NP-hard problem because of the optimal solution within polynomial time algorithm is unknown yet. On the other hand, this paper proposes a heuristic greedy algorithm with rules for finding solutions. Firstly, this paper reduces the weight matrix of original data to w_ij ≤ b_i/l in order to n jobs(items) pack m machines(bins) with l = n/m. The maximum profit of each job was assigned to the machine for the reduced data. Secondly, the allocation was adjusted so that the sum of the weights assigned to each machine did not exceed the machine capacity. Finally, the k-opt swap optimization was performed to maximize the profit. The proposed algorithm is applied to 50 benchmarking data, and the best known solution for about 1/3 data is to solve the problem. The remaining 2/3 data showed comparable results to metaheuristic techniques. Therefore, the proposed algorithm shows the possibility that rules for finding solutions in polynomial time exist for GAP. Experiments demonstrate that it can be a P-problem from an NP-hard.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2817-2834
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• 2016

The existing reversible data hiding methods for block truncation coding (BTC) compressed images often utilize difference expansion or histogram shifting technique for data embedment. Although these methods effectively embed data into the compressed codes, the embedding operations may swap the numerical order of the higher and lower quantization levels. Since the numerical order of these two quantization levels can be exploited to carry additional data without destroying the quality of decoded image, the existing methods cannot take the advantages of this property to embed data more efficiently. In this paper, we embed data by shifting the higher and lower quantization levels in opposite direction. Because the embedment does not change numerical order of quantization levels, we exploit this property to carry additional data without further reducing the image quality. The proposed method performs no-distortion embedding if the payload is small, and performs reversible data embedding for large payload. The experimental results show that the proposed method offers better embedding performance over prior works in terms of payload and image quality.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.2
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• pp.8-17
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• 2005

This paper dealt with a kind of heterogeneous vehicle routing problem with known demand and time deadline of customers. The customers are supposed to have one of tight deadline and loose deadline. The demand of customers with tight deadline must be fulfilled in the deadline. However, the late delivery is allowed to customers with loose deadline. That is, the paper suggests a model to minimize total acquisition cost, total travel distance and total violation time for a fleet size and mix vehicle routing problem with time deadline, and proposes a heuristic algorithm for the model. The proposed algorithm consists of two phases, i.e. generation of an initial solution and improvement of the current solution. An initial solution is generated based on a modified insertion heuristic and iterative Improvement procedure is accomplished using neighborhood generation methods such as swap and reallocation. The proposed algorithm is evaluated using a well known numerical example.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.187-190
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• 2003

Many manufacturing companies consider the integrated and concurrent scheduling because they need the global optimization technology that could manufacture various products more responsive to customer needs. In this paper, we propose an advanced scheduling model to generate the schedules considering resource constraints and precedence constraints in make-to-order (MTO) manufacturing environments. Precedence of work- in-process(WIP) and resources constraints have recently emerged as one of the main constraints in advanced scheduling problems. The advanced scheduling problems is formulated as a multiobjective mathematical model for generating operation schedules which are obeyed resources constraints, alternative workstations of operations and the precedence constraints of WIP in MTO manufacturing. For effectively solving the advanced scheduling problem, the multi-objective hybrid genetic algorithm (m-hGA) is proposed in this paper. The m-hGA is to minimize the makespan, total flow time of order, and maximum tardiness for each order, simultaneously. The m-hGA approach with local search-based mutation through swap mutation is developed to solve the advanced scheduling problem. Numerical example is tested and presented for advanced scheduling problems with various orders to describe the performance of the proposed m-hGA.

• Korean Journal of Veterinary Research
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• v.41 no.4
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• pp.529-533
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• 2001

The infectivity of an isolate of avian pneumovirus (APV) from turkeys to Balb/c mice was investigated to examine the transmission possibility to mammals. Three different age groups (3, 5 and 7 weeks old) were exposed by oculonasal route with a cell cultured APV of turkey origin. No clinical signs were observed from both APV-inoculated and commingled mice. However, all the tissue samples including blood from mice in the APV-inoculated group were positive for APV by polymerase chain reaction (PCR) up to 6 days postinoculation. At 14 days postinoculation, APV was not detected from blood samples by PCR, but sera showed the presence of APV-specific antibodies. In commingled mice, APV was detected from lung and rectal swap samples by PCR. These results suggest that an APV isolate from turkey could be transmitted to mice by direct contact or other ways.

• IE interfaces
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• v.13 no.3
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• pp.471-478
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• 2000

One of the most important problems encountered by parcel transportation firms or LTL (Less-than-truckload) firms is the planning of daily linehaul operations. The transportation firm's goal is to determine the most efficient way to move all freight from its originating terminal to its destination terminal after each shipment is picked up from the shipping dock. The purpose of this study is to design a transportation system and develop an efficient scheduling algorithm for linehaul operations carrying small amount of shipment. This paper presents three approaches for efficient linehaul operations. The first approach examines drivers using the roundtrips which start from a terminal, visit several terminals, and return to the starting terminal. The second approach uses a freight assembly center where drivers take freight for a number of destination terminals which they then swap for freight for their starting terminal. The third approach is similar to the second approach in that it uses a transshipment point like a freight assembly terminal for shipment, but it has several transshipment points since each shipment may have a different transshipment point. In this study, we developed a mathematical formulation and algorithm for each approach. The experimental results using data of a LTL firm show that the third approach is more efficient than the other two. Mileage and overnight stays of the third approach are reduced by 10% and 30%, respectively.

• Proceedings of the KIPE Conference
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• 2011.07a
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• pp.304-305
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• 2011

정보화 사회로 진입함에 따라 전자화 된 정보의 저장 및 관리는 매우 중요한 사안으로 부각되고 있으며 모든 통신기기 및 전산시스템은 365일 가동이 보장되어야 하므로 여러 대의 전원을 병렬 운전하여 신뢰성을 높이고 용량을 증대시키는 방안이 연구되고 있다. 특히, 신뢰성이 요구되는 분야에서는 리던던시(Redundancy) 개념이 중요하게 되어 병렬 운전의 도입이 확산 되고 있다. 현재 새로운 전력 구조는 절연된 컨버터의 평균 전력량을 다운시켜 다수의 전력변환기를 병렬운전 시키는 방향으로 변하고 있으며, 이는 전력변환기의 신뢰성을 증가시키고 예비기기에 대한 부담을 감소시키는 큰 장점을 갖고 있다. 최근에는 이더넷 라이터를 이용하여 부하분담(Load Sharing) 및 핫스왑(Hot-swap)기능을 DC/DC 컨버터에 내장하고 있는 추세이다. 본 연구에서는 7[kW]급 지능형 DC 모듈전원 제어기술 개발에 초점을 두고 최적의 부하분담을 갖는 고성능 전류 제어 알고리즘을 소개하고자 한다.

• IE interfaces
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• v.23 no.2
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• pp.147-155
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• 2010

Reliability allocation is defined as a problem of determination of the reliability for subsystems and components to achieve target system reliability. The determination of both optimal component reliability and the number of component redundancy allowing mixed components to maximize the system reliability under resource constraints is called reliability-redundancy allocation problem(RAP). The main objective of this study is to suggest a mathematical programming model and a hybrid parallel genetic algorithm(HPGA) for reliability-redundancy allocation problem that decides both optimal component reliability and the number of component redundancy to maximize the system reliability under cost and weight constraints. The global optimal solutions of each example are obtained by using CPLEX 11.1. The component structure, reliability, cost, and weight were computed by using HPGA and compared the results of existing metaheuristic such as Genetic Algoritm(GA), Tabu Search(TS), Ant Colony Optimization(ACO), Immune Algorithm(IA) and also evaluated performance of HPGA. The result of suggested algorithm gives the same or better solutions when compared with existing algorithms, because the suggested algorithm could paratactically evolved by operating several sub-populations and improve solution through swap, 2-opt, and interchange processes. In order to calculate the improvement of reliability for existing studies and suggested algorithm, a maximum possible improvement(MPI) was applied in this study.

• Journal of Computing Science and Engineering
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• v.8 no.3
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• pp.157-172
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• 2014

Contemporary embedded systems often use NAND flash memory instead of hard disks as their swap space of virtual memory. Since the read/write characteristics of NAND flash memory are very different from those of hard disks, an efficient page replacement algorithm is needed for this environment. Our analysis shows that temporal locality is dominant in virtual memory references but that is not the case for write references, when the read and write references are monitored separately. Based on this observation, we present a new page replacement algorithm that uses different strategies for read and write operations in predicting the re-reference likelihood of pages. For read operations, only temporal locality is used; but for write operations, both write frequency and temporal locality are used. The algorithm logically partitions the memory space into read and write areas to keep track of their reference patterns precisely, and then dynamically adjusts their size based on their reference patterns and I/O costs. Without requiring any external parameter to tune, the proposed algorithm outperforms CLOCK, CAR, and CFLRU by 20%-66%. It also supports optimized implementations for virtual memory systems.

• Journal of the Korean Mathematical Society
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• v.57 no.5
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• pp.1167-1186
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• 2020

This paper considers the case of pricing discretely-sampled variance swaps under the class of equity-interest rate hybridization. Our modeling framework consists of the equity which follows the dynamics of the Heston stochastic volatility model, and the stochastic interest rate is driven by the Cox-Ingersoll-Ross (CIR) process with full correlation structure imposed among the state variables. This full correlation structure possesses the limitation to have fully analytical pricing formula for hybrid models of variance swaps, due to the non-affinity property embedded in the model itself. We address this issue by obtaining an efficient semi-closed form pricing formula of variance swaps for an approximation of the hybrid model via the derivation of characteristic functions. Subsequently, we implement numerical experiments to evaluate the accuracy of our pricing formula. Our findings confirm that the impact of the correlation between the underlying and the interest rate is significant for pricing discretely-sampled variance swaps.