• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권10호
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• pp.3394-3408
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• 2014

Conventional mobile state (MS) and base station (BS) association based on average signal strength often results in imbalance of cell load which may require more powerful processor at BSs and degrades the perceived transmission rate of MSs. To deal with this problem, a Markov decision process (MDP) for load balancing in a multi-cell system with multi-carriers is formulated. To solve the problem, exploiting Sarsa algorithm of on-line learning type [12], ${\alpha}$-controllable load balancing algorithm is proposed. It is designed to control tradeoff between the cell load deviation of BSs and the perceived transmission rates of MSs. We also propose an ${\varepsilon}$-differential soft greedy policy for on-line learning which is proven to be asymptotically convergent to the optimal greedy policy under some condition. Simulation results verify that the ${\alpha}$-controllable load balancing algorithm controls the behavior of the algorithm depending on the choice of ${\alpha}$. It is shown to be very efficient in balancing cell loads of BSs with low ${\alpha}$.

• 산업공학
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• 제11권3호
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• pp.155-166
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• 1998

The productivity and quality are most challenging problems facing all companies. This paper presents a process improvement of the SMPS(switching mode power supply) assembly line through elimination of unnecessary operations, a proper factory layout, motion study, and line balancing techniques. The proposed assembly line increases the productivity by 23.9%, and decrease the proportion of nonconforming items by 48.9%.

• 한국경영과학회지
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• 제37권3호
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• pp.39-55
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• 2012

This paper presents an endosymbiotic evolutionary algorithm (EEA) to solve both problems of line balancing and model sequencing in a mixed-model two-sided assembly line (MMtAL) simultaneously. It is important to have a proper balancing and model sequencing for an efficient operation of MMtAL. EEA imitates the natural evolution process of endosymbionts, which is an extension of existing symbiotic evolutionary algorithms. It provides a proper balance between parallel search with the separated individuals representing partial solutions and integrated search with endosymbionts representing entire solutions. The strategy of localized coevolution and the concept of steady-state genetic algorithms are used to improve the search efficiency. The experimental results reveal that EEA is better than two compared symbiotic evolutionary algorithms as well as a traditional genetic algorithm in solution quality.

• 지능정보연구
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• 제2권1호
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• pp.93-107
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• 1996

A flexible flow line(FFL) consists of several groups of identical machines. All work-orders flow along the same path through successive machine groups. Thus, we emphasized the balancing of workloads between machine groups in order to maximize total productivity. On the other hand, many different types of work-orders, in varying batch or lot sizes, are produced simultaneously. The mix of work-orders, their lot sizes, and the sequence in which they are produced affect the amount of workload. However, the work-orders and their lot sizes are prefixed and cannot be changed. Because of these reasons, we have developed an optimal route selection model using heuristic search and Min-Max algorithm for balancing the workload between machine groups in the FFL.

• 대한안전경영과학회지
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• 제5권4호
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• pp.187-194
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• 2003

The purpose of a man-machine chart is improved utilization of a man or a machine. Improved utilization can mean less idle time, rebalanced idle time, or less idle time of an excessive component. In this study we improved the productivity of the assembly line in the electronics company using man-machine chart. The results are applicable for improving the effectiveness of line balancing problems in the electronics industry.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.1237-1240
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• 1996

This paper proposes a heuristic algorithm for performing the line balancing of PCB assembly fine including multiple surface mounters efficiently. We consider a PCB assembly line including the multiple surface mounters arranged serially as a target system. We assume that the number of heads of surface mounters can be changed. Also, the conveyor is assumed to move at a constant speed and have no buffer. Considering the minimum number of machines required for the desired production rate is a discrete nonincreasing function which is inversely proportional to the cycle time, we propose an optimization algorithm for line balancing by using the binary search method. Also we propose an head-changing algorithm. The algorithms are validated through the computer simulation.

• 대한안전경영과학회지
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• 제19권1호
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• pp.203-210
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• 2017

Companies are pursuing the management of small quantity batch production or JIT(Just-in-time) system for improving the delivery response and LOB(Line Balancing) in order to satisfy consumers' increasing demands in the current global economic recession. And in order to improve the growth of production for reducing manufacturing cost, improvements of the Load Balancing have become an important reformation factor. Thus this paper is aimed at warehouse which procures materials on the assembly line in procurement logistics of automotive logistics and proceed with research on heuristic algorithm development which can increase the Load Balancing of workers. As a result of this study, when applied the primary target value, it was verified that the whole workers decreased from 28 to 24. Furthermore, when specified the secondary target value and applied algorithm once more, it was verified that the Load Balance Ratio was improved from 44.96% to 91.7%.

• 대한기계학회논문집
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• 제18권2호
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• pp.339-350
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• 1994

This paper presents a method for automatic generation of line balanced assembly sequences based on disassemblability and proposes a method of evaluating an assembly work time using neural networks. Since a line balancing problem in flexible assembly system requires a sophisticated planning method, reasoning about line balanced assembly sequences is an important field of concern for planning assembly lay-out. For the efficient inference of line balanced assembly sequences, many works have been reported on how to evaluate an assembly work time at each work station. However, most of them have some limitations in that they use cumbersome user query or approximated assembly work time data without considering assembly conditions. To overcome such criticism, this paper proposes a new approach to mathematically verify assembly conditions based on disassemblability. Based upon the results, we present a method of evaluating assembly work time using neural networks. The proposed method provides an effective means of solving the line balancing problem and gives a design guidance of planning assembly lay-out in flexible assembly application. An example study is given to illustrate the concepts and procedure of the proposed scheme.

• 한국소음진동공학회논문집
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• 제15권11호
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• pp.1268-1275
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• 2005

Vibration in Engine module could be reduced by introducing a balance shaft module which has one or more unbalanced rotors. Since the unbalanced rotor is installed in an opposite direction of the free force or unbalance moment by engine component, the unexpected vibration could be decreased kinematically. The essential equation of the unbalanced rotor was Presented for two cases, 3 in-line and 4 in-line cylinder engine type, And the efficiency of the balance shaft is investigated by the vehicle testing that is focused on measuring the reduced vibration level when adapting a balancing module. With the signal processing of measured signals, some important issues on design the balancing shaft could be derived and the overall design process is explained in the final part including the peripheral component, i.e. housing and bush.

• 한국경영과학회지
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• 제34권2호
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• pp.101-111
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• 2009

This paper considers two-sided assembly line balancing with preemptive multiple goals. In the problem, three goals are taken into account in the following priority order : minimizing the number of mated-stations, achieving the goal level of workload smoothness, and maximizing the work relatedness. An evolutionary algorithm is used to solve the multiple goal problems. A new structure is presented in the algorithm, which is helpful to searching the solution satisfying the goals in the order of the priority. The proper evolutionary components such as encoding and decoding method, evaluation scheme, and genetic operators, which are specific to the problem being solved, are designed in order to improve the algorithm's performance. The computational results show that the proposed algorithm is premising in the solution quality.