• IE interfaces
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• v.12 no.3
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• pp.362-373
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• 1999

Resource Constrained Dynamic Multi-Projects Scheduling (RCDMPS) is intended to schedule activities of two or more projects sequentially arriving at die shop under restricted resources. The aim of this paper is to develop a new problem solving method for RCDMPS to make an effect schedule based by constraint programming. The constraint-based scheduling method employs ILOG Solver which is C++ constraint reasoning library for solving complex resource management problems and ILOG Schedule which is a add-on library to ILOG Solver dedicated to solving scheduling problems. And this method interfaces with ILOG Views so that the result of scheduling displays with Gantt chart. The scheduling method suggested in this paper was applied to a company scheduling problem and compared with the other heuristic methods, and then it shows that the new scheduling system has more preference.

• Journal of Korean Institute of Industrial Engineers
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• v.11 no.2
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• pp.57-73
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• 1985

Group scheduling problem in a multi-stage manufacturing system is reviewed and two heuristic procedures for minimizing the makespan are developed by employing the methods of flow shop sequencing heuristics with a slight modification. The comparisons among the five heuristics, three previously reported heuristics and two heuristics suggested by this study, are made on different problem sizes. The computational results indicate that NEH-GS method gives better group schedules than the other heuristics tested, but its computation time increases rapidly as the problem size increases. On the other hand, CDS-GS method provides relatively good group schedules with less computation time compared with NEH-GS method.

• Journal of the Korean Operations Research and Management Science Society
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• v.37 no.1
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• pp.19-28
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• 2012

We consider a multi-agent scheduling problem such that each agent tries to maximize the weighted number of just-in-time jobs. Two objectives are considered : the first is to find the optimal solution for one agent with constraints on the other agents' weight functions, and the second is to find the largest set of efficient schedules of which corresponding objective vectors are different for the case with identical weights. We show that when the number of agents is fixed, the single machine case with the first objective is NP-hard in the ordinary sense, and present the polynomial- time algorithm for the two-machine flow shop case with the second objective and identical weights.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.4
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• pp.319-325
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• 2001

Recently. AGV systems are used to serve the raw material to each work stations automatically. There exists a trade-off between the adequate service supply and the number of purchased AGVs. Also, to reduce the overall production cost, the amount of inventory hold on the shop floor should be considered. In this paper, we present a heuristic technique for determining the number of AGVs which includes the net present fixed costs of each station, each purchased AGV, delivering cost, stock inventory cost, and safety stock inventory cost. Secondly, by using a genetic algorithm, the optimal number of AGVs and the optimal reorder quantity at each station are decided. Lastly, to verify then heuristic algorithm, we have done a computer simulation with different GA parameters.

• Journal of the Korea Society for Simulation
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• v.7 no.2
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• pp.45-62
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• 1998

This research is concerned with buffer management in a multi-cell FMS with an AGVS. Buffers in manufacturing systems are required to reduce blocking and starving caused by breakdowns, variability in process times, and diversity of part routing. Due to the high per unit buffer cost, which primarily consists of floor space and equipment costs, the total capacity of buffers in and FMS is very limited. Proper buffer management can provide a high system efficiency. This paper presents a buffer management model for a multi-cell FMS with an AGVS and a simulation study to compare the proposed model to a conventional buffer management model in a job shop FMS.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.52
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• pp.297-309
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• 1999

Resource Constrained Dynamic Multi-Projects Scheduling(RCDMPS) is intended to minimize the total processing time(makespan) of two or more projects sequentially arriving at the shop under restricted resources. The aim of this paper is to develop the new Tabu Search heuristic for RCDMPS to minimize makespan. We propose the insertion method to generate the neighborhood solutions in applying the Tabu Search for the RCDMPS and the diversification strategy to search the solution space diversely. The proposed diversification strategy apply the dynamic tabu list that the tabu list size is generated and renewed at each iteration by the complexity of the project, and change the proposed tabu attribute. In this paper, We use the dynamic tabu list for the diversification strategy and intensification strategy in the tabu search, and compare with other dispatching heuristic method to verify that the new heuristic method minimize the makespan of the problem.

• Journal of Intelligence and Information Systems
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• v.1 no.2
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• pp.123-137
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• 1995

Most of solution methods in scheduling attempt to generate good solutions by either developing algorithms or heuristic rules. However, scheduling problems in the real world require considering more factors such as multiple objectives, different combinations of heuristic rules due to problem characteristics. In this respect, the traditional mathematical a, pp.oach showed limited performance so that new a, pp.oaches need to be developed. Expert system is one of them. When an expert system is developed for scheduling one of the most difficult processes faced could be knowledge acquisition on scheduling heuristics. In this paper we propose a method for the acquisition of knowledge on the selection of scheduling heuristics using Dempster-Shafer Theory(DST). We also show the examples in the multi-objectives environment.

• IE interfaces
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• v.7 no.3
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• pp.171-180
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• 1994

Defined is a Multi-level Parallel Machine Flow-Shop (MPMFS) which reflects some real world manufacturing situations. Just-In-Time (JIT) philosophy is applied to the MPMFS scheduling in order to achieve lowering work-in-process inventory level as well as meeting due dates. A schedule generating simulator is developed. The latest start time of each operation is determined by a backward simulation followed by another forward simulation to analyze the schedule feasibility and actual inventory level. Reasonable schedules are available through adjusting some parameters for allowance factors such as set-up times of machines and other environmental changes. The SLAMSYSTEM under Window is employed for this processing with some input/output data handling processes devised under DOS.

• International journal of advanced smart convergence
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• v.10 no.4
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• pp.172-182
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• 2021

We look at the business model development of a fan community platform 'Weverse' from two-sided platform (TSP) to multi-sided platform (MSP) and investigate its platform business model. From the Rocket Model's theoretical perspective, the results reveal that Weverse firstly focuses on inviting artists as many as possible starting from BTS, then attracts new artists' fans naturally. For success of this TSP, it forms MSP, 'Weverse Shop' to meet two sides' relevant needs timely and filtered. In third stage of connection, various partnerships are attempted in terms of open platform strategies. For instance, by combining 'VLive' and Weverse, Naver's fan platform business is transferred to Weverse. For core transaction through direct and indirect monetization, several cobranding activities are tried. Lastly, regarding optimization, newly born Weverse being launched in the first half of 2022 is supposed to create further synergies with Naver's R&D capabilities in data, AI, and other technologies like metaverse platform 'ZEPETO' which already sells clothing items of Weverse artists.

• The Journal of the Korea Contents Association
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• v.16 no.5
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• pp.428-439
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• 2016

It becomes undeniable trends that offline shopping stores operate their own online shopping stores too. The multi-channel shopping stores like this allow consumers to have much choices to shop from either offline channel or online channel. This trend, however, also opens new research issues. Especially, we have found from literature survey that a new research model is necessary for more in-depth study of the consumer behavior analysis in the multi-channel trends like this, where those constructs such as offline trust, uncertainty, switching cost, and individual negative emotion are considered. It is noted, especially in the multi-channel environments, that uncertainty and switching cost need to be considered, and that individual tends to feel negative emotion much more. By relying on 406 valid questionnaires, we obtained empirical results such that switching cost and offline trust have a positive effect on continuance intention, and uncertainty tends to increase switching cost. Individual negative emotion also affects continuance intention significantly.