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A Novel Air Indexing Scheme forWindow Query in Non-Flat Wireless Spatial Data Broadcast
임석진,윤희용,최진탁,Jinsong Ouyang 한국통신학회 2011 Journal of communications and networks Vol.13 No.4
Various air indexing and data scheduling schemes for wireless broadcast of spatial data have been developed for energy efficient query processing. The existing schemes are not effective when the clients’ data access patterns are skewed to some items. It is because the schemes are based on flat broadcast that does not take the popularity of the data items into consideration. In this paper, thus, we propose a data scheduling scheme letting the pop-ular items appear more frequently on the channel, and grid-based distributed index for non-flat broadcast (GDIN) for window query processing. The proposed GDIN allows quick and energy efficient processing of window query, matching the clients’ linear channel access pattern and letting the clients access only the queried data items. The simulation results show that the proposed GDIN signif-icantly outperforms the existing schemes in terms of access time,tuning time, and energy efficiency
시뮬레이션과 유전알고리즘을 이용한 생산-분배스케쥴에 대한 연구
임석진 한국경영공학회 2007 한국경영공학회지 Vol.12 No.3
The purpose of this paper is to generate realistic production scheduling in the supply chain. The scheduling model determines the best schedule using operation sequences and machine and strongly satisfies the due dates of customer order. The model is NP-hard in the strong sense in general. And, real system can be happened various kinds of uncertain factors such as queuing, breakdowns and repairing time in the manufacturing supply chain. To solve this problem a hybrid approach involving a genetic algorithm(GA) and computer simulation is proposed. Such an approach has not been treated in the literature. The GA is employed in order to quickly generate feasible production and delivery schedules. The simulation is used to minimize the maximum completion time for the production and delivery plan with last sequence with fixed schedules from the GA model. More realistic production and delivery schedules with an optimal completion time by performing the iterative hybrid approach can be obtained. This proposed approach generates: (1) selecting the best machine for each operation, (2) deciding the sequence of operation to product and route to deliver, (3) minimizing the makespan for each order. The results of computational experiments for a simple example of the supply chain are given and discussed to validate the proposed approach. It has been shown that the hybrid approach is powerful for complex production-delivery scheduling in the manufacturing supply chain.
임석진,모창우 대한안전경영과학회 2015 대한안전경영과학회지 Vol.17 No.3
The competition between companies for prior occupation of the market is becoming fierce. In this highly competitive situation, it is important for companies to differentiate themselves if they are going to have a chance at success. And the competition to create the best solution method possible is higher than ever. Increased competition is forcing companies to lower costs and improve efficiency. A supply chain management(SCM) has become one of the most important solution methods of competitive advantage. This study has developed a simulator for the supply chain network problem. The simulator is designed to simulate the conditions of an actual supply chain network considering uncertainties. The simulator developed using commercial simulation tool ARENA and the results of computational experiments for a simple example were given and discussed to validate the developed simulator. Further research is needed, but using the simulator could become a useful tool for decision making in the supply chain network area.
Genetic algorithm을 이용한 supply chain network에서의 최적생산 분배에 관한 연구
임석진,정석재,김경섭,박면웅 한국경영과학회 2003 한국경영과학회 학술대회논문집 Vol.- No.1(1)
Recently, a multi facility, multi product and multi period industrial problem has been widely investigated in Supply Chain Management (SCM). One of the key issues in the current SCM research area involves reducing both production and distribution costs. The purpose of this study is to determine the optimum quantity of production and transportation with minimum cost in the supply chain network. We have presented a mathematical model that deals with real world factors and constraints. Considering the complexity of solving such model, we have applied the genetic algorithm approach for solving this model computational experiments using a commercial genetic algorithm based optimizer. The results show that the real size problems we encountered can be solved in reasonable time.
공급사슬네트워크에서 시뮬레이션과 유전알고리즘을 이용한 통합생산분배계획에 대한 연구
임석진 대한안전경영과학회 2020 대한안전경영과학회지 Vol.22 No.4
Many of companies have made significant improvements for globalization and competitive business environment The supply chain management has received many attentions in the area of that business environment. The purpose of this study is to generate realistic production and distribution planning in the supply chain network. The planning model determines the best schedule using operation sequences and routing to deliver. To solve the problem a hybrid approach involving a genetic algorithm (GA) and computer simulation is proposed. This proposed approach is for: (1) selecting the best machine for each operation, (2) deciding the sequence of operation to product and route to deliver, and (3) minimizing the completion time for each order. This study developed mathematical model for production, distribution, production-distribution and proposed GA-Simulation solution procedure. The results of computational experiments for a simple example of the supply chain network are given and discussed to validate the proposed approach. It has been shown that the hybrid approach is powerful for complex production and distribution planning in the manufacturing supply chain network. The proposed approach can be used to generate realistic production and distribution planning considering stochastic natures in the actual supply chain and support decision making for companies.