• Title/Summary/Keyword: Storage Space Allocation

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Parallel reservoirs system operation using NYC-Space Allocation-Rule (NYC-Space Allocation Rule을 이용한 병렬저수지 연계운영)

  • Park Ki-Bum;Lee Soon-Tak
    • Journal of Environmental Science International
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    • v.14 no.6
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    • pp.533-542
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    • 2005
  • In this study, an optimization technique was developed from the application of Allocation Rule. Average Allocation coefficients of the Andong and Imha dam compare constant water supply condition with vary water supply condition that are above the contribute ratio $67\%\~50\%$ the Andong dam in Rule(A)-Rule(C). In the Refill Season, Andong dam water supply contribution is higher than Imha dam at the Control point water supply. In the Allocation analysis results, Rule(A) is calculated storage ratio because Andong dam contribute to Control point larger than Imha dam which Andong dam storage is larger than Imha dam storage. Rule(B) calculated sum of the storage and inflow ratio for Andong dam and Imha dam, as Andong dam contribution is higher than Imha dam. Rule(C) calculated that sum of storage, inflow and water supply is divided average storage ratio, as the best results of the Allocation coefficients and water supply capacity. The results of storage analysis is larger vary water supply condition than constant water supply condition and the results of water supply analysis is larger vary water supply condition than constant water supply condition. Water supply deficit is decrease $30\%$ for vary water supply condition.

Allocating Storage Spaces for Temporary Inventories Considering Handling, Transportation, and Storage Capacities (취급, 수송 및 저장능력을 고려한 임시 재고의 저장 공간 할당)

  • Won Seung-Hwan;Kim Kap-Hwan
    • Journal of the Korean Operations Research and Management Science Society
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    • v.31 no.3
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    • pp.11-25
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    • 2006
  • Space may be a scarce resource in manufacturing shops, warehouses, freight terminals, and container terminals. This Paper discusses how to locate temporary storage Inventories In limited storage areas. A typical inventory is delivered from the location of the preceding process to the storage area and stored In the storage area during the certain period of time. And it may be relocated from the storage position to another. Finally. it is delivered from the final storage area to the location of the next process. Because this logistic process for an inventory requires handling activities, transportation activities, and storage spaces, the limitation in capacities of handling equipment, transportation equipment, and storage space must be considered when allocating spaces to the inventory. This problem Is modeled as a multicommodity minimal cost flow problem. And a heuristic algorithm for the Problem is proposed. Numerical experiments are presented to validate the mathematical model and the heuristic algorithm.

Dynamic storage management for mobile platform based on the characteristics of mobile applications (응용프로그램 특성을 고려한 모바일 플랫폼의 동적 메모리 관리기법)

  • You, Yong-Duck;Park, Sang-Hyun;Choi, Hoon
    • The KIPS Transactions:PartA
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    • v.13A no.7 s.104
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    • pp.561-572
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    • 2006
  • Performance of the mobile devices greatly depends on the efficient resource management because they are usually resource-restricted. In particular, the dynamic storage allocation algorithms very important part of the mobile device's operating system and OS-like software platform. The existing dynamic storage allocation algorithms did not consider application's execution style and the type, life-time, and characteristics of memory objects that the application uses. Those algorithms, as a result, could not manage memory efficiently Therefore, this Paper analyzes the mobile application's execution characteristics and proposes anew dynamic storage allocation algorithm which saves the memory space and improves mobile application's execution speed. The test result shows that the proposed algorithm works 6.5 times faster than the linked-list algorithm[11], 2.5 times faster better than the Doug. Lea's algorithm[12] and 10.5 times faster than the Brent algorithm[14].

Particle Swarm Optimization for Snowplow Route Allocation and Location of Snow Control Material Storage (Particle Swarm Optimization을 이용한 제설차량 작업구간 할당 및 제설전진기지 위치 최적화)

  • Park, U-Yeol;Kim, Geun-Young;Kim, Sun-Young;Kim, Hee-Jae
    • Journal of the Korea Institute of Building Construction
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    • v.17 no.4
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    • pp.369-375
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    • 2017
  • This study suggests PSO(Particle Swarm Optimization) algorithm that optimizes the snowplow route allocation and the location of the snow control material storage to improve the efficiency in snow removal works. The modified PSO algorithm for improving the search capacity is proposed, and this study suggests the solution representation, the parameter setting, and the fitness function for the given optimization problems. Computational experiments in real-world case are carried out to justify the proposed method and compared with the traditional PSO algorithms. The results show that the proposed algorithms can find the better solution than the traditional PSO algorithms by searching for the wider solution space without falling into the local optima. The finding of this study is efficiently employed to solve the optimization of the snowplow route allocation by minimizing the workload of each snowplow to search the location of the snow control material storage as well.

컨테이너 터미널에서의 장치장 운용 계획에 관한 연구

  • Jeon, Su-Min;Kim, Gap-Hwan;Kim, Jae-Jung;Ryu, Gwang-Ryeol;Park, Nam-Gyu;Choe, Hyeong-Rim
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2005.11a
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    • pp.442-450
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    • 2005
  • One of the important tactical problems for the efficient operation of container terminals is to determine the usage of storage space There are two different strategies for stacking containers; mixing strategy. in which outbound containers and inbound containers are mixed in the same block. and segregating strategy, in which outbound containers and inbound containers are stacked in blocks different from each other. The performance of space allocation strategies also depends on the types of handling equipment in the yard and the number of handling equipment allocated to each block. A simulation model is developed considering various handling characteristics of yard cranes. Performances of various space and equipment allocation strategies are evaluated by using the simulation model.

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An efficient Storage Reclamation Algorithm for RISC Parallel Processing (RISC 병렬 처리를 위한 기억공간의 효율적인 활용 알고리즘)

  • 이철원;임인칠
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.28B no.9
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    • pp.703-711
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    • 1991
  • In this paper, an efficient storage reclamation algorithm for RISC parallel processing in the object orented programming environments is presented. The memory management for the dynamic memory allocation and the frequent memory access in object oriented programming is the main factor that decreases RISC parallel processing performance. The proposed algorithm can be efficiently allocated the memory space of RISCy computer which is required the frequent memory access, so it can be increased RISC parallel processing performance. The proposed algorithm is verified the efficiency by implementing C language on SUN SPARC(4.3 BSD UNIX).

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A Heuristic Algorithm of an Efficient Berth Allocation for a Public Container Terminal (공공 컨테이너 터미널의 효율적인 선석할당을 위한 발견적 알고리즘 개발에 관한 연구)

  • Keum, J.S.
    • Journal of Korean Port Research
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    • v.11 no.2
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    • pp.191-202
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    • 1997
  • As the suitability of berth allocation will ultimately have a significant influence on the performance of a berth, a great deal of attention should be given to berth allocation. Generally, a berth allocation problem has conflicting factors between servers and users. In addition, there is uncertainty in great extent caused by various factors such as departure delay, inclement weather on route, poor handling equipment, a lack of storage space, and other factors contribute to the uncertainty of arrival and berthing time. Thus, it is necessary to establish berth allocation planning which reflects the positions of interested parties and the ambiguity of parameters. For this, a berth allocation problem is formulated by fuzzy 0-1 integer programming introducing the concept of maximum Position Shift(MPS). But, the above approach has limitations in terms of computational time and computer memory when the size of problem is increased. It also has limitations with respect to the integration of other sub-systems such as ship planning system and yard planning system. For solving such problem, this paper focuses particularly on developing an efficient heuristic algorithm as a new technique of getting an effective solution. And also the suggested algorithm is verified through the illustrative examples and empirical appalicaton to BCTOC.

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Evaluation Models for the Container Handling Times of the Automated Transfer Crane in Container Terminals (컨테이너 터미널에서 자동화된 트랜스퍼 크레인의 컨테이너 취급시간을 위한 평가모형)

  • Kim, Ki-Young
    • IE interfaces
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    • v.19 no.3
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    • pp.214-224
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    • 2006
  • The container handling times of automated transfer cranes(ATCs) significantly affect the productivity of container terminals. In this paper, evaluation models for the container handling times of ATCs are suggested for import container blocks with different transfer point configurations. Firstly, evaluation models for various motion times of stacking and retrieving operations of ATC are suggested for two basic alternatives of import container blocks. In addition, in considering the space allocation, evaluation methods for the container handling times of ATC are suggested. Finally, the container handling times for each case are compared with each other in order to analyze how the block shape and the transfer point locations affect the container handling times of ATC.

A Study On Optimized Design of Decision Support Systems for Container Terminal Operations (컨테이너 터미널 운영을 위한 의사결정시스템 설계의 최적화에 관한 연구)

  • Hong, Dong-Hee;Chung, Tae-Choong
    • The KIPS Transactions:PartA
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    • v.10A no.5
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    • pp.519-528
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    • 2003
  • Container terminals need decisions in the course of daily-24 hour and 365 day - operations, and all these decisions are inter-related. The ultimate goal of Decision Support System is to minimize ship loading/unloading time, resources used to handle the workload, and congestion on the roads inside the terminal. It is also to make the best possible use of the storage space available. Therefore, the necessity of decision support tools are emphasized to enhance the operational efficiency of container shipping terminals more, because of limits and complexity of these decisions. So, in thia paper, we draw evaluation items for Decision Support Systems and suggest optimization strategy of evaluation items which have the greatest influence on Decision Support system, that is, yard stacking allocation, RTGC deployment among blocks, and YT allocation to QCs. We also estimate the efficiency of Decision Support System design by simulation using G2 language, comparing ship loading/unloading time.

Pricing the Storage of Inbound Containers with a Discrete Probability Distribution of Retrieval Times

  • Kim, Ki-Young;Kim, Kap-Hwan
    • Industrial Engineering and Management Systems
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    • v.9 no.2
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    • pp.165-177
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    • 2010
  • This paper discusses a method for pricing the storage of inbound containers in a container yard. The pricing structure is characterized by a free-time-limit and a storage price for the storage time that extends beyond the free-time-limit. A cost model is developed from the viewpoint of a public terminal operator as well as a private terminal operator. Unlike a previous study on this issue, this study assumes that the retrieval times follow a discrete probability distribution, which is more realistic than the previous study. A solution procedure is suggested and illustrated by using numerical examples.