• Title/Summary/Keyword: 할당 최적화

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An Optimization Modeling Study on Coastal Patrol Killer Medium(PKM) Requirement (연안 해역 소형 함정 소요 최적화 모델링 연구)

  • Hong, Yoon-Gee;Kim, Young-In;Kim, Yang-Rae;Lee, Jung-Woo;Jang, Dong-Hak
    • Journal of the military operations research society of Korea
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    • v.36 no.2
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    • pp.25-37
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    • 2010
  • This paper deals with achieving the optimal quantity of required PKMs to cover the coastal areas divided into the proper size of sectors, and then using Set Cover Model, Clustered Model, etc. It is optimized via "Requirement Optimization Process" to allocate PKMs reasonably which is considered as conducting mission deployment sectors. This "Hybrid Proper Requirement Model" accommodating the optimization process is introduced and testified by examining a requirement problem.

Waste Load Allocation Method for Total Maximum Daily Load Program of a Polluted River (수질오염총량관리제 대상 오염심화 하천에 대한 오염부하량 할당방법)

  • Cho, Jae-Heon
    • Journal of Environmental Impact Assessment
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    • v.22 no.2
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    • pp.157-170
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    • 2013
  • 수질오염총량관리제 시행 하천에 대해서는 객관적이고 과학적 방법으로 유역내 각 지역의 오염부하량을 할당할 필요가 있다. 본 연구에서는 대도시에서 배출되는 오염부하의 영향을 크게 받는 영산강수계의 중상류부를 대상으로 오염부하량 할당 방법에 대해 검토하였다. 오염부하량 할당을 위한 수질모델링은, 수질관리에 흔히 적용되어온 QUAL2E의 최근 판인, QUAL2Kw를 이용해서 수행하였다. 모델 적용 대상 지역의 각 reach의 수질매개변수는 QUAL2Kw의 자동보정 기능을 이용해서 추정하였다. 오염부하량 할당의 최적화는 유전알고리즘(genetic algorithm)을 이용하였고, 최소부하량 삭감법(least waste load removal allocation), 일정 부하량 이상 최소부하량 삭감법(least waste load removal over a certain value), 동일삭감률 할당법(equal removal rate)의 세가지 방법을 적용하고 비교 검토하였다. 동일삭감률 할당법은 다른 방법보다 유역 전체 부하량 삭감량이 훨씬 크기 때문에 효과적이지 않았고, 이 방법을 쓰기 위해서는 부하량 삭감대상인 각 소유역과 하수처리장을 그 규모와 특성에 따라 세분화할 필요가 있다. 동일삭감률 할당법의 적용시 세가지 범주로 나누어서 삭감률을 적용하였다. 오염부하량 삭감의 효율성을 감안할 때 최소 부하량 삭감법보다 일정 부하량 이상 최소부하량 삭감법이 더 적절한 것으로 검토되었다.

Task Assignment of Multiple UAVs using MILP and GA (혼합정수 선형계획법과 유전 알고리듬을 이용한 다수 무인항공기 임무할당)

  • Choi, Hyun-Jin;Seo, Joong-Bo;Kim, You-Dan
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.38 no.5
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    • pp.427-436
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    • 2010
  • This paper deals with a task assignment problem of multiple UAVs performing multiple tasks on multiple targets. The task assignment problem of multiple UAVs is a kind of combinatorial optimization problems such as traveling salesman problem or vehicle routing problem, and it has NP-hard computational complexity. Therefore, computation time increases as the size of considered problem increases. To solve the problem efficiently, approximation methods or heuristic methods are widely used. In this study, the problem is formulated as a mixed integer linear program, and is solved by a mixed integer linear programming and a genetic algorithm, respectively. Numerical simulations for the environment of the multiple targets, multiple tasks, and obstacles were performed to analyze the optimality and efficiency of each method.

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.

A Task Prioritizing Algorithm Optimized for Task Duplication Based Processor Allocation Method (태스크 복제 기반 프로세서 할당 방법에 최적화된 태스크 우선순위 결정 알고리즘)

  • Song, In-Seong;Yoon, Wan-Oh;Lee, Chang-Ho;Choi, Sang-Bang
    • Journal of Internet Computing and Services
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    • v.12 no.6
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    • pp.1-17
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    • 2011
  • The performance of DHCS depends on the algorithm which schedules input DAG. However, as the task scheduling problem in DHCS is an NP-complete problem, heuristic approach has to be made. Task scheduling algorithm consists of task prioritizing phase and processor allocation phase, and most of studies are considering both phases together. In this paper, we focus on task prioritizing phase and propose a WPD algorithm which is optimized for task duplication based processor allocation method. For an evaluation of the proposed WPD algorithm, we combined WPD algorithm with processor allocation phase of HMPID, HCPFD, HCT algorithms, which are using task duplication based processor allocation method. The results show that WPD algorithm makes a better use of task duplication than conventional task prioritizing methods and provides 9.58% better performance than HCPFD algorithm, 1.31% than HCT algorithm.

Automated Stacking Crane Dispatching Strategy in a Container Terminal using Genetic Algorithm (유전 알고리즘을 이용한 자동화 컨테이너 터미널에서의 장치장 크레인의 작업 할당 전략)

  • Wu, Jiemin;Yang, Young-Jee;Choe, Ri;Ryu, Kwang-Ryel
    • Journal of Navigation and Port Research
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    • v.36 no.5
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    • pp.387-394
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    • 2012
  • In an automated container terminal, automated stacking cranes(ASCs) take charge of handling of containers in a block of the stacking yard. This paper proposes a multi-criteria strategy to solve the problem of job dispatching of twin ASCs which are identical to each another in size and specification. To consider terminal situation from different angles, the proposed method evaluates candidate jobs through various factors and it dispatches the best score job to a crane by doing a weighted sum of the evaluated values. In this paper, we derive the criteria for job dispatching strategy, and we propose a genetic algorithm to optimize weights for aggregating evaluated results. Experimental results are shown that it is suitable for real time terminal with lower computational cost and the strategy using various criteria improves the efficiency of the container terminal.

An Efficient and Fair Substream Allocation Method for a Distributed Video Streaming System using Multiple Substreams (다수의 부스트림을 이용한 분산 비디오 스트리밍 시스템을 위한 공정하고 효율적인 부스트림 할당 기법)

  • Park, Jae-Sung
    • The KIPS Transactions:PartC
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    • v.19C no.2
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    • pp.145-148
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    • 2012
  • In a distributed streaming system using an advanced coding scheme that encodes a video into multiple substreams, the capacity of the system depends on the amount of contribution of participating peers. Thus, an incentive mechanism for peers to contribute voluntarily is needed to increase system capacity. In addition, since peers are not only a provider but also a consumer in the system (i.e. prosumer), the overall capacity of the system must be allocated fairly among the peers while it must be allocated in a way that can maximize the net quality of experience of peers to increase system efficiency. In this paper, we propose a substream allocation method to solve the problems taking an optimization approach. Unlike the other optimization approaches, the proposed method is verified quantitatively in a simulation study that it can use the capacity of video streaming system efficiently while allocating fair amount of substreams among peers because it considers explicitly the prosumer characteristics of peers.

Optimal Weapon-Target Assignment Algorithm for Closed-In Weapon Systems Considering Variable Burst Time (가변 연속사격 시간을 고려한 근접 방어 시스템의 최적 무장 할당 알고리듬)

  • Kim, Bosoek;Lee, Chang-Hun;Tahk, Min-Jea;Kim, Da-Sol;Kim, Sang-Hyun;Lee, Hyun-Seok
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.49 no.5
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    • pp.365-372
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    • 2021
  • This paper deals with an optimal Weapon-Target Assignment (WTA) algorithm for Closed-In Weapon Systems (CIWS), considering variable burst time. In this study, the WTA problem for CIWS is formulated based on Mixed Integer Linear Programming (MILP). Unlike the previous study assuming that the burst time is fixed regardless of the engagement range, the proposed method utilizes the variable burst time based on the kill probability according to the engagement range. Thus, the proposed method can reflect a more realistic engagement situation and reduce the reaction time of CIWS against targets, compared to the existing method. In this paper, we first reformulate the existing MILP-based WTA problem to accommodate the variable burst Time. The proposed method is then validated through numerical simulations with the help of a commercial optimization tool.

A Study on the Optimized Algorithm for Incremental Attribute Propagation of Attribute Grammar (속성 문법의 점진적 속성 전파를 위한 최적화 알고리즘에 관한 연구)

  • 장재춘;안희학
    • Proceedings of the Korean Information Science Society Conference
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    • 2001.04a
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    • pp.46-48
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    • 2001
  • 속성에 할당된 새로운 조건을 통해 평가를 수행할 때 이미 산출된 부분을 재사용하기 위해서는 새로운 평가방법이 필요하다. 이 논문에서는 평가된 속성 값의 전파를 고려한 최적화 알고리즘을 제안하는 기존 속성 트리의 서브 트리와 새로운 속성 트리의 서브 트리를 비교하여 전파되는 속성 값과 노드가 일치할 경우 기존 속성 트리의 서브 트리를 새로운 속성 트리에서 사용이 가능한 최적화된 알고리즘을 제안하고 평가하였다.

Reliability Optimization for Multiple Multi-level Redundancy Allocation Problems using Genetic Algorithm (유전자 알고리듬을 활용한 혼합 다수준 리던던시 할당문제의 신뢰성 최적화)

  • Kim Ho-Gyun;Bae Chang-Ok;Yun Won-Yeong
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2006.05a
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    • pp.110-116
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    • 2006
  • 지금까지 대부분의 리던던시 할당문제(RAP: redundancy allocation problems) 관련 연구들에서는 최상위 수준에서의 시스템 리던던시보다는 최하위 수준인 부품의 리던던시를 고려하였다. 이는 최하위 수준에서의 리던던시가 최상위 수준의 리던던시보다 효과적이라고 알려진 일반적 원리 때문이었다. 최근 한 연구에서는 동일하지 않은 예비부품을 사용하여 리던던시를 실시하는 경우 직렬구조의 시스템에서도 일반적 원리와 다른 결과가 나타날 수 있음을 보이고, 시스템을 구성하는 모든 수준에서 리던던시가 가능한 다수준 리던던시 할당문제(MRAP: multi-level RAP)를 제시하였다. 그러나 MRAP는 모든 수준에서의 리던던시를 고려하지만 단지 한 수준을 선택하여 리던던시를 할 수 있다는 가정사항을 포함하고 있다. 본 연구에서는 MRAP의 이러한 가정사항을 완화하여 시스템을 구성하는 모든 수준에서 리던던시를 위한 수준을 복수로 선택 가능한 혼합 다수준 리던던시 할당문제(MMRAP: multiple MRAP)를 제시하고 모형화하며, 문제의 해법을 위한 유전자 알고리듬(GA: genetic algorithm)을 제시한다. 제시한 GA를 활용한 몇 가지 수치실험을 통해 모형이 기존의 RAP 경우보다 효과적임을 입증한다.

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