• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2010년도 춘계학술발표대회
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• pp.314-317
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• 2010

본 연구는 차량 경로 스케줄링 문제(VRSPTW, the Vehicle Routing and Scheduling Problem with Time Window)를 해결하기 위하여, 멀티 비용 함수(Multi Cost Function)를 갖는 개미 군집 최적화(Ant Colony Optimization)을 이용한 휴리스틱을 제안하였다. 멀티 비용 함수는 각 개미가 다음 고객 노드로 이동하기 위해 비용을 평가할 때 거리, 요구량, 각도, 시간제약에 대해 서로 다른 가중치를 반영하여 우수한 초기 경로를 구할 수 있도록 한다. 본 연구의 실험결과에서 제안된 휴리스틱이 Solomon I1 휴리스틱과 기회시간이 반영된 하이브리드 휴리스틱보다 효율적으로 최근사 해를 얻을 수 있음을 보였다.

• 한국경영과학회지
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• 제38권2호
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• pp.141-157
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• 2013

In this paper, we consider the minimization of the total weighted earliness-tardiness penalty of jobs, regarding the partial precedences between jobs. We present an optimal scheduling algorithm in O(n(n+m log m)) where n is the number of jobs and m is the number of partial precedences. In the algorithm, the optimal schedule is constructed iteratively by considering each group of contiguous jobs as a block that is represented by a tree.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.197-198
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• 2008

In this paper, we study an opportunistic scheduling scheme for the OFDMA system with streaming services. The service is modeled by using the appropriate utility function. We formulate a stochastic optimization problem that aims at maximizing network utility while satisfying the QoS requirement of each user. The problem is solved by using the dual approach and the stochastic sub-gradient algorithm.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 추계학술대회 논문집 전력기술부문
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• pp.447-449
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• 2003

In competitive electricity markets, maintenance schedule is submitted by Genco's and Transco's, and coordinated by ISO with the adequacy criterion. This paper presents an alternative coordination procedure by ISO on the maintenance schedule.

• Journal of Communications and Networks
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• 제14권5호
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• pp.554-565
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• 2012

In this paper, we study a cross-layer and end-to-end optimization problem for the integrated wireless and wireline network that consists of one wireline core network and multiple wireless access networks. We consider joint end-to-end flow control/distribution at the transport and network layers and opportunistic scheduling at the data link and physical layers. We formulate a single stochastic optimization problem and solve it by using a dual approach and a stochastic sub-gradient algorithm. The developed algorithm can be implemented in a distributed way, vertically among communication layers and horizontally among all entities in the network, clearly showing what should be done at each layer and each entity and what parameters should be exchanged between layers and between entities. Numerical results show that our cross-layer and end-to-end optimization approach provides more efficient resource allocation than the conventional layered and separated optimization approach.

• 한국통신학회:학술대회논문집
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• 한국통신학회 1986년도 추계학술발표회 논문집
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• pp.114-118
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• 1986

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 1999년도 춘계공동학술대회:정보화시대의 지식경영
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• pp.279-279
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• 1999

• Water Engineering Research
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• 제3권1호
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• pp.63-74
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• 2002

• 한국수자원학회논문집
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• 제52권8호
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• pp.565-573
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• 2019

본 연구에서는 지능형 정수장 운영시스템 개발 연구의 일환으로 선형계획법(Linear Programming, LP)을 이용한 정수장 취수계획 최적화 모형을 개발하였다. 개발된 최적화 모형은 원수의 정수처리비용의 최소화를 목적함수로 설정하였으며, 취수 후 정수처리에 소요되는 지연시간과 시간별 전력단가를 고려하여 취수가능량, 예측수요량, 정수지 운영수위 등의 제약조건을 만족하는 최적 취수계획을 제시하였다. 국내 H 정수장을 대상으로 경제적이고 안정적인 정수장 운영을 위해 세 가지 최적화 전략을 적용하고, 그 결과를 경제성과 안정성 측면에서 비교, 분석하였다. 개발 모형은 국내 정수장의 보다 효율적인 취수계획 수립을 위한 의사결정 지원시스템의 형태로 실무에서 활용이 가능할 것으로 기대된다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.392-392
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• 2000

This study performs optimization of paper mill scheduling using MINLP(Mixed-Integer Non-Linear Programming) method and 2-step decomposing strategy. Paper mill process is normally composed of five units: paper machine, coater, rewinder, sheet cutter and roll wrapper/ream wrapper. Various kinds of papers are produced through these units. The bottleneck of this process is how to cut product papers efficiently from raw paper reel and this is called trim loss problem or cutting stock problem. As the trim must be burned or recycled through energy consumption, minimizing quantity of the trim is important. To minimize it, the trim loss problem is mathematically formulated in MINLP form of minimizing cutting patterns and trim as well as satisfying customer's elder. The MINLP form of the problem includes bilinearity causing non-linearity and non-convexity. Bilinearity is eliminated by parameterization of one variable and the MINLP form is decomposed to MILP(Mixed-Integer Linear programming) form. And the MILP problem is optimized by means of the optimization package. Thus trim loss problem is efficiently minimized by this 2-step optimization method.