• 제목/요약/키워드: Combinatorial Optimization Problem

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Optimization Methods for Power Allocation and Interference Coordination Simultaneously with MIMO and Full Duplex for Multi-Robot Networks

  • Wang, Guisheng;Wang, Yequn;Dong, Shufu;Huang, Guoce;Sun, Qilu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권1호
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    • pp.216-239
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    • 2021
  • The present work addresses the challenging problem of coordinating power allocation with interference management in multi-robot networks by applying the promising expansion capabilities of multiple-input multiple-output (MIMO) and full duplex systems, which achieves it for maximizing the throughput of networks under the impacts of Doppler frequency shifts and external jamming. The proposed power allocation with interference coordination formulation accounts for three types of the interference, including cross-tier, co-tier, and mixed-tier interference signals with cluster head nodes operating in different full-duplex modes, and their signal-to-noise-ratios are respectively derived under the impacts of Doppler frequency shifts and external jamming. In addition, various optimization algorithms, including two centralized iterative optimization algorithms and three decentralized optimization algorithms, are applied for solving the complex and non-convex combinatorial optimization problem associated with the power allocation and interference coordination. Simulation results demonstrate that the overall network throughput increases gradually to some degree with increasing numbers of MIMO antennas. In addition, increasing the number of clusters to a certain extent increases the overall network throughput, although internal interference becomes a severe problem for further increases in the number of clusters. Accordingly, applications of multi-robot networks require that a balance should be preserved between robot deployment density and communication capacity.

배전계통 사고복구 문제에 갠선된 유전 알고리즘 적용 (An Application of Enhanced Genetic Algorithm to solve the Distribution System Restoration Problem)

  • 이정관;문경준;황기현;서정일;이화석;박준호
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1999년도 하계학술대회 논문집 C
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    • pp.1123-1125
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    • 1999
  • This paper proposes an optimization technique using Genetic Algorithm(GA) for service restoration in the distribution system. Restoration planning problem can be treated as a combinatorial optimization problem. So GA is appropriate to solve the service restoration problem in the distribution network. But searching capabilities of the GA can be enhanced by developing relevant repairing operation and modifying GA operations. In this paper, we aimed at finding appropriate open sectionalizing switch position for the restoration of distribution networks after disturbances using enhanced GA with repairing operation and modified mutation. Simulation results show that proposed method found the open sectionalizing switches with less out of service area and minimize transmission line losses and voltage drop.

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Differential Evolution Algorithm for Job Shop Scheduling Problem

  • Wisittipanich, Warisa;Kachitvichyanukul, Voratas
    • Industrial Engineering and Management Systems
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    • 제10권3호
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    • pp.203-208
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    • 2011
  • Job shop scheduling is well-known as one of the hardest combinatorial optimization problems and has been demonstrated to be NP-hard problem. In the past decades, several researchers have devoted their effort to develop evolutionary algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for job shop scheduling problem. Differential Evolution (DE) algorithm is a more recent evolutionary algorithm which has been widely applied and shown its strength in many application areas. However, the applications of DE on scheduling problems are still limited. This paper proposes a one-stage differential evolution algorithm (1ST-DE) for job shop scheduling problem. The proposed algorithm employs random key representation and permutation of m-job repetition to generate active schedules. The performance of proposed method is evaluated on a set of benchmark problems and compared with results from an existing PSO algorithm. The numerical results demonstrated that the proposed algorithm is able to provide good solutions especially for the large size problems with relatively fast computing time.

배전계통계획의 최소비용 경로탐색을 위한 신경회로망의 구현 (Implementation of Neural Network for Cost Minimum Routing of Distribution System Planning)

  • 최남진;김병섭;채명석;신중린
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1999년도 추계학술대회 논문집 학회본부 A
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    • pp.232-235
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    • 1999
  • This paper presents a HNN(Hopfield Neural Network) model to solve the ORP(Optimal Routing Problem) in DSP(Distribution System Planning). This problem is generally formulated as a combinatorial optimization problem with various equality and inequality constraints. Precedent study[3] considered only fixed cert, but in this paper, we proposed the capability of optimization by fixed cost and variable cost. And suggested the corrected formulation of energy function for improving the characteristics of convergence. The proposed algorithm has been evaluated through the sample distribution planning problem and the simmulation results are presented.

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부품 조립 공정에서 경로의 최적화 알고리즘 (Optimal Algorithm of Path in the Part-Matching Process)

  • 오제휘;차영엽
    • 한국정밀공학회지
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    • 제14권8호
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    • pp.122-129
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    • 1997
  • In this paper, we propose a Hopfield model for solving the part-matching in case that is the number of parts and positions are changed. The goal of this paper is to minimize part-connection in pairs and total path of part-connections. Therefore, this kind of problem is referred to as a combinatiorial optimization problem. First of all, we review the theoretical basis for Hopfield model and present two optimal algorithms of part-matching. The first algorithm is Traveling Salesman Problem(TSP) which improved the original and the second algorithm is Wdighted Matching Problem (WMP). Finally, we show demonstration through com- puter simulation and analyze the stability and feasibility of the generated solutions for the proposed con- nection methods. Therefore, we prove that the second algorithm is better than the first algorithm.

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배전계통에서 유전적 알고리즘을 이용한 접속변경순서결정방법 (A Re-Configuration Genetic Algorithm for Distribution Systems)

  • 최대섭
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2005년도 춘계학술대회 논문집 전기설비전문위원
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    • pp.62-63
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    • 2005
  • Recently, sectionalizing switches have been coming to be operated by remote control through the distribution SCADA system. However, the problem of determining the optimal switching sequence is a combinatorial optimization problem, and is quite difficult to solve, Hence, it is imperative to develop practically applicable solution algorithms create a new arbitral distribution system configuration from an initial configuration, and some of these algorithms do not show a load transfer sequence to reach the objective system.

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배전계통에서 유전적 알고리즘을 이용한 접속변경순서 결정방법 (A Re-Configuration Genetic Algorithm for Distribution Systems)

  • 최대섭
    • 한국조명전기설비학회:학술대회논문집
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    • 한국조명전기설비학회 2004년도 학술대회 논문집
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    • pp.381-383
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    • 2004
  • Recently, sectionalizing switches have been coming to be operated by remote control through the distribution SCADA system. However, the problem of determining the optimal switching sequence is a combinatorial optimization problem, and is quite difficult to solve. Hence, it is imperative to develop practically applicable solution algorithms create a new arbitral distribution system configuration from an initial configuration, and some of these algorithms do not show a load transfer sequence to reach the objective system.

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배전계통에서 유전적 알고리즘을 이용한 접속변경순서결정방법 (A Re-Configuration Genetic Algorithm for Distribution Systems)

  • 최대섭
    • 한국조명전기설비학회:학술대회논문집
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    • 한국조명전기설비학회 2005년도 춘계학술대회논문집
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    • pp.418-420
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    • 2005
  • Recently, sectionalizing switches have been coming to be operated by remote control through the distribution SCADA system. However, the problem of determining the optimal switching sequence is a combinatorial optimization problem, and is quite difficult In solve. Hence, it is imperative to develop practically applicable solution algorithms create a new arbitral distribution system configuration from an initial configuration and some of these algorithms do not show a load transfer sequence to reach the objective system.

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동일하지 않는 병렬기계 일정계획을 위한 휴리스틱 방법 (A Hueristic Algorithm for Nonidentical Parallel Machines Scheduling)

  • 전태웅;박해천
    • 산업경영시스템학회지
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    • 제23권59호
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    • pp.37-42
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    • 2000
  • The parallel machines scheduling problems is one of the combinatorial optimization problems that often occurs in the real world. This problem is classified into two cases, one of which is the case which processing time are identical and the other, nonidentical. Not so much researches have been made on the case that nonidentical parallel machines scheduling problem. This study proposes Tabu Search methods for solving parallel machines scheduling problems related to due dates: minimizing mean tardiness, minimizing the number of tardy jobs, minimizing the maximum tardiness.

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Optimal Design of Superframe Pattern for DVB-RCS Return Link

  • Lee, Ki-Dong;Cho, Yong-Hoon;Lee, Seung-Joon;Lee, Ho-Jin
    • ETRI Journal
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    • 제24권3호
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    • pp.251-254
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    • 2002
  • We developed a method for optimal superframe design in the multi-frequency time division multiple access (MF-TDMA) return-link of a satellite multimedia interactive network called a digital video broadcasting return channel over satellite (DVB-RCS) sub-network. To find the optimal superframe pattern with the maximum data throughput, we formulated the design problem as a non-linear combinatorial optimization problem. We also devised the proposed simple method so that it would have field applicability for improving radio resource utilization in the MF-TDMA return link.

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