• 한국통신학회논문지
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• 제33권3A호
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• pp.248-255
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• 2008

OFDMA 시스템에서 주파수축에서의 다중사용자 스케줄링의 성능은 채널의 주파수 선택적 특성과 상관이 있다. 채널이 주파수축에서 평탄하면 다중사용자 스케줄링의 이득이 줄어들 수 있으며 반대로 주파수 선택적 특성이 너무 커서 할당 대역폭 내에서 채널의 변화가 심하게 일어난다면 충분한 스케줄링 이득을 얻기 어려워진다. 다중 사용자 스케줄링 이득을 최대화하기 위해서는 순환지연 다이버시티를 적용하여 채널의 주파수 선택적 특성을 조절할 수 있다. 이 논문에서는 할당 대역폭과 채널 특성을 고려하여 순환지연 다이버시티를 적용할 때의 최적의 지연값을 결정하는 방법을 제안한다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2011년도 춘계학술발표대회
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• pp.220-223
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• 2011

For successfully commercialized grid systems, it is required to provide an efficient scheduling scheme which is able to optimize benefits for three participants such as consumers, brokers, and providers so that every participant has sufficient benefit to maintain a sustainable market. In this paper, we define this job scheduling problem as an objective optimization problem for three participants. The three objectives are to maximize the success rate of job execution, total achieved profit, and the system utilization. To address the scheduling problem, we propose heuristics referred to as SLA-aware scheduling scheme (SA) for optimal resource allocation. The simulation results show that the improvement and the effectiveness of the proposed scheme and the proposed scheme can outperform well-known scheduling schemes such as first come first serve (FCFS), shortest job first (SJF), and earliest deadline first (EDF).

• 대한산업공학회지
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• 제25권3호
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• pp.360-368
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• 1999

We consider the problem of scheduling n jobs with sequence-dependent processing times on a set of parallel-identical machines. The processing time of each job consists of a pure processing time and a sequence-dependent setup time. The objective is to maximize the total remaining machine available time which can be used for other tasks. For the problem, a hybrid genetic algorithm is proposed. The algorithm combines a genetic algorithm for global search and a heuristic for local optimization to improve the speed of evolution convergence. The genetic operators are developed such that parallel machines can be handled in an efficient and effective way. For local optimization, the adjacent pairwise interchange method is used. The proposed hybrid genetic algorithm is compared with two heuristics, the nearest setup time method and the maximum penalty method. Computational results for a series of randomly generated problems demonstrate that the proposed algorithm outperforms the two heuristics.

• 한국경영과학회지
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• 제24권2호
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• pp.121-134
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• 1999

In this paper, I propose a hybrid genetic algorithm(HGAM) incorporating a greedy interchange local optimization procedure for the multiobjective vehicle scheduling problems with service due times where three conflicting objectives of the minimization of total vehicle travel time, total weighted tardiness, and fleet size are explicitly treated. The vehicle is allowed to visit a node exceeding its due time with a penalty, but within the latest allowable time. The HGAM applies a mixed farming and migration strategy in the evolution process. The strategy splits the population into sub-populations, all of them evolving independently, and applys a local optimization procedure periodically to some best entities in sub-populations which are then substituted by the newly improved solutions. A solution of the HCAM is represented by a diploid structure. The HGAM uses a molified PMX operator for crossover and new types of mutation operator. The performance of the HGAM is extensively evaluated using the Solomons test problems. The results show that the HGAM attains better solutions than the BC-saving algorithm, but with a much longer computation time.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2012년도 한국컴퓨터종합학술대회논문집 Vol.39 No.1(D)
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• pp.297-299
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• 2012

In this paper, we introduce a joint flow control and scheduling algorithm for multi-hop cognitive radio networks with spectrum underlay. Our proposed algorithm maximizes the total utility of secondary users while stabilizing the cognitive radio network and still satisfies the total interference from secondary users to primary network is less than an accepted level. Based on Lyapunov optimization technique, we show that our scheme is arbitrarily close to the optimal.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2003년도 춘계공동학술대회
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• pp.1071-1076
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• 2003

Evolutionary algorithm is recognized as a promising approach to solving multi-objective combinatorial optimization problems. When no preference information of decision makers is given, multi-objective optimization problems have been commonly used to search for diverse and good Pareto optimal solution. In this paper we propose a new multi-objective evolutionary algorithm based on competitive coevolutionary algorithm, and demonstrate the applicability of the algorithm. The proposed algorithm is designed to promote both population diversity and rapidity of convergence. To achieve this, the strategies of fitness evaluation and the operation of the Pareto set are developed. The algorithm is applied to job shop scheduling problems (JSPs). The JSPs have two objectives: minimizing makespan and minimizing earliness or tardiness. The proposed algorithm is compared with existing evolutionary algorithms in terms of solution quality and diversity. The experimental results reveal the effectiveness of our approach.

• 디지털산업정보학회논문지
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• 제8권1호
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• pp.41-46
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• 2012

In this paper, An efficient circuit design algorithm considering constraint is proposed. The proposed algorithm sets up in time constraint and area constraint, power consumption constraint for a circuit implementation. First, scheduling process for time constraint. Select the FU(Function Unit) which is satisfied with time constraint among the high level synthesis results. Analyze area and power consumption of selected FUs. Constraint set for area and power constraint. Device selection to see to setting condition. Optimization circuit implementation in selected device. The proposed algorithm compared with [7] and [8] algorithm. Therefore the proposed algorithm is proved an efficient algorithm for optimization circuit implementation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권4호
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• pp.1679-1691
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• 2016

Successive interference cancellation (SIC) is an effective means of multi-packet reception to combat interference at the physical layer. We investigate the joint optimization issue of channel access and power control for capacity maximization in SIC-enabled wireless networks. We propose a new interference model to characterize the sequential detection nature of SIC. Afterward, we formulize the joint optimization problem, prove it to be a nondeterministic polynomial-time-hard problem, and propose a novel approximation approach based on the genetic algorithm (GA). Finally, we discuss the design and parameter setting of the GA approach and validate its performance through extensive simulations.

• 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.