• Title/Summary/Keyword: Scheduling Optimization

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Optimal Block Transportation Scheduling Considering the Minimization of the Travel Distance without Overload of a Transporter (트랜스포터의 공주행(空走行) 최소화를 고려한 블록 운반 계획 최적화)

  • Yim, Sun-Bin;Roh, Myung-Il;Cha, Ju-Hwan;Lee, Kyu-Yeul
    • Journal of the Society of Naval Architects of Korea
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    • v.45 no.6
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    • pp.646-655
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    • 2008
  • A main issue about production management of shipyards is to efficiently manage the work in process and logistics. However, so far the management of a transporter for moving building blocks has not been efficiently performed. To solve the issues, optimal block transporting scheduling system is developed for minimizing of the travel distance without overload of a transporter. To implement the developed system, a hybrid optimization algorithm for an optimal block transportation scheduling is proposed by combining the genetic algorithm and the ant algorithm. Finally, to evaluate the applicability of the developed system, it is applied to a block transportation scheduling problem of shipyards. The result shows that the developed system can generate the optimal block transportation scheduling of a transporter which minimizes the travel distance without overload of the transporter.

Energy-Efficient Adaptive Dynamic Sensor Scheduling for Target Monitoring in Wireless Sensor Networks

  • Zhang, Jian;Wu, Cheng-Dong;Zhang, Yun-Zhou;Ji, Peng
    • ETRI Journal
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    • v.33 no.6
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    • pp.857-863
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    • 2011
  • Due to uncertainties in target motion and randomness of deployed sensor nodes, the problem of imbalance of energy consumption arises from sensor scheduling. This paper presents an energy-efficient adaptive sensor scheduling for a target monitoring algorithm in a local monitoring region of wireless sensor networks. Owing to excessive scheduling of an individual node, one node with a high value generated by a decision function is preferentially selected as a tasking node to balance the local energy consumption of a dynamic clustering, and the node with the highest value is chosen as the cluster head. Others with lower ones are in reserve. In addition, an optimization problem is derived to satisfy the problem of sensor scheduling subject to the joint detection probability for tasking sensors. Particles of the target in particle filter algorithm are resampled for a higher tracking accuracy. Simulation results show this algorithm can improve the required tracking accuracy, and nodes are efficiently scheduled. Hence, there is a 41.67% savings in energy consumption.

Delay Determination of Cyclic Delay Diversity for Multi-user Scheduling in OFDMA Systems (OFDMA 시스템의 다중 사용자 스케줄링을 위한 순환지연 다이버시티의 지연값 결정)

  • Rim, Min-Joong;Hur, Seong-Ho;Song, Hyun-Joo;Lim, Dae-Woon;Jeong, Byung-Jang;Noh, Tae-Gyun
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.3A
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    • pp.248-255
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    • 2008
  • In an OFDMA system the performance of multi-user scheduling in the frequency domain is affected by the frequency selectivity of the channel. If the channel is too flat in the frequency domain, the multi-user scheduling gain might be degraded. On the contrary, if the frequency selectivity is too high and the magnitude of the frequency response severely fluctuates on the allocation bandwidth, it is also hard to get sufficient scheduling gain. For maximizing the multi-user scheduling gain, a cyclic delay diversity technique can be used to adjust the frequency selectivity of the channel. This paper proposes a method to determine the optimal delay value of cyclic delay diversity according to the allocation bandwidth and the channel characteristics.

SLA-Aware Scheduling Scheme for Market-based Computational Grid (마켓 기반 계산 그리드를 위한 SLA 인지형 스케줄링 기법)

  • Han, Young-Joo;Ye, Ren;Youn, Chan-Hyun
    • Annual Conference of KIPS
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    • 2011.04a
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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).

A Genetic Algorithm for Scheduling Sequence-Dependant Jobs on Parallel Identical Machines (병렬의 동일기계에서 처리되는 순서의존적인 작업들의 스케쥴링을 위한 유전알고리즘)

  • Lee, Moon-Kyu;Lee, Seung-Joo
    • Journal of Korean Institute of Industrial Engineers
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    • v.25 no.3
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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.

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A Hybrid Genetic Algorithm for the Multiobjective Vehicle Scheduling Problems with Service Due Times (서비스 납기가 주어진 다목적차량일정문제를 위한 혼성유전알고리듬의 개발)

    • Journal of the Korean Operations Research and Management Science Society
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    • v.24 no.2
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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.

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Joint Scheduling and Flow Control for Multi-hop Cognitive Radio Network with Spectrum Underlay

  • Quang, Nguyen Tran;Dang, Duc Ngoc Minh;Hong, Choong-Seon
    • Proceedings of the Korean Information Science Society Conference
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    • 2012.06d
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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.

Multi-objective job shop scheduling using a competitive coevolutionary algorithm (경쟁 공진화알고리듬을 이용한 다목적 Job shop 일정계획)

  • Lee Hyeon Su;Sin Gyeong Seok;Kim Yeo Geun
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2003.05a
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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.

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An efficient circuit design algorithm considering constraint (제한조건을 고려한 효율적 회로 설계 알고리즘)

  • Kim, Jae Jin
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.8 no.1
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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.

A Genetic Approach for Joint Link Scheduling and Power Control in SIC-enable Wireless Networks

  • Wang, Xiaodong;Shen, Hu;Lv, Shaohe;Zhou, Xingming
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.4
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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.