• Title/Summary/Keyword: scheduling optimization

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Dynamic Routing and Scheduling of Multiple AGV System (다중 무인운반차량 시스템에서의 동적 라우팅과 스케줄링)

  • 전동훈
    • Journal of the Korea Society for Simulation
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    • v.8 no.3
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    • pp.67-76
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    • 1999
  • The study of the optimization of operating policy of AGV system, which is used in many factory automation environments has been proceeded by many researchers. The major operating policy of AGV system consists of routing and scheduling policy. AGV routing is composed with collision avoidance and minimal cost path find algorithm. To allocate jobs to the AGV system, AGV scheduling has to include AGV selection rules, parking rules, and recharging rules. Also in these rules, the key time parameters such as processing time of the device, loading/unloading time and charging time should be considered. In this research, we compare and analyze several operating policies of multiple loop-multiple AGV system by making a computer model and simulating it to present an appropriate operating policy.

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A Wireless MAC Scheduler Based on Video Traces for Cross-Layer Optimization (계층간 최적화를 위해 비디오 트레이스에 기반한 무선 MAC 스케줄러)

  • Cho, Seong-Ik;Pyun, Ki-Hyun
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.55 no.5
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    • pp.236-239
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    • 2006
  • A wireless MAC scheduler that provides a high level of quality-of-service (QoS) for video-on-demand (VOD) applications while achieving a reasonable level of system throughput is proposed. The proposed scheduler considers both channel qualities of mobiles and the urgency of real-time packets coming from VOD applications in a cross-layer approach between application and MAC layers.

User Scheduling Algorithm Based on Signal Quality and Inter-User Interference for Outage Minimization in Full-Duplex Cellular Networks (전이중 셀룰라 네트워크에서 아웃티지 최소화를 위한 신호 품질과 사용자간 간섭량 기반의 사용자 스케쥴링 알고리즘)

  • Choi, Hyun-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.11
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    • pp.2576-2583
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    • 2015
  • In a full-duplex (FD) wireless cellular network, uplink (UL) users induce the severe inter-user interference to downlink (DL) users. Therefore, a user scheduling that makes a pair of DL user and UL user to use the same radio resource simultaneously influences the system performances significantly. In this paper, we first formulate an optimization problem for user scheduling to minimize the occurrence of outage, aiming to guarantee the quality of service of users, and then we propose a suboptimal user scheduling algorithm with low complexity. The proposed scheduling algorithm is designed in a way where the DL user with a worse signal quality has a higher priority to choose its UL user that causes less interference. Simulation results show that the FD system using the proposed user scheduling algorithm achieves the optimal performance and significantly decreases the outage probability compared with the conventional half-duplex cellular system.

Reinforcement Learning for Minimizing Tardiness and Set-Up Change in Parallel Machine Scheduling Problems for Profile Shops in Shipyard (조선소 병렬 기계 공정에서의 납기 지연 및 셋업 변경 최소화를 위한 강화학습 기반의 생산라인 투입순서 결정)

  • So-Hyun Nam;Young-In Cho;Jong Hun Woo
    • Journal of the Society of Naval Architects of Korea
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    • v.60 no.3
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    • pp.202-211
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    • 2023
  • The profile shops in shipyards produce section steels required for block production of ships. Due to the limitations of shipyard's production capacity, a considerable amount of work is already outsourced. In addition, the need to improve the productivity of the profile shops is growing because the production volume is expected to increase due to the recent boom in the shipbuilding industry. In this study, a scheduling optimization was conducted for a parallel welding line of the profile process, with the aim of minimizing tardiness and the number of set-up changes as objective functions to achieve productivity improvements. In particular, this study applied a dynamic scheduling method to determine the job sequence considering variability of processing time. A Markov decision process model was proposed for the job sequence problem, considering the trade-off relationship between two objective functions. Deep reinforcement learning was also used to learn the optimal scheduling policy. The developed algorithm was evaluated by comparing its performance with priority rules (SSPT, ATCS, MDD, COVERT rule) in test scenarios constructed by the sampling data. As a result, the proposed scheduling algorithms outperformed than the priority rules in terms of set-up ratio, tardiness, and makespan.

Broadcast Scheduling for Wireless Networks Based on Theory of Complex Networks (복잡계 네트워크 기반 무선 네트워크를 위한 브로드캐스트 스케줄링 기법)

  • Park, Jong-Hong;Seo, Sunho;Chung, Jong-Moon
    • Journal of Internet Computing and Services
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    • v.17 no.5
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    • pp.1-8
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    • 2016
  • This paper proposes a novel broadcast scheduling algorithm for wireless large-scale networks based on theory of complex networks. In the proposed algorithm, the network topology is formed based on a scale-free network and the probability of link distribution is analyzed. In this paper, the characteristics of complex systems are analyzed (which are not concerned by the existing broadcast scheduling algorithm techniques) and the optimization of network transmission efficiency and network time delay are provided.

Non-periodic Subway Scheduling that Minimizes Operational Cost and Passenger Waiting Time

  • Hong, YunWoo;Chung, Yerim;Min, YunHong
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.8
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    • pp.133-142
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    • 2018
  • Subway metro scheduling is one of the most important problems impacting passenger convenience today. To operate efficiently, the Seoul metro uses regular, periodic schedules for all lanes, both north and southbound. However, many past studies suggest that non-periodic scheduling would better optimize costs. Since the Seoul metro is continuously facing a deficit, adopting a non-periodic schedule may be necessary. Two objectives are presented; the first, to minimize the average passengers' waiting time, and the second, to minimize total costs, the sum of the passenger waiting time, and the operational costs. In this paper, we use passenger smart card data and a precise estimation of transfer times. To find the optimal time-table, a genetic algorithm is used to find the best solution for both objectives. Using Python 3.5 for the analysis, for the first objective, we are able to reduce the average waiting time, even when there are fewer trains. For the second objective, we are able to save about 4.5 thousand USD with six fewer trains.

Multi-Objective Genetic Algorithm based on Multi-Robot Positions for Scheduling Problems (스케줄링 문제를 위한 멀티로봇 위치 기반 다목적 유전 알고리즘)

  • Choi, Jong Hoon;Kim, Je Seok;Jeong, Jin Han;Kim, Jung Min;Park, Jahng Hyon
    • Journal of the Korean Society for Precision Engineering
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    • v.31 no.8
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    • pp.689-696
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    • 2014
  • This paper presents a scheduling problem for a high-density robotic workcell using multi-objective genetic algorithm. We propose a new algorithm based on NSGA-II(Non-dominated Sorting Algorithm-II) which is the most popular algorithm to solve multi-objective optimization problems. To solve the problem efficiently, the proposed algorithm divides the problem into two processes: clustering and scheduling. In clustering process, we focus on multi-robot positions because they are fixed in manufacturing system and have a great effect on task distribution. We test the algorithm by changing multi-robot positions and compare it to previous work. Test results shows that the proposed algorithm is effective under various conditions.

ISO Coordination of Generator Maintenance Scheduling in Competitive Electricity Markets using Simulated Annealing

  • Han, Seok-Man;Chung, Koo-Hyung;Kim, Balho-H.
    • Journal of Electrical Engineering and Technology
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    • v.6 no.4
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    • pp.431-438
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    • 2011
  • To ensure that equipment outages do not directly impact the reliability of the ISO-controlled grid, market participants request permission and receive approval for planned outages from the independent system operator (ISO) in competitive electricity markets. In the face of major generation outages, the ISO will make a critical decision as regards the scheduling of the essential maintenance for myriads of generating units over a fixed planning horizon in accordance with security and adequacy assessments. Mainly, we are concerned with a fundamental framework for ISO's maintenance coordination in order to determine precedence of conflicting outages. Simulated annealing, a powerful, general-purpose optimization methodology suitable for real combinatorial search problems, is used. Generally, the ISO will put forward its best effort to adjust individual generator maintenance schedules according to the time preferences of each power generator (GENCO) by taking advantage of several factors such as installed capacity and relative weightings assigned to the GENCOs. Thus, computer testing on a four-GENCO model is conducted to demonstrate the effectiveness of the proposed method and the applicability of the solution scheme to large-scale maintenance scheduling coordination problems.

Scheduling of a Casting Sequence Under Just-In-Time (JIT) Production (적시 생산 방식에서의 주조공정 스케줄링)

  • Park, Yong-Kuk;Yang, Jung-Min
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.32 no.3
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    • pp.40-48
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    • 2009
  • In this article, scheduling of a casting sequence is studied in a casting foundry which must deliver products according to the Just-in-time(JIT) production policy of a customer. When a foundry manufactures a variety of casts with an identical alloy simultaneously, it frequently faces the task of production scheduling. An optimal casting schedule should be emphasized in order to maximize the production rate and raw material efficiency under the constraints of limited resources; melting furnaces and operation time for a casting machine. To solve this practical problem-fulfilling the objectives of casting the assigned mixed orders for the highest raw material efficiency in a way specified by the customer's JIT schedule, we implement simple integer programming. A simulation to solve a real production problem in a typical casting plant proves that the proposed method provides a feasible solution with a high accuracy for a complex, multi-variable and multi-constraint optimization problem. Employing this simple methodology, a casting foundry having an automated casting machine can produce a mixed order of casts with a maximum furnace utilization within the due date, and provide them according to their customer's JIT inventory policy.

Power Scheduling of Smart Buildings in the Smart Grid Environment Using IT Optimization Techniques (IT 최적화 기술을 이용한 지능형전력망 환경의 스마트 빌딩 전력 스케줄링)

  • Lee, Eunji;Seo, Yu-Ri;Yoon, So-Young;Jang, Hye-Rin;Bahn, Hyokyung
    • Journal of Information Technology Services
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    • v.11 no.sup
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    • pp.41-50
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    • 2012
  • With the recent advances in smart grid technologies and the increasing dissemination of smart meters, the power usage of each time unit can be detected in modern smart building environments. Thus, the utility company can adopt different price of electricity at each time slot considering the peak time. Korea government also announces the smart-grid roadmap that includes a law for realtime price of electricity. In this paper, we propose an efficient power scheduling scheme for smart buildings that adopt smart meters and real-time pricing of electricity. Our scheme dynamically changes the power mode of each consumer device according to the change of power rates. Specifically, we analyze the electricity demands and prices at each time, and then perform real-time power scheduling of consumer devices based on collaboration of each device. Experimental results show that the proposed scheme reduces the electricity charge of a smart building by up to 36.4%.