• International Journal of Naval Architecture and Ocean Engineering
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• v.8 no.4
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• pp.398-408
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• 2016

Based on non-completely hybrid flow line scheduling of panel block in shipbuilding, several uncertain factors influencing the problem were analyzed in a real environment, and a nonlinear integer programming model was built for each sub-scheduling problem. To narrow the difference between theory and application, rolling horizon and rescheduling methods are proposed. Moreover, with respect to the uncertainty of processing time, arriving time and due time, we take the minimizing of the early and delayed delivery costs as the objective, and establish an evaluation with a global penalty function. Finally, numerical experiments and a simulation analysis were undertaken to demonstrate the effectiveness of the model and algorithm.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.102-105
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• 1993

The objective of this study is to solve the operation scheduling problem of plural battery energy storage systems (BESS), and to find useful intonation from its result. Unlike conventional energy storage system, BESS has on hardware characteristics such as high efficiency, fast-acting response and operational loss. Considering rate constraints of thermal unit power as well as hardware characteristics of BESS, the operation scheduling has an intricated problem. In order to solve this optimization problem, we use successive approximations dynamic programming. In two types of operation, the proposed algorithm is applied to test system. one is daily optimal operation, the other weekly optimal operation.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.