• IE interfaces
• /
• v.24 no.4
• /
• pp.281-294
• /
• 2011

This paper considers the rail crane scheduling problem which is defined as determining the sequence of loading/unloading container on/from a freight train. The objective is to minimize the weighted sum of the range of order completion time and makespan. The range of order completion time implies the difference between the maximum of completion time and minimum of start time of each customer order consisting of jobs. Makespan refers to the time when all the jobs are completed. In a rail freight terminal, logistics firms as a customer wish to reduce the range of their order completion time. To develop a methodology for the crane scheduling, we formulate the problem as a mixed integer program and develop three metaheuristics, namely, genetic algorithm, simulated annealing, and tabu search. To validate the effectiveness of heuristic algorithms, computational experiments are done based on a set of real life data. Results of the experiments show that heuristic algorithms give good solutions for small-size and large-size problems in terms of solution quality and computation time.

• Journal of Korean Society for Quality Management
• /
• v.47 no.4
• /
• pp.823-835
• /
• 2019

Purpose: This study deals with a production planning and scheduling problem to minimize the total weighted tardiness on hybrid flow shop with sets of non-identical parallel machines on stages, where parallel machines in the set are dedicated to perform specific subsets of jobs and sequence-dependent setup times are also considered. Methods: A two-stage approach, that applies MILP model in the 1st stage and dispatching rules in the 2nd stage, is proposed in this paper. The MILP model is used to assign jobs to a specific machine in order to equalize the workload of the machines at each stage, while new dispatching rules are proposed and applied to sequence jobs in the queue at each stage. Results: The proposed two-stage approach was implemented by using a commercial MILP solver and a commercial simulation software and a case study was developed based on the spark plug manufacturing process, which is an automotive component, and verified using the company's actual production history. The computational experiment shows that it can reduce the tardiness when used in conjunction with the dispatching rule. Conclusion: This proposed two-stage approach can be used for HFS systems with dedicated machines, which can be evaluated in terms of tardiness and makespan. The method is expected to be used for the aggregated production planning or shop floor-level production scheduling.

• JSTS:Journal of Semiconductor Technology and Science
• /
• v.16 no.6
• /
• pp.808-816
• /
• 2016

As the number of CPU/GPU cores and IPs in SOC increases and applications require explosive memory bandwidth, simultaneously achieving good throughput and fairness in the memory system among interfering applications is very challenging. Recent works proposed priority-based thread scheduling and channel partitioning to improve throughput and fairness. However, combining these different approaches leads to performance and fairness degradation. In this paper, we analyze the problems incurred when combining priority-based scheduling and channel partitioning and propose dynamic priority thread scheduling and adaptive channel partitioning method. In addition, we propose dynamic address mapping to further optimize the proposed scheme. Combining proposed methods could enhance weighted speedup and fairness for memory intensive applications by 4.2% and 10.2% over TCM or by 19.7% and 19.9% over FR-FCFS on average whereas the proposed scheme requires space less than TCM by 8%.

• IE interfaces
• /
• v.21 no.3
• /
• pp.274-282
• /
• 2008

This paper considers a transporter scheduling problem under dynamic block transportation environment in shipbuilding. In dynamic situations, there exist the addition or cancellation of block transportation requirements, sudden breakdowns and maintenance of transporters. The transportation of the blocks in the shipyard has some distinct characteristics. Some blocks are available to be picked up at a specific time during the planning horizon while some other blocks need to be delivered before a specific time. These requirements cause two penalty times : 1) delay times incurred when a block is picked up after a required start time, and 2) tardy times incurred when a block shipment is completed after the required delivery time. The blocks are located at different areas in the shipyard and transported by transporters. The objective of this paper is to propose heuristic algorithms which minimize the weighted sum of empty transporter travel times, delay times, and tardy times. Four heuristic algorithms for transporter scheduling are proposed and their performance is evaluated.

• Industrial Engineering and Management Systems
• /
• v.12 no.2
• /
• pp.151-160
• /
• 2013

In the past decades, several algorithms based on evolutionary approaches have been proposed for solving job shop scheduling problems (JSP), which is well-known as one of the most difficult combinatorial optimization problems. Most of them have concentrated on finding optimal solutions of a single objective, i.e., makespan, or total weighted tardiness. However, real-world scheduling problems generally involve multiple objectives which must be considered simultaneously. This paper proposes an efficient particle swarm optimization based approach to find a Pareto front for multi-objective JSP. The objective is to simultaneously minimize makespan and total tardiness of jobs. The proposed algorithm employs an Elite group to store the updated non-dominated solutions found by the whole swarm and utilizes those solutions as the guidance for particle movement. A single swarm with a mixture of four groups of particles with different movement strategies is adopted to search for Pareto solutions. The performance of the proposed method is evaluated on a set of benchmark problems and compared with the results from the existing algorithms. The experimental results demonstrate that the proposed algorithm is capable of providing a set of diverse and high-quality non-dominated solutions.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.30 no.5A
• /
• pp.417-425
• /
• 2005

KOINONIA is high-rate Wireless Personal Area Network (WPAN) technology, and is developed for multimedia traffic transmission in personal area. A KOINONIA piconet is a collection of one or more associated slaves under a single master. Efficient scheduling of a master for the traffic of slaves is essential to use channel effectively and to guarantee QoS of multimedia traffic. We propose a new scheduling algorithm to allocate channel time at desired intervals regardless of superframe length, and a Connection Admission Control(CAC) algorithm to regulate the number of traffics in a piconet. Our proposed algorithms have been shown to save channel time and to meet QoS requirements compared to the conventional weighted round-robin algorithm.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.46 no.9
• /
• pp.49-57
• /
• 2009

In this paper, we propose a multiple voltage scheduling method which reduces energy consumption considering both timing constraints and resource constraints. In the other multiple voltage scheduling techniques, high voltage is assigned to operations in the longest path and low voltage is assigned to operations that are not on the longest path. However, in those methods, voltages are assigned to specific operations restrictively. We use a simulated annealing technique, in which several voltages are assigned to specific operations flexibly regardless of whether they are on the longest path. In this paper, a post processing algorithm is proposed to further reduce the energy consumption. In some cases, designers may want to reduce the level shifters. To make tradeoff between the total energy and the number (or energy) of level shifters weighted term can be added to the cost function. When the level shifter energy is weighted six times, for example, the number of level shifters is reduced by about 24% and their energy consumption is reduced by about 20%.

• Journal of KIISE:Computer Systems and Theory
• /
• v.33 no.10
• /
• pp.722-733
• /
• 2006

In scalable streaming application, there are two important knobs to tune to effectively exploit the underlying network resource and to maximize the user perceivable quality of service(QoS): layer selection and packet scheduling. In this work, we propose Semantics Aware Packet Scheduling (SAPS) algorithm to address these issues. Using packet dependency graph, SAPS algorithm selects a layer to maximize QoS. We aim at minimizing distortion in selecting layers. In inter-frame coded video streaming, minimizing packet loss does not imply maximizing QoS. In determining the packet transmission schedule, we exploit the fact that significance of each packet loss is different dependent upon its frame type and the position within group of picture(GOP). In SAPS algorithm, each packet is assigned a weight called QoS Impact Factor Transmission schedule is derived based upon weighted smoothing. In simulation experiment, we observed that QOS actually improves when packet loss becomes worse. The simulation results show that the SAPS not only maximizes user perceivable QoS but also minimizes resource requirements.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.25 no.1A
• /
• pp.122-131
• /
• 2000

In this paper, we propose a cell scheduling algorithm for input queueing ATM switch. The input queueing architecture is attractive for building an ultra-high speed ATM (Asynchronous Transfer Mode) switch. We proposea WMUCS (Weighted Matrix Unit Cell Scheduler) based on the MUCS which resolves HOL blocking and outputport contention. The MUCS algorithm selects an optimal set of entries as winning cells from traffic matrix (weightmatrix). Our WMUCS differs from the MUCS in generating weight matrices. This change solves the starvationproblem and it reduces the cell loss variance. The performance of the proposed algorithm is evaluated by thesimulation program written in C++. The simulation results show that the maximum throughput, the average celldelay, and the cell loss rate are significantly improved. We can see that the performance of WMUCS is excellentand the cost-effective implementation of the ATM switch using proposed cell scheduling algorithm.

• Journal of the Korea Society for Simulation
• /
• v.24 no.4
• /
• pp.77-88
• /
• 2015

In this paper, we consider a two-agent single-machine scheduling problem with exponential job-dependent position-based learning effects. The objective is to minimize the total weighted completion time of one agent with the restriction that the makespan of the other agent cannot exceed an upper bound. First, we propose a branch-and-bound algorithm by developing some dominance /feasibility properties and a lower bound to find an optimal solution. Second, we design an efficient simulated annealing (SA) algorithm to search a near optimal solution by considering six different SAs to generate initial solutions. We show the performance superiority of the suggested SA using a numerical experiment. Specifically, we verify that there is no significant difference in the performance of %errors between different considered SAs using the paired t-test. Furthermore, we testify that random generation method is better than the others for agent A, whereas the initial solution method for agent B did not affect the performance of %errors.