• Title/Summary/Keyword: Task assignment problem

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A Heuristic Method for Assembly Line Balancing of Large-Sized Product (대형제품의 조립라인 밸런싱을 위한 Heuristic 기법)

  • Kim, Y.G.;Kwon, S.H.;Cho, M.R.
    • Journal of Korean Institute of Industrial Engineers
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    • v.17 no.2
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    • pp.51-61
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    • 1991
  • This paper presents a heuristic method for the Assembly Line Balancing(ALB) of the large-sized product. In the ALB problem of the large-sized product such as bus and truck, the assignments of the Related Task Groups(RTG), the same side tasks, and team tasks should be considered. In this paper, a new concept of the RTG and two kinds of assignment rules are proposed to resolve the above considerations. The first assignment rule allots the RTG with the constraint of the same side tasks to the station while the second allots the RTG to the station, relaxing the above constraint to increase the applicability of the method. An assignment rule for team tasks is also presented. The benefits of the method are to improve work methods, to give more job satisfaction to workers, and to allow greater flexibility in the design of assembly lines.

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Performance Analysis of Data Association Applied Frequency Weighting in 3-Passive Linear Array Sonars (주파수 가중치를 적용한 3조의 수동 선배열 소나 센서의 정보 연관 성능 분석)

  • 구본화;윤제한;홍우영;고한석
    • The Journal of the Acoustical Society of Korea
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    • v.23 no.2
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    • pp.109-116
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    • 2004
  • This paper deals with data association using 3 sets of passive linear array sonars (PUS) geometrically positioned in a Y-shaped configuration, but fixed in an underwater environment. The data association problem is directly transformed into a 3-D assignment problem, which is known to be NP-hard. For generic passive sensors, it can be sotted using conventional algorithms, while it in PLAS becomes a formidable task due to the presence of bearing ambiguity. In particular, we proposed data association method robust to bearing measurements errors by incorporating frequency information and analyze a region of ghost problem by geometrical relation PUS and target. We analyzed the effectiveness of the proposed method by representative simulation in multi-target.

Reinforcement Learning-based Dynamic Weapon Assignment to Multi-Caliber Long-Range Artillery Attacks (다종 장사정포 공격에 대한 강화학습 기반의 동적 무기할당)

  • Hyeonho Kim;Jung Hun Kim;Joohoe Kong;Ji Hoon Kyung
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.45 no.4
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    • pp.42-52
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    • 2022
  • North Korea continues to upgrade and display its long-range rocket launchers to emphasize its military strength. Recently Republic of Korea kicked off the development of anti-artillery interception system similar to Israel's "Iron Dome", designed to protect against North Korea's arsenal of long-range rockets. The system may not work smoothly without the function assigning interceptors to incoming various-caliber artillery rockets. We view the assignment task as a dynamic weapon target assignment (DWTA) problem. DWTA is a multistage decision process in which decision in a stage affects decision processes and its results in the subsequent stages. We represent the DWTA problem as a Markov decision process (MDP). Distance from Seoul to North Korea's multiple rocket launchers positioned near the border, limits the processing time of the model solver within only a few second. It is impossible to compute the exact optimal solution within the allowed time interval due to the curse of dimensionality inherently in MDP model of practical DWTA problem. We apply two reinforcement-based algorithms to get the approximate solution of the MDP model within the time limit. To check the quality of the approximate solution, we adopt Shoot-Shoot-Look(SSL) policy as a baseline. Simulation results showed that both algorithms provide better solution than the solution from the baseline strategy.

The Effect of Worker Heterogeneity in Learning and Forgetting on System Productivity (학습과 망각에 대한 작업자들의 이질성 정도가 시스템 생산성에 미치는 영향)

  • Kim, Sungsu
    • Journal of the Korean Operations Research and Management Science Society
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    • v.40 no.4
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    • pp.145-156
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    • 2015
  • Incorporation of individual learning and forgetting behaviors within worker-task assignment models produces a mixed integer nonlinear program (MINLP) problem, which is difficult to solve as a NP hard due to its nonlinearity in the objective function. Previous studies commonly assume homogeneity among workers in workforce scheduling that takes account of learning and forgetting characteristics. This paper expands previous researches by considering heterogeneous individual learning/forgetting, and investigates the impact of worker heterogeneity in initial expertise, steady-state productivity, learning and forgetting on system performance to assist manager's decision-making in worker-task assignments without tackling complex MINLP models. In order to understand the performance implications of workforce heterogeneity, this paper examines analytically how heterogeneity in each of the four parameters of the exponential learning and forgetting (L/F) model affects system performance in three cases : consecutive assignments with no break, n breaks of s-length each, and total b break-periods occurred over T periods. The study presents the direction of change in worker performance under different assignment schedules as the variance in initial expertise, steady-state productivity, learning or forgetting increases. Thus, it implies whether having more heterogenous workforce in terms of each of four parameters in the L/F model is desired or not in different schedules from the perspective of system productivity measurement.

Task Reconstruction Method for Real-Time Singularity Avoidance for Robotic Manipulators : Dynamic Task Priority Based Analysis (로봇 매니플레이터의 실시간 특이점 회피를 위한 작업 재구성법: 동적 작업 우선도에 기초한 해석)

  • 김진현;최영진
    • Journal of Institute of Control, Robotics and Systems
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    • v.10 no.10
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    • pp.855-868
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    • 2004
  • There are several types of singularities in controlling robotic manipulators: kinematic singularity, algorithmic singularity, semi-kinematic singularity, semi-algorithmic singularity, and representation singularity. The kinematic and algorithmic singularities have been investigated intensively because they are not predictable or difficult to avoid. The problem with these singularities is an unnecessary performance reduction in non-singular region and the difficulty in performance tuning. Tn this paper, we propose a method of avoiding kinematic and algorithmic singularities by applying a task reconstruction approach while maximizing the task performance by calculating singularity measures. The proposed method is implemented by removing the component approaching the singularity calculated by using singularity measure in real time. The outstanding feature of the proposed task reconstruction method (TR-method) is that it is based on a local task reconstruction as opposed to the local joint reconstruction of many other approaches. And, this method has dynamic task priority assignment feature which ensures the system stability under singular regions owing to the change of task priority. The TR-method enables us to increase the task controller gain to improve the task performance whereas this increase can destabilize the system for the conventional algorithms in real experiments. In addition, the physical meaning of tuning parameters is very straightforward. Hence, we can maximize task performance even near the singular region while simultaneously obtaining the singularity-free motion. The advantage of the proposed method is experimentally tested by using the 7-dof spatial manipulator, and the result shows that the new method improves the performance several times over the existing algorithms.

Task Scheduling Algorithm in Multiprocessor System Using Genetic Algorithm (유전 알고리즘을 이용한 멀티프로세서 시스템에서의 태스크 스케쥴링 알고리즘)

  • Kim Hyun-Chul
    • Journal of Korea Multimedia Society
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    • v.9 no.1
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    • pp.119-126
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    • 2006
  • The task scheduling in multiprocessor system is one of the key elements in the effective utilization of multiprocessor systems. The optimal assignment of tasks to multiprocessor is, in almost practical cases, an NP-hard problem. Consequently algorithms based on various modern heuristics have been proposed for practical reason. This paper proposes a new task scheduling algorithm using Genetic Algorithm which combines simulated annealing (GA+SA) in multiprocessor environment. In solution algorithms, the Genetic Algorithm (GA) and the simulated annealing (SA) are cooperatively used. In this method, the convergence of GA is improved by introducing the probability of SA as the criterion for acceptance of new trial solution. The objective of proposed scheduling algorithm is to minimize makespan. The effectiveness of the proposed algorithm is shown through simulation studies. In simulation studies, the result of proposed algorithm is better than that of any other algorithms.

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A Simultaneous Delivery and Pick-up Heterogeneous Vehicle Routing Problem with Separate Loading Area (다품종 독립 적재공간을 갖는 배달과 수거를 동시에 고려한 차량경로문제)

  • Kim, Gak-Gyu;Kim, Seong-Woo;Kim, Seong-Woo
    • Journal of Korean Institute of Industrial Engineers
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    • v.39 no.6
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    • pp.554-561
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    • 2013
  • As a special topic of the vehicle routing problems (VRP), VRPSDP extends the vehicle routing problem as considering simultaneous pickup and delivery for goods. The past studies have mainly dealt with a only weight constraint of a loading capacity for heterogeneous products. However. this study suggests VRPSDP considering separate loading area according to characteristics of loading species. The objective is to design a set of minimum distance routes for the vehicle routing assignment with independent capacity for heterogeneous species. And then we present a another HVRPSDP model which is easy to utilizes in a unique circumstance that is a guarantee of executing a task simultaneously from the various areas under restricted time and raising an application of vehicles that returns at the depot for the next mission like the military group. The optimal results of the suggested mathematical models are solved by the ILOG CPLEX software ver. 12.4 that is provided by IBM company.

Polynomial-time Greedy Algorithm for Anti-Air Missiles Assignment Problem (지대공 미사일 배정 문제의 다항시간 탐욕 알고리즘)

  • Lee, Sang-Un
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.19 no.3
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    • pp.185-191
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    • 2019
  • During the modern battlefields of multi-batches flight formation attack situation, it is an essential task for a commander to make a proper fire distribution of air defense missile launch platforms for threat targets with effectively and quickly. Pan et al. try to solve this problem using genetic algorithm, but they are fails. This paper gets the initial feasible solution using high threat target first destroying strategy only use 75% available fire of each missile launch platform. Then, the assigned missile is moving to another target in the case of decreasing total threat. As a result of experiment, while the proposed algorithm is polynomial-time complexity greedy algorithm but this can be improve the solution than genetic algorithm.

A Period Assignment Algorithm for Real-Time System Design (실시간 시스템 설계를 위한 주기 할당 알고리즘)

  • Ryu, Min-Soo;Hong, Seong-Soo
    • Journal of KIISE:Computer Systems and Theory
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    • v.27 no.1
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    • pp.61-67
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    • 2000
  • Digital controllers found in many industrial real-time systems consist of a number of interacting periodic tasks. To sustain the required control quality, these tasks possess the maximum activation periods as performance constraints. An essential step in developing a real-time system is thus to assign each of these tasks a constant period such that the maximum activation requirements are met while the system utilization is minimized [1]. Given a task graph design allowing producer/consumer relationships among tasks [2], resource demands of tasks, and range constraints on periods, the period assignment problem falls into a class of nonlinear optimization problems. This paper proposes a ploynomial time approximation algorithm which produces a solution whose utilization does not exceed twice the optimal utilization. Our experimental analysis shows that the proposed algorithm finds solutions which are very close to the optimal ones in most cases of practical interest.

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Mathematical model and heuristic for the assignment of military engineering equipments in ROK army (공병 장비의 최적할당을 위한 수리모형 및 휴리스틱 알고리즘)

  • Park, Jongbok;Ahn, Namsu
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.4
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    • pp.138-144
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    • 2020
  • The Army's engineers are carrying out a range of operations using various equipment, of which, artillery unit support is the representative engineering operation field. The main task of the artillery unit is to attack the enemy's center with firepower from the rear of a friendly force. The artillery must move its original position after firing several times to prevent exposure of the shooting position. This paper proposed a mathematical model and heuristic algorithm that can be used to determine the optimal allocation among engineer equipment, the team (work), and position while reflecting the constraints of the construction of an artillery position. The model proposed in this paper derived the optimal solution for the small size problems, but it takes a long time to derive the optimal solution for the problem of equipment placement of the engineer battalion and brigade scale. Although the heuristic suggested in this study does not guarantee the optimal solution, the solution could be obtained in a reasonable amount of time.