• The KIPS Transactions:PartB
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• v.8B no.6
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• pp.601-608
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• 2001

The automated assignment of multiple tasks to executing agents is a key problem in the area of multi-agent systems. In many domains, significant savings can be achieved by reallocating tasks among agents with different costs for handling tasks. The automation of task reallocation among self-interested agents requires that the individual agents use a common negotiation protocol that prescribes how they have to interact in order to come to an agreement on "who does what". In this paper, we introduce the multi-agent Traveling Salesman Problem(TSP) as an example of task reallocation problem, and suggest the Vickery auction as an interagent negotiation protocol for solving this problem. In general, auction-based protocols show several advantageous features: they are easily implementable, they enforce an efficient assignment process, and they guarantce an agreement even in scenarios in which the agents possess only very little domain-specific Knowledge. Furthermore Vickrey auctions have the additional advantage that each interested agent bids only once and that the dominant strategy is to bid one′s true valuation. In order to apply this market-based protocol into task reallocation among self-interested agents, we define the profit of each agent, the goal of negotiation, tasks to be traded out through auctions, the bidding strategy, and the sequence of auctions. Through several experiments with sample multi-agent TSPs, we show that the task allocation can improve monotonically at each step and then finally an optimal task allocation can be found with this protocol.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.5
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• pp.427-436
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• 2010

This paper deals with a task assignment problem of multiple UAVs performing multiple tasks on multiple targets. The task assignment problem of multiple UAVs is a kind of combinatorial optimization problems such as traveling salesman problem or vehicle routing problem, and it has NP-hard computational complexity. Therefore, computation time increases as the size of considered problem increases. To solve the problem efficiently, approximation methods or heuristic methods are widely used. In this study, the problem is formulated as a mixed integer linear program, and is solved by a mixed integer linear programming and a genetic algorithm, respectively. Numerical simulations for the environment of the multiple targets, multiple tasks, and obstacles were performed to analyze the optimality and efficiency of each method.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.59-61
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• 2004

Researches about scheduling distributed real-time systems have some weak points, not scheduling both sporadic and periodic tasks and messages or being unable to guaranteeing the end-to-end constraints due to omitting precedence relations between sporadic tasks. This paper describes the application model of sporadic tasks with precedence constraints in a distributed real-time system. It is shown that existing scheduling methods such as Rate Monotonic scheduling are not proper to be applied to the system having sporadic tasks with precedence constraints. So this paper proposes an end-to-end laxity-based priority assignment algorithm which considers the practical laxity of a task and allocates a proper priority to a task.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.3
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• pp.210-220
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• 2003

This work presents a method of point to surface assignment fur 3D metrology of solder pastes on PCB. A bounding box enclosing the solder paste tightly on all sides is introduced to avoid incorrect assignment. The shape of bounding box fur solder paste brick is variable according to geometry of measured points. The surface geometry of bounding box is obtained by using five peaks selected in the histogram of normalized gradient vectors. By using the bounding box enclosing the solder pastes, the task of point-to-surface assignment has been successfully conducted, then geometrical features are obtained through the task of surface fitting.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.47-53
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• 1995

The Generalized Assignment (GAP) determines the minimum assignment of n tasks to m workstations such that each task is assigned to exactly one workstation, subject to the capacity of a workstation. In this paper, we presented a new heuristic search algorithm for GAPs. Then we tested it on 4 different benchmark sample sets of random problems generated according to uniform distribution on a microcomputer.

• Journal of Industrial Technology
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• v.29 no.B
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• pp.25-31
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• 2009

The necessity of university's educational change is rising up, along with a social environment that keeps changing. This study deals with a newly educational style by recognizing the necessity of variance for engineering education, according to engineers' diversified roles within a company. The study was conducted by 7 members of middle-sized group, replaced from 5 members of small-sized and each was given his task by his job such as CEO, CMO, CSO, CIO, CCO, CQO or Auditor. On the basis of four theoretical backgrounds, this paper investigated students' level of learning satisfaction shown before and after task undertaking through a questionnaire and appraised the result made before and after task undertaking. This study is expected to improve a teaching method of university engineering education.

• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.2
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• pp.1-22
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• 1993

This paper deals with the problem of mixed model assembly line balancing. In mixed model assembly lines, tsks should be assigned to stations in such a manner that all stations have approximately the same amount of work on a production cycle basis. Further in balancing assembly lines, the related tasks, the performing task side and the team tasks should be considered to improve work methods, to give more job satisfaction to workers, and to allow greater flexibility in the design of assembly lines. In this paper, the heuristic dispatch assignment rule is developed to assign evenly tasks of each model to all stations. The heuristic method based on the assignment rule developed is presented for mixed model assembly line balancing with the considerations of the related tasks, the performing task side, and the team tasks. The proposed method is analyzed, and compared with other methods for line balancing.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.103-105
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• 2017

Hadoop MapReduce is a processing framework in which users' job can be efficiently processed in parallel and distributed ways on the Hadoop cluster. MapReduce task schedulers are used to select target nodes and assigns user's tasks to them. Previous schedulers cannot fully utilize resources of Hadoop cluster because they does not consider dynamic characteristics of cluster based on nodes' availability. To increase utilization of Hadoop cluster, this paper proposes a novel task assignment policy for MapReduce that assigns a job tasks to dynamic cluster efficiently by considering availability of each node.

• Journal of the Korea Society for Simulation
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• v.27 no.2
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• pp.71-81
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• 2018

Forklifts in a shipyard lift and transport heavy objects. Tasks occur dynamically and the rate of the task occurrence changes over time. Especially, the rate of the task occurrence is high immediately after morning and afternoon business hours. The weight of objects varies according to task characteristic, and a forklift also has the workable or allowable weight limit. In this study, we propose an online forklift dispatching algorithm based on nearest-neighbor dispatching rule using minimal cost assignment approach in order to attain the efficient operations. The proposed algorithm considers various types of forklift and multiple jobs at the same time to determine the dispatch plan. We generate dummy forklifts and dummy tasks to handle unbalance in the numbers of forklifts and tasks by taking their capacity limits and weights. In addition, a method of systematic forklift selection is also devised considering the condition of the forklift. The performance indicator is the total travel distance and the average task waiting time. We validate our approach against the priority rule-based method of the previous study by discrete-event simulation.

• Journal of Information Processing Systems
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• v.14 no.1
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• pp.129-139
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• 2018

The crowdsourcing software development (CSD) is growing rapidly in the open call format in a competitive environment. In CSD, tasks are posted on a web-based CSD platform for CSD workers to compete for the task and win rewards. Task searching and assigning are very important aspects of the CSD environment because tasks posted on different platforms are in hundreds. To search and evaluate a thousand submissions on the platform are very difficult and time-consuming process for both the developer and platform. However, there are many other problems that are affecting CSD quality and reliability of CSD workers to assign the task which include the required knowledge, large participation, time complexity and incentive motivations. In order to attract the right person for the right task, the execution of action plans will help the CSD platform as well the CSD worker for the best matching with their tasks. This study formalized the task assignment method by utilizing different situations in a CSD competition-based environment in artificial intelligence (AI) planning. The results from this study suggested that assigning the task has many challenges whenever there are undefined conditions, especially in a competitive environment. Our main focus is to evaluate the AI automated planning to provide the best possible solution to matching the CSD worker with their personality type.