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Journal articles on the topic 'Task assignment'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Zhang, Li. "Complementarity, Task Assignment, and Incentives." Journal of Management Accounting Research 15, no. 1 (2003): 225–46. http://dx.doi.org/10.2308/jmar.2003.15.1.225.

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This paper studies the effect of complementarity on task assignment decisions and the design of optimal incentives for employees in charge of multiple tasks. A principal hires two identical agents. Each agent performs two tasks involving complementarities when the tasks vary in the informativeness of their performance measures. The principal tension governing how tasks are assigned lies between the heterogeneity loss due to aggregate performance measures under broad task assignments and the resulting positive information externalities. Although the aggregate performance measures under broad ta

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2

Wang, Wenfei, Maolong Lv, Le Ru, Bo Lu, Shiguang Hu, and Xinlong Chang. "Multi-UAV Unbalanced Targets Coordinated Dynamic Task Allocation in Phases." Aerospace 9, no. 9 (2022): 491. http://dx.doi.org/10.3390/aerospace9090491.

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Unmanned aerial vehicles (UAVs) can be used in swarms to achieve multiple tasks cooperatively. Multi-UAV and multi-target cooperative task assignments are difficult. To solve the problem of unbalanced, phased, cooperative assignment between UAVs and tasks, we establish an unbalanced, phased task assignment model that considers the constraints of task execution, time, and target task execution demand. Based on an improved consensus-based bundle algorithm (CBBA), we propose a two-tier task bidding mechanism. According to dynamic changes in new tasks, we study a dynamic assignment strategy and pr

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3

Bethke, Brett, Mario Valenti, and Jonathan How. "UAV Task Assignment." IEEE Robotics & Automation Magazine 15, no. 1 (2008): 39–44. http://dx.doi.org/10.1109/m-ra.2007.914931.

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He, Xiaoxue, Yubo Wang, Xu Zhao, Tiancong Huang, and Yantao Yu. "Task Assignment and Path Planning Mechanism Based on Grade-Matching Degree and Task Similarity in Participatory Crowdsensing." Sensors 24, no. 2 (2024): 651. http://dx.doi.org/10.3390/s24020651.

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Participatory crowdsensing (PCS) is an innovative data sensing paradigm that leverages the sensors carried in mobile devices to collect large-scale environmental information and personal behavioral data with the user’s participation. In PCS, task assignment and path planning pose complex challenges. Previous studies have only focused on the assignment of individual tasks, neglecting or overlooking the associations between tasks. In practice, users often tend to execute similar tasks when choosing assignments. Additionally, users frequently engage in tasks that do not match their abilities, lea

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Lujak, Marin, Alessio Salvatore, Alberto Fernández, Stefano Giordani, and Kendal Cousy. "How to fairly and efficiently assign tasks in individually rational agents’ coalitions? Models and fairness measures." Computer Science and Information Systems, no. 00 (2023): 75. http://dx.doi.org/10.2298/csis230119075l.

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An individually rational agent will participate in a multiagent coalition if the participation, given available information and knowledge, brings a payoff that is at least as high as the one achieved by not participating. Since agents? performance and skills may vary from task to task, the decisions about individual agent-task assignment will determine the overall performance of the coalition. Maximising the efficiency of the one-on-one assignment of tasks to agents corresponds to the conventional linear sum assignment problem, which considers efficiency as the sum of the costs or benefits of

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Li, Yunhui, Liang Chang, Long Li, Xuguang Bao, and Tianlong Gu. "TASC-MADM: Task Assignment in Spatial Crowdsourcing Based on Multiattribute Decision-Making." Security and Communication Networks 2021 (August 20, 2021): 1–14. http://dx.doi.org/10.1155/2021/5448397.

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The methodology, formulating a reasonable task assignment to find the most suitable workers for a task and achieving the desired objectives, is the most fundamental challenge in spatial crowdsourcing. Many task assignment approaches have been proposed to improve the quality of crowdsourcing results and the number of task assignment and to limit the budget and the travel cost. However, these approaches have two shortcomings: (1) these approaches are commonly based on the attributes influencing the result of task assignment. However, different tasks may have different preferences for individual

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7

Li, Xiang, Yan Zhao, Xiaofang Zhou, and Kai Zheng. "Consensus-Based Group Task Assignment with Social Impact in Spatial Crowdsourcing." Data Science and Engineering 5, no. 4 (2020): 375–90. http://dx.doi.org/10.1007/s41019-020-00142-0.

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Abstract With the pervasiveness of GPS-enabled smart devices and increased wireless communication technologies, spatial crowdsourcing (SC) has drawn increasing attention in assigning location-sensitive tasks to moving workers. In real-world scenarios, for the complex tasks, SC is more likely to assign each task to more than one worker, called group task assignment (GTA), for the reason that an individual worker cannot complete the task well by herself. It is a challenging issue to assign worker groups the tasks that they are interested in and willing to perform. In this paper, we propose a nov

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8

Mir, Shantona, and Sukanto Roy. "Assignment Again! Investigating the Psychological Perspectives of Assignment and Assignment Deadlines among Tertiary Level Students." English Language Teaching Perspectives 9, no. 1-2 (2024): 117–30. http://dx.doi.org/10.3126/eltp.v9i1-2.68725.

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This paper aims to study university students' psychological perspectives on assignment deadlines. The purpose of this study is to investigate the issues faced by students before assignment submission and their relation to the education system, programme of study, personalities of teachers, and the importance of assignments. All in all, this paper delves into students' psychological barriers regarding assignments and the problems teachers face while assigning assignments. A mixed method is applied to conduct the research. The quantitative data has been collected using a survey among students fr

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Li, Xin, Wenyang Gan, Pang Wen, and Daqi Zhu. "Multi-AUV Kinematic Task Assignment Based on Self-Organizing Map Neural Network and Dubins Path Generator." Sensors 24, no. 19 (2024): 6345. http://dx.doi.org/10.3390/s24196345.

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To deal with the task assignment problem of multi-AUV systems under kinematic constraints, which means steering capability constraints for underactuated AUVs or other vehicles likely, an improved task assignment algorithm is proposed combining the Dubins Path algorithm with improved SOM neural network algorithm. At first, the aimed tasks are assigned to the AUVs by the improved SOM neural network method based on workload balance and neighborhood function. When there exists kinematic constraints or obstacles which may cause failure of trajectory planning, task re-assignment will be implemented

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10

Zhao, Yan, Jinfu Xia, Guanfeng Liu, et al. "Preference-Aware Task Assignment in Spatial Crowdsourcing." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 2629–36. http://dx.doi.org/10.1609/aaai.v33i01.33012629.

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With the ubiquity of smart devices, Spatial Crowdsourcing (SC) has emerged as a new transformative platform that engages mobile users to perform spatio-temporal tasks by physically traveling to specified locations. Thus, various SC techniques have been studied for performance optimization, among which one of the major challenges is how to assign workers the tasks that they are really interested in and willing to perform. In this paper, we propose a novel preference-aware spatial task assignment system based on workers’ temporal preferences, which consists of two components: History-based Conte

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Shuan-Jun Song, Shuan-Jun Song, Long-Guang Peng Shuan-Jun Song, Jie Zhang Long-Guang Peng, and Zhen Liu Jie Zhang. "A Dynamic Task Assignment Optimization Method for Multi-AGV System Based on Genetic Algorithm." 電腦學刊 34, no. 3 (2023): 093–108. http://dx.doi.org/10.53106/199115992023063403007.

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<p>Aiming at the influence of AGV without considering the working state on task assignment decision in multi-AGV system task assignment, a dynamic task assignment decision method with task completion prediction based on genetic algorithm. When assigning the arrived tasks at each stage, the decision method brings the working AGVs and the idle AGVs into the set of schedulable vehicles at the same time, which expands the scope of the optimal decision, makes the available AGV resources more fully mobilized in the dynamic scheduling process, and improves the efficiency of the whole scheduling

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Shah, Julie, Patrick Conrad, and Brian Williams. "Fast Distributed Multi-agent Plan Execution with Dynamic Task Assignment and Scheduling." Proceedings of the International Conference on Automated Planning and Scheduling 19 (October 16, 2009): 289–96. http://dx.doi.org/10.1609/icaps.v19i1.13362.

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An essential quality of a good partner is her responsiveness to other team members. Recent work in dynamic plan execution exhibits elements of this quality through the ability to adapt to the temporal uncertainties of others agents and the environment. However, a good teammate also has the ability to adapt on-the-fly through task assignment. We generalize the framework of dynamic execution to perform plan execution with dynamic task assignment as well as scheduling.This paper introduces Chaski, a multi-agent executive for scheduling temporal plans with online task assignment. Chaski enables an

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Diana, Ulfa, and Rifky Fauzi. "PEMBAGIAN TUGAS APEL PAGI MINGGUAN PEGAWAI INSTANSI XYZ DENGAN MENGGUNAKAN PEWARNAAN GRAF BESERTA ANALISIS BEBAN PENUGASAN." Al-Aqlu: Jurnal Matematika, Teknik dan Sains 3, no. 1 (2025): 31–42. https://doi.org/10.59896/aqlu.v3i1.60.

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This study addresses the issue of the weekly morning roll call duty assignment at XYZ Agency. The allocation of morning roll call duties at XYZ Agency has been incidental, leading to uneven task assignments for employees. The author proposes a solution to this problem by implementing the Welch-Powell Algorithm on Graph Coloring to determine the allocation of morning roll call duties for XYZ Agency employees. This is achieved by representing each employee as a point, and the edges represent job similarities. The graph coloring results in this study produce 4 colors: red, green, blue, and purple

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14

Costa, Joan E. Ricart I. "Managerial Task Assignment and Promotions." Econometrica 56, no. 2 (1988): 449. http://dx.doi.org/10.2307/1911081.

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15

Manoj, K., Krishna Raj, and G. Chaitanya Bharathi. "Employee Task Assignment Android Application." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 12 (2024): 1–6. https://doi.org/10.55041/ijsrem39596.

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An Android-based Employee Tracking System was created to monitor all employee activities. This system tracks scheduling and time-off requests, which are crucial for managers to determine when employees are expected to be in the office or working remotely. The system provides a convenient way for managers to oversee their team’s performance via mobile phones. It was developed using the JAVA programming language, with data being stored in an SQLite database. The design followed an Object-Oriented Analysis and Design methodology, incorporating a structured, iterative approach. Data was gathered t

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16

Puschke, Kerstin. "Task assignment and organizational form." Journal of Economics 96, no. 2 (2008): 149–68. http://dx.doi.org/10.1007/s00712-008-0033-z.

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17

Hettiachchi, Danula, Vassilis Kostakos, and Jorge Goncalves. "A Survey on Task Assignment in Crowdsourcing." ACM Computing Surveys 55, no. 3 (2023): 1–35. http://dx.doi.org/10.1145/3494522.

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Quality improvement methods are essential to gathering high-quality crowdsourced data, both for research and industry applications. A popular and broadly applicable method is task assignment that dynamically adjusts crowd workflow parameters. In this survey, we review task assignment methods that address: heterogeneous task assignment, question assignment, and plurality problems in crowdsourcing. We discuss and contrast how these methods estimate worker performance, and highlight potential challenges in their implementation. Finally, we discuss future research directions for task assignment me

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18

Rahmawati, Anisa Ayu. "Factors Associated with Nurses' Job Satisfaction in the Implementation of the Team Assignment Method." Genius Journal 6, no. 1 (2025): 147–54. https://doi.org/10.56359/gj.v6i1.596.

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Introduction: The implementation of team-based nursing assignments is increasingly recognized as a crucial factor influencing nurses' job satisfaction. However, the effectiveness of this method in enhancing job satisfaction remains insufficiently explored, especially in Indonesian hospital settings. Objective: This study aimed to identify the factors related to nurses' job satisfaction in relation to the application of the team assignment method at Bhayangkara Hospital, Bandar Lampung in 2025. Method: This quantitative research employed a cross-sectional design involving 55 nurses selected usi

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19

Sun, Cheng, Yuwen Yao, and Enhui Zheng. "Enhancing Unmanned Aerial Vehicle Task Assignment with the Adaptive Sampling-Based Task Rationality Review Algorithm." Drones 8, no. 9 (2024): 422. http://dx.doi.org/10.3390/drones8090422.

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As the application areas of unmanned aerial vehicles (UAVs) continue to expand, the importance of UAV task allocation becomes increasingly evident. A highly effective and efficient UAV task assignment method can significantly enhance the quality of task completion. However, traditional heuristic algorithms often perform poorly in complex and dynamic environments, and existing auction-based algorithms typically fail to ensure optimal assignment results. Therefore, this paper proposes a more rigorous and comprehensive mathematical model for UAV task assignment. By introducing task path decision

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20

Wagner, Glenn, Howie Choset, and Nora Ayanian. "Subdimensional Expansion and Optimal Task Reassignment." Proceedings of the International Symposium on Combinatorial Search 3, no. 1 (2021): 177–78. http://dx.doi.org/10.1609/socs.v3i1.18261.

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Multirobot path planning and task assignment are traditionally treated separately, however task assignment can greatly impact the difficulty of the path planning problem, and the ultimate quality of solution is dependent upon both. We introduce task reassignment, an approach to optimally solving the coupled task assignment and path planning problems. We show that task reassignment improves solution quality, and reduces planning time in some situations.

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21

Miles, Jeffrey A. "The Influence of Goal Commitment and Partner Status on Team Assignment Outcomes." Psychological Reports 123, no. 3 (2019): 844–71. http://dx.doi.org/10.1177/0033294118821299.

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The present study replicated and extended research on the influence of team assignment methods on task performance and fairness perceptions. This study examined the influence of team assignment methods, goal commitment, and partner status on team member performance and fairness perceptions in a laboratory setting. The assignment conditions were comprised of three variables: assignment method (random, self-decision, and ability), performer status (assigned or unassigned), and partner status (unassigned team member stayed or left during task performance). A significant interaction was found betw

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22

Aeni, Nur, Vivit Rosmayanti, and Tuti Wijayanti. "Threats to the Execution of the English Presentation Task for University Students." Jadila: Journal of Development and Innovation in Language and Literature Education 5, no. 1 (2025): 61–78. https://doi.org/10.52760/jadila.v5i1.804.

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English presentation tasks for university students are designed to enhance communication skills, boost confidence, and improve language proficiency. These tasks involve researching topic, organizing content, and delivering it effectively to an audience. However, not all students can deliver it confidently. The purpose of the study was to find out what elements affect EFL learners' comprehension of the materials when English presenting assignments are implemented. To triangulate the data for this qualitative descriptive study, interviews and classroom observations were used. The researcher empl

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Holder, Joshua, Natasha Jaques, and Mehran Mesbahi. "Multi Agent Reinforcement Learning for Sequential Satellite Assignment Problems." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 25 (2025): 26516–24. https://doi.org/10.1609/aaai.v39i25.34852.

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Assignment problems are a classic combinatorial optimization problem in which a group of agents must be assigned to a group of tasks such that maximum utility is achieved while satisfying assignment constraints. Given the utility of each agent completing each task, polynomial-time algorithms exist to solve a single assignment problem in its simplest form. However, in many modern-day applications such as satellite constellations, power grids, and mobile robot scheduling, assignment problems unfold over time, with the utility for a given assignment depending heavily on the state of the system. W

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24

Wu, Xiaohu, Yihao Liu, Xueyan Tang, et al. "Multi-Agent Pickup and Delivery with Task Deadlines." Proceedings of the International Symposium on Combinatorial Search 12, no. 1 (2021): 206–8. http://dx.doi.org/10.1609/socs.v12i1.18585.

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We study the multi-agent pickup and delivery problem with task deadlines, where a team of agents execute tasks with individual deadlines to maximize the number of tasks completed by their deadlines. We take an integrated approach that assigns and plans one task at a time taking into account the agent states resulting from all the previous task assignments and path planning. We define metrics to effectively determine which agent ought to execute a given task and which task is most worth assignment next. We leverage the bounding technique to greatly improve the computational efficiency.

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Weng, Jiali, and Xike Xie. "Optimizing Spatial Crowdsourcing: A Quality- Aware Task Assignment Approach for Mobile Communication." Journal of Electronic Research and Application 8, no. 3 (2024): 104–11. http://dx.doi.org/10.26689/jera.v8i3.7214.

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The widespread use of advanced electronic devices has led to the emergence of spatial crowdsourcing, a method that taps into collective efforts to perform real-world tasks like environmental monitoring and traffic surveillance. Our research focuses on a specific type of spatial crowdsourcing that involves ongoing, collaborative efforts for continuous spatial data acquisition. However, due to limited budgets and workforce availability, the collected data often lacks completeness, posing a data deficiency problem. To address this, we propose a reciprocal framework to optimize task assignments by

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Zhu, Xiaojuan, Kuan-Ching Li, Jinwei Zhang, and Shunxiang Zhang. "Distributed Reliable and Efficient Transmission Task Assignment for WSNs." Sensors 19, no. 22 (2019): 5028. http://dx.doi.org/10.3390/s19225028.

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Task assignment is a crucial problem in wireless sensor networks (WSNs) that may affect the completion quality of sensing tasks. From the perspective of global optimization, a transmission-oriented reliable and energy-efficient task allocation (TRETA) is proposed, which is based on a comprehensive multi-level view of the network and an evaluation model for transmission in WSNs. To deliver better fault tolerance, TRETA dynamically adjusts in event-driven mode. Aiming to solve the reliable and efficient distributed task allocation problem in WSNs, two distributed task assignments for WSNs based

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Wang, Weining. "Unmasking Illegitimate Task Assignment: Exploring Its Impact on Employee Well-being and the Role of Information Management Systems in HR." Journal of Information Systems Engineering and Management 9, no. 3 (2024): 26259. http://dx.doi.org/10.55267/iadt.07.14776.

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This research aims to explore the direct relationship between the illegitimate task assignment and employee well-being. The relationship between the variables illegitimate task assignment and HR information management systems was also explored in this research. Moreover, this research also aims to explore the mediating role of HR information management systems among the proposed direct relationship of this research. To achieve the aim of this research the data was collected from the 319 employees of 13 software companies in Hunan Province, China. This research findings reveal a significant imp

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McGahan, William T., Hardy Ernst, and Laurel Evelyn Dyson. "Individual Learning Strategies and Choice in Student-Generated Multimedia." International Journal of Mobile and Blended Learning 8, no. 3 (2016): 1–18. http://dx.doi.org/10.4018/ijmbl.2016070101.

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There has been an increasing focus on student-generated multimedia assessment as a way of introducing the benefits of both visual literacy and peer-mediated learning into university courses. One such assessment was offered to first-year health science students but, contrary to expectations, led to poorer performance in their end-of-semester examinations. Following an analysis, the assignment was redesigned to offer students a choice of either a group-based animation task or an individual written task. Results showed improved performance on the assignment when students were offered a choice of

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Jyoti, Arora, and Sharma Surbhi. "Solving Task Assignment Problem Using Branch and Bound Method." Journal of Applied Mathematics and Statistical Analysis 4, no. 1 (2023): 1–7. https://doi.org/10.5281/zenodo.7813430.

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<em>The main aim of this paper is to present an algorithm of Branch and Bound method for solving task assignment problem. The branch and bound approach is based on divide and conquer method in which large problem is divided into smaller subsets of solutions. Our algorithm calculates lower bounds on solutions to the Task Assignment problem, which is further divided into subsets. Experimental results show that this Branch and Bound method to solve Task Assignment problem shows better results than standard Hungarian Method. A Numerical example is taken to illustrate the solution procedure</em>

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Bracci, A., M. Innocenti, and L. Pollini. "Cooperative Task Assignment Using Dynamic Ranking." IFAC Proceedings Volumes 41, no. 2 (2008): 5712–17. http://dx.doi.org/10.3182/20080706-5-kr-1001.00963.

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31

Ho, Chien-Ju, and Jennifer Vaughan. "Online Task Assignment in Crowdsourcing Markets." Proceedings of the AAAI Conference on Artificial Intelligence 26, no. 1 (2021): 45–51. http://dx.doi.org/10.1609/aaai.v26i1.8120.

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We explore the problem of assigning heterogeneous tasks to workers with different, unknown skill sets in crowdsourcing markets such as Amazon Mechanical Turk. We first formalize the online task assignment problem, in which a requester has a fixed set of tasks and a budget that specifies how many times he would like each task completed. Workers arrive one at a time (with the same worker potentially arriving multiple times), and must be assigned to a task upon arrival. The goal is to allocate workers to tasks in a way that maximizes the total benefit that the requester obtains from the completed

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32

Moore, B. J., and K. M. Passino. "Distributed Task Assignment for Mobile Agents." IEEE Transactions on Automatic Control 52, no. 4 (2007): 749–53. http://dx.doi.org/10.1109/tac.2007.894545.

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Devereux, Paul J. "Task Assignment over the Business Cycle." Journal of Labor Economics 18, no. 1 (2000): 98–124. http://dx.doi.org/10.1086/209952.

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Radojković, Petar, Vladimir Čakarević, Miquel Moretó, et al. "Optimal task assignment in multithreaded processors." ACM SIGARCH Computer Architecture News 40, no. 1 (2012): 235–48. http://dx.doi.org/10.1145/2189750.2151002.

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Chen, Zhao, Peng Cheng, Lei Chen, Xuemin Lin, and Cyrus Shahabi. "Fair task assignment in spatial crowdsourcing." Proceedings of the VLDB Endowment 13, no. 12 (2020): 2479–92. http://dx.doi.org/10.14778/3407790.3407839.

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36

Cheol-Hoon Lee and K. G. Shin. "Optimal task assignment in homogeneous networks." IEEE Transactions on Parallel and Distributed Systems 8, no. 2 (1997): 119–29. http://dx.doi.org/10.1109/71.577254.

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Tong, Yongxin, and Zimu Zhou. "Dynamic task assignment in spatial crowdsourcing." SIGSPATIAL Special 10, no. 2 (2018): 18–25. http://dx.doi.org/10.1145/3292390.3292395.

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SEO, KYUNG-RYONG, and KYU-HO PARK. "TASK ASSIGNMENT IN HOST-SATELLITE SYSTEMS." Journal of Circuits, Systems and Computers 06, no. 03 (1996): 213–25. http://dx.doi.org/10.1142/s0218126696000170.

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This paper deals with the problem of assigning task modules of a program over a multiple computer system such that the sum of execution and communication costs is minimized. If the number of processors is two, this problem can be solved efficiently using the network flow approach pioneered by Stone.13 However, the general n-processor problem (n>3) in a fully connected system is known to be NP-complete.14 A host-satellite system considered in this paper is composed of a powerful host processor p0 and N homogeneous satellite processors pk’s, 1≤k≤N, in which each satellite processor pk is conn

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Broberg, James, Zahir Tari, and Panlop Zeephongsekul. "Task assignment with work-conserving migration." Parallel Computing 32, no. 11-12 (2006): 808–30. http://dx.doi.org/10.1016/j.parco.2006.09.005.

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Ucar, Bora, Cevdet Aykanat, Kamer Kaya, and Murat Ikinci. "Task assignment in heterogeneous computing systems." Journal of Parallel and Distributed Computing 66, no. 1 (2006): 32–46. http://dx.doi.org/10.1016/j.jpdc.2005.06.014.

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Gutjahr, W. J., M. Hitz, and T. A. Mueck. "Task assignment in Cayley interconnection topologies." Parallel Computing 23, no. 10 (1997): 1429–60. http://dx.doi.org/10.1016/s0167-8191(97)89285-x.

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Zhang, Yonglong, Haiyan Qin, Bin Li, Jin Wang, Sungyoung Lee, and Zhiqiu Huang. "Truthful mechanism for crowdsourcing task assignment." Tsinghua Science and Technology 23, no. 6 (2018): 645–59. http://dx.doi.org/10.26599/tst.2018.9010064.

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HSU, CHIUN-CHIEH, SHENG-DE WANG, and TE-SON KUO. "Task assignment in distributed computing systems." International Journal of Systems Science 21, no. 12 (1990): 2425–40. http://dx.doi.org/10.1080/00207729008910562.

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Raravi, Gurulingesh, and Vincent Nélis. "Task Assignment Algorithms for Heterogeneous Multiprocessors." ACM Transactions on Embedded Computing Systems 13, no. 5s (2014): 1–26. http://dx.doi.org/10.1145/2660494.

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Li, Yongkui, Yujie Lu, Dongyu Li, and Liang Ma. "Metanetwork Analysis for Project Task Assignment." Journal of Construction Engineering and Management 141, no. 12 (2015): 04015044. http://dx.doi.org/10.1061/(asce)co.1943-7862.0001019.

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Radojković, Petar, Vladimir Čakarević, Miquel Moretó, et al. "Optimal task assignment in multithreaded processors." ACM SIGPLAN Notices 47, no. 4 (2012): 235–48. http://dx.doi.org/10.1145/2248487.2151002.

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Siva Ram Murthy, C., and V. Rajaraman. "Task assignment in a multiprocessor system." Microprocessing and Microprogramming 26, no. 1 (1989): 63–71. http://dx.doi.org/10.1016/0165-6074(89)90282-2.

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Daido, Kohei, Kimiyuki Morita, Takeshi Murooka, and Hiromasa Ogawa. "Task assignment under agent loss aversion." Economics Letters 121, no. 1 (2013): 35–38. http://dx.doi.org/10.1016/j.econlet.2013.06.040.

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De Paola, Maria, and Vincenzo Scoppa. "Task assignment, incentives and technological factors." Managerial and Decision Economics 30, no. 1 (2009): 43–55. http://dx.doi.org/10.1002/mde.1434.

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Kumar, Harendra, M. P. Singh, and Pradeep Kumar Yadav. "Optimal Tasks Assignment for Multiple Heterogeneous Processors with Dynamic Re-assignment." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 4, no. 2 (2005): 528–35. http://dx.doi.org/10.24297/ijct.v4i2b2.3313.

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Abstract:

Distributed Computing System [DCS] has attracted several researchers by posing several challenging problems. In this paper we have developed a mathematical model for allocating â€œMâ€ tasks of distributed program to â€œNâ€ multiple processors (M>N) that minimizes the total cost of the program. Relocating the tasks from one processor to another at certain points during the course of execution of the program that contributes to the total cost of the running program has been taken into account. Most of the researchers have considered the cost for relocating the task from one processor to ano

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