Providing fairness to mobile workforces in an automated task allocation process: A semantic multi-agent approach

Research output: Contribution to journalArticle

Abstract

Problem statement: Mobile Workforces (MW) unlike computational resources of an automated system are active but not passive entities. Therefore, an automated resource allocation system that deals with MWs should assign tasks to them fairly and in a comparatively equal manner. An unfair task allocation in a group will cause dissatisfaction, which in turn demotivates MWs who are supposed to work as a team. Approach: In an automated Mobile Workforce Brokering System (MWBS) tasks are automatically assigned to MWs at Run-Time phase of the system's run. However, the environmental risks specifically risk of disconnection disrupts the task allocation process. Disconnection causes unfair task allocation when an MW must carry the next upcoming task according to a rotator work schedule, but he is disconnected. In this situation another MW has to perform the task in order to satisfy a pre-planned daily workload. Results: In this study we explore through the Run-Time phase of MWBS and explain how its underpinning ontology-driven coordination model tackles the risk of disconnection and improves the fairness in the task allocation process. Conclusion: Moreover, fairness rates in task allocation processes are compared between an existing system and MWBS and improvement in fairness rate is shown and analyzed for 4 consecutive periods (months) of the system's run.

Original languageEnglish
Pages (from-to)1055-1062
Number of pages8
JournalAmerican Journal of Applied Sciences
Volume9
Issue number7
Publication statusPublished - 2012

Fingerprint

Semantics
Resource allocation
Ontology

Keywords

  • Fairness in task allocation
  • Mobile workforce
  • Mobile workforce brokering system
  • Mobile workforce management system
  • Ontology-driven dynamic coordination model
  • Risk of disconnection
  • Semantic multi-agent systems

ASJC Scopus subject areas

  • General

Cite this

@article{4e256f0688334520b587ea8495ed5f5c,
title = "Providing fairness to mobile workforces in an automated task allocation process: A semantic multi-agent approach",
abstract = "Problem statement: Mobile Workforces (MW) unlike computational resources of an automated system are active but not passive entities. Therefore, an automated resource allocation system that deals with MWs should assign tasks to them fairly and in a comparatively equal manner. An unfair task allocation in a group will cause dissatisfaction, which in turn demotivates MWs who are supposed to work as a team. Approach: In an automated Mobile Workforce Brokering System (MWBS) tasks are automatically assigned to MWs at Run-Time phase of the system's run. However, the environmental risks specifically risk of disconnection disrupts the task allocation process. Disconnection causes unfair task allocation when an MW must carry the next upcoming task according to a rotator work schedule, but he is disconnected. In this situation another MW has to perform the task in order to satisfy a pre-planned daily workload. Results: In this study we explore through the Run-Time phase of MWBS and explain how its underpinning ontology-driven coordination model tackles the risk of disconnection and improves the fairness in the task allocation process. Conclusion: Moreover, fairness rates in task allocation processes are compared between an existing system and MWBS and improvement in fairness rate is shown and analyzed for 4 consecutive periods (months) of the system's run.",
keywords = "Fairness in task allocation, Mobile workforce, Mobile workforce brokering system, Mobile workforce management system, Ontology-driven dynamic coordination model, Risk of disconnection, Semantic multi-agent systems",
author = "Arash Mousavi and Riza Sulaiman and Nordin, {Md. Jan} and {Ali Othman}, Zulaiha and {Abdul Shukor}, Syaimak",
year = "2012",
language = "English",
volume = "9",
pages = "1055--1062",
journal = "American Journal of Applied Sciences",
issn = "1546-9239",
publisher = "Science Publications",
number = "7",

}

TY - JOUR

T1 - Providing fairness to mobile workforces in an automated task allocation process

T2 - A semantic multi-agent approach

AU - Mousavi, Arash

AU - Sulaiman, Riza

AU - Nordin, Md. Jan

AU - Ali Othman, Zulaiha

AU - Abdul Shukor, Syaimak

PY - 2012

Y1 - 2012

N2 - Problem statement: Mobile Workforces (MW) unlike computational resources of an automated system are active but not passive entities. Therefore, an automated resource allocation system that deals with MWs should assign tasks to them fairly and in a comparatively equal manner. An unfair task allocation in a group will cause dissatisfaction, which in turn demotivates MWs who are supposed to work as a team. Approach: In an automated Mobile Workforce Brokering System (MWBS) tasks are automatically assigned to MWs at Run-Time phase of the system's run. However, the environmental risks specifically risk of disconnection disrupts the task allocation process. Disconnection causes unfair task allocation when an MW must carry the next upcoming task according to a rotator work schedule, but he is disconnected. In this situation another MW has to perform the task in order to satisfy a pre-planned daily workload. Results: In this study we explore through the Run-Time phase of MWBS and explain how its underpinning ontology-driven coordination model tackles the risk of disconnection and improves the fairness in the task allocation process. Conclusion: Moreover, fairness rates in task allocation processes are compared between an existing system and MWBS and improvement in fairness rate is shown and analyzed for 4 consecutive periods (months) of the system's run.

AB - Problem statement: Mobile Workforces (MW) unlike computational resources of an automated system are active but not passive entities. Therefore, an automated resource allocation system that deals with MWs should assign tasks to them fairly and in a comparatively equal manner. An unfair task allocation in a group will cause dissatisfaction, which in turn demotivates MWs who are supposed to work as a team. Approach: In an automated Mobile Workforce Brokering System (MWBS) tasks are automatically assigned to MWs at Run-Time phase of the system's run. However, the environmental risks specifically risk of disconnection disrupts the task allocation process. Disconnection causes unfair task allocation when an MW must carry the next upcoming task according to a rotator work schedule, but he is disconnected. In this situation another MW has to perform the task in order to satisfy a pre-planned daily workload. Results: In this study we explore through the Run-Time phase of MWBS and explain how its underpinning ontology-driven coordination model tackles the risk of disconnection and improves the fairness in the task allocation process. Conclusion: Moreover, fairness rates in task allocation processes are compared between an existing system and MWBS and improvement in fairness rate is shown and analyzed for 4 consecutive periods (months) of the system's run.

KW - Fairness in task allocation

KW - Mobile workforce

KW - Mobile workforce brokering system

KW - Mobile workforce management system

KW - Ontology-driven dynamic coordination model

KW - Risk of disconnection

KW - Semantic multi-agent systems

UR - http://www.scopus.com/inward/record.url?scp=84864411793&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84864411793&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:84864411793

VL - 9

SP - 1055

EP - 1062

JO - American Journal of Applied Sciences

JF - American Journal of Applied Sciences

SN - 1546-9239

IS - 7

ER -