A New Model for Reassignment of Tasks to Available Employees in Iraq’s Firms

A New Model for Reassignment of Tasks to Available Employees in Iraq’s Firms

Generalized assignment problem (GAP) is a well-known problem in the combinatorial optimization. This problem is a specific form of assignment problem (AP) when the employees can carry out more than one task simultaneously or each work can be assigned to more than one employee. In this paper, a new m...

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Main Authors: Dhurgam Kalel Ibrahim Alsaad, Reza Ghanbari, Ali Akbar Sohrabi, Khatere Ghorbani Moghadam
Format: Article
Language:English
Published: Hindawi Limited 2020-01-01
Series:International Journal of Mathematics and Mathematical Sciences
Online Access:http://dx.doi.org/10.1155/2020/2673793
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spelling doaj-835a1995ddb248898343c81aa1439efc2020-11-25T02:23:45ZengHindawi LimitedInternational Journal of Mathematics and Mathematical Sciences0161-17121687-04252020-01-01202010.1155/2020/26737932673793A New Model for Reassignment of Tasks to Available Employees in Iraq’s FirmsDhurgam Kalel Ibrahim Alsaad0Reza Ghanbari1Ali Akbar Sohrabi2Khatere Ghorbani Moghadam3Faculty of Mathematical Sciences, Department of Applied Mathematics, Ferdowsi University of Mashhad, Mashhad, IranFaculty of Mathematical Sciences, Department of Applied Mathematics, Ferdowsi University of Mashhad, Mashhad, IranFaculty of Mathematical Sciences, Department of Applied Mathematics, Ferdowsi University of Mashhad, Mashhad, IranMember of Optimization Laboratory in Faculty of Mathematical Sciences, Department of Applied Mathematics, Ferdowsi University of Mashhad, Mashhad, IranGeneralized assignment problem (GAP) is a well-known problem in the combinatorial optimization. This problem is a specific form of assignment problem (AP) when the employees can carry out more than one task simultaneously or each work can be assigned to more than one employee. In this paper, a new model is proposed for reassigning tasks on the available employees of Iraq companies when at least one of the jobholders is absent. Likewise, the returning workers from long holidays assumption are incorporated. Finally, a heuristic algorithm for solving reassignment tasks on laborers is introduced.http://dx.doi.org/10.1155/2020/2673793
collection DOAJ
language English
format Article
sources DOAJ
author Dhurgam Kalel Ibrahim Alsaad
Reza Ghanbari
Ali Akbar Sohrabi
Khatere Ghorbani Moghadam
spellingShingle Dhurgam Kalel Ibrahim Alsaad
Reza Ghanbari
Ali Akbar Sohrabi
Khatere Ghorbani Moghadam
A New Model for Reassignment of Tasks to Available Employees in Iraq’s Firms
International Journal of Mathematics and Mathematical Sciences
author_facet Dhurgam Kalel Ibrahim Alsaad
Reza Ghanbari
Ali Akbar Sohrabi
Khatere Ghorbani Moghadam
author_sort Dhurgam Kalel Ibrahim Alsaad
title A New Model for Reassignment of Tasks to Available Employees in Iraq’s Firms
title_short A New Model for Reassignment of Tasks to Available Employees in Iraq’s Firms
title_full A New Model for Reassignment of Tasks to Available Employees in Iraq’s Firms
title_fullStr A New Model for Reassignment of Tasks to Available Employees in Iraq’s Firms
title_full_unstemmed A New Model for Reassignment of Tasks to Available Employees in Iraq’s Firms
title_sort new model for reassignment of tasks to available employees in iraq’s firms
publisher Hindawi Limited
series International Journal of Mathematics and Mathematical Sciences
issn 0161-1712
1687-0425
publishDate 2020-01-01
description Generalized assignment problem (GAP) is a well-known problem in the combinatorial optimization. This problem is a specific form of assignment problem (AP) when the employees can carry out more than one task simultaneously or each work can be assigned to more than one employee. In this paper, a new model is proposed for reassigning tasks on the available employees of Iraq companies when at least one of the jobholders is absent. Likewise, the returning workers from long holidays assumption are incorporated. Finally, a heuristic algorithm for solving reassignment tasks on laborers is introduced.
url http://dx.doi.org/10.1155/2020/2673793
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