A Multi Objective Time-Cost-Quality Optimization Model fot Project Scheduling and Human Resource Assignment Considering Manpower Competency

Document Type : Original Article

Authors

1 PhD student, Construction engineering and management, Islamic Azad University, Qeshm international Branch

2 Assistant Professor, Department of civil engineering, Islamic Azad University, Chaloos Branch

3 Assistant professor, Pardisan University of Fereydonkenar, Fereydonkenar, Iran

Abstract

Today, information and knowledge are so intertwined with human life that the present age has been called the information era. In this situation, the role of human in the organization and the way of looking at him/her will have a significant contribution to the success or failure of the organization. The role of human resources is becoming more and more prominent and it is now mentioned as the only factor in gaining a sustainable competitive advantage. Furthermore, due to dramatic developments in the field of human resource management, competency-based human resource planning has found a special place. In this study, a project scheduling problem considering multi-skilled resource and manpower competency is investigated. To do this end, an integrated multi-objective optimization model of project scheduling and human resource assignment including total completion time and execution cost minimization and project quality maximization is presented. To solve problem exactly, a mixed-integer programming model is developed and then solved by ε-constraint method in GAMS software. As the proposed model is NP-hard, a non-dominated sorting genetic (NSGA-II) algorithm is developed to solve the large scale problem. Furthermore, in order to validate the proposed algorithm, its results compare with exact method for instance problem in small scale. Results indicate that the proposed algorithm is outperformed and it can be used for real case problems.

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References

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History

  • Receive Date: 09 December 2020
  • Revise Date: 01 May 2021
  • Accept Date: 30 May 2021

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