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Analysis of Multi-skilled Labor Application in Multi-task Projects

Khaghani, Farnaz | 2016

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 48616 (09)
  4. University: Sharif University of Technology
  5. Department: Civil Engineering
  6. Advisor(s): Mortaheb, Mohammad Mehdi; Pourzahedi, Hossein
  7. Abstract:
  8. One of the main challenges construction industry face is the shortage of skilled labor. It is also one of the main reason of project’s delay. Many strategies including compensation payment, longer hiring duration and increase in wages has been proposed. Conventional scheduling assumes unlimited amount of resources or if consider the resource, is restricted to single-skilled resource. This is in contrast with real-world where workers may not be available at any time or they may possess a range of skills. Multiskilling is a workforce strategy that has been shown to reduce indirect labor cost, improve productivity and make the planning more realistic. Past researches proposed algorithms using substitution rule to assign and allocate resources to activities. However, none of these researches addressed a comprehensive method for minimizing the time of the project. This research developed a framework for an algorithm in order to allocate a set of multi-skilled labor to a set of activities in order to minimize the total time of the project. The algorithm is inspired by the ant colony system optimization mechanism. It is conducted that the model works better than the mathematical model also developed by the authors, in large scale projects with large number of activities where the GAMS or CPLEX takes considerable time for giving an optimum solution. A Matlab code was then developed for solving the algorithm. By running the Matlab code for various simulated scenarios, besides the validation of the results and comparing to GAMS answers, additional observations were made. For example, the multi-skilled labor strategy works more efficient and considerable as the number of parallel activities increase
  9. Keywords:
  10. Project Management ; Optimization ; Human Resources Management ; Project Planning ; Ant Colony Algorithm ; Multi-Skilled Labor

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