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Developing a Multi-Skilled Project Scheduling Problem Model Considering Costs

Makhan, Mohammad Reza | 2020

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 53151 (01)
  4. University: Sharif University of Technology
  5. Department: Industrial Engineering
  6. Advisor(s): Shadrokh, Shahram
  7. Abstract:
  8. This research intends to investigate the multi-skilled project scheduling problems (MSPSP) considering staffs’ dynamic efficiency. In doing so, a mixed-integer nonlinear programming (MINLP) model is proposed, considering the influence of personnel learning and forgetting on activities duration. The more the staff spends time on their various skills, the more learned and efficient they will be on that skill (according to personal learning curves) so that they can complete new tasks less costly and more quickly. Most project-based organizations want to maximize value by finishing the projects efficiently and developing their staff’s competence through projects. Inherently, any resource-constrained scheduling problem is from the class of NP-hard problems, thus to solve the proposed model, a genetic algorithm is designed and implemented using the python programming language. The model is validated using projects and staff data of an Iranian project-based organization. Saphiran Consulting company, an ERP implementation organization with multi-skilled staff, has consultants and programmers with different levels of seniority who have various degrees of competence in some modules and skills of ERP implementation. Data gathering method consists of direct observation and open-ended interview. The results are discussed, mainly how the learning curve of personnel affects the total value of a project-based organization
  9. Keywords:
  10. Evolutionary Algorithm ; Multi-Objective Function ; Project Based Organization ; Mixed Integer Nonlinear Programming (MINLP) ; Multi-Skilled Labor ; Learning Effect ; Forgetting Effect ; Multi-Skilled Project Scheduling Problem

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