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Solve the Project Scheduling Problem Considering the Assumed Discount in Buying Cost Function for Nonrenewable and Perishable Resources

Hassani Keleshteri, Bagher | 2014

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 46053 (01)
  4. University: Sharif University of Technology
  5. Department: Industrial Engineering
  6. Advisor(s): Shadrokh, Shahram
  7. Abstract:
  8. Project Scheduling is one of the most important branches of operations research and management science. In this paper, project scheduling problem with a deterministic duration of activities is studied. Resources are considered nonrenewable ones which are perishable. First of all, the project scheduling problem has been studied with a rate of corruption of inventory. Then, a rate of corruption with three parameters for Weibull is considered. Cost function for purchasing a renewable Perishable resource, has been assumed that has growing discounts for the purchase of certain health differently. Project costs are included purchase costs and maintenance costs. The objective function is the minimization of the total cost of the project. Decision variables are determine the start time and cycle of all activities and the quantity of order for nonrenewable and perishable resources. Initially the project scheduling problem with deterministic corruption has been introduced. Then, their exact and approximate methods have been studied. The issue of corruption Weibull project schedule with three parameters, has been introduced to solve this problem due to the random nature of the simulation optimization method. Given that the project scheduling is NP-hard, with the increasing scale of the problem, the possibility of finding the optimal solution in a reasonable time is not feasible. In order to solve the problem in large scales, the Genetic Algorithm, and then Simulated Annealing Algorithm have been presented and by using new techniques to search the solution space of a problem, solving time and their accuracy have been improved
  9. Keywords:
  10. Project Scheduling ; Weibull Distribution ; Genetic Algorithm ; Simulation Optimization ; Simulated Annealing Method ; Incremental Discount ; Nonrenewable Perishable Resources

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