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Using NSGA-II for Solving Bi-Objective Robust Generalized Assignment Problem

Aghababaee, Zahra | 2013

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 44281 (01)
  4. University: Sharif University of Technology
  5. Department: Industrial Engineering
  6. Advisor(s): Eshghi, Kourosh
  7. Abstract:
  8. One of the newest approaches in optimization fields under uncertainty which absorb many scientists is robust optimization. This approach uses uncertain data instead of stochastic distributions and its goal is to find a solution which is robust under uncertainty of input data.
    Assignment problem is one of the most applicable problems in real world which its parameter is faced uncertainty. Because of this reason, the aim of this thesis is to find a method for solving generalized assignment problem robustly which the coefficients of costs and use of resources by agents for performing the jobs is undetermined. These parameters are interval data and have just lower and upper bound.
    For becoming this problem more alike to real world problems, two goals are considered for this problem with the first one is to minimize the cost of assignment and the second one is to minimize the difference between maximum and minimum amount of resource which is use by agents. For reaching this goal, using of non-dominated sorting genetic algorithm-II is proposed, and the result of using this algorithm for one group of generalized assignment which has the desired characterictics is mentioned to show the validity of model and algorithm
  9. Keywords:
  10. Multiobjective Optimization ; Genetic Algorithm ; Robust Optimization ; Interval Uncertainty ; Non-Dominate Sorting Genetic Algorithm (NSGAII) Method ; Generalized Assignment Problem

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