Developing a Joint Location-Inventory-Transportation Model under Uncertainty, M.Sc. Thesis Sharif University of Technology ; Mahlooji, Hashem (Supervisor)
Abstract
In this research, an integrated location-inventory-transportation problem with uncertainty in the parameters is analyzed using Robust Optimization techniques. Unknown demand distribution is the underlying assumption, which relates better to the reality. The model’s main purpose is to determine the number and locations of the Distribution Centers (DC) that connect the supplier to the retailers, and then to assign retailers to them. The problem’s mathematical model is developed on the basis of Robust Optimization techniques and the solution space is explored by Tabu Search. The results show that the Tabu Search method achieves optimality in small-scale cases, while providing desirable...
Cataloging briefDeveloping a Joint Location-Inventory-Transportation Model under Uncertainty, M.Sc. Thesis Sharif University of Technology ; Mahlooji, Hashem (Supervisor)
Abstract
In this research, an integrated location-inventory-transportation problem with uncertainty in the parameters is analyzed using Robust Optimization techniques. Unknown demand distribution is the underlying assumption, which relates better to the reality. The model’s main purpose is to determine the number and locations of the Distribution Centers (DC) that connect the supplier to the retailers, and then to assign retailers to them. The problem’s mathematical model is developed on the basis of Robust Optimization techniques and the solution space is explored by Tabu Search. The results show that the Tabu Search method achieves optimality in small-scale cases, while providing desirable...
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