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- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 50101 (01)
- University: Sharif University of Technology
- Department: Industrial Engineering
- Advisor(s): Najafi, Mahdi
- Abstract:
- Given the great importance and urgency of preventive operation against illegal drug trafficking as a social scourge, it is necessary to schedule and optimize the police decision in order to interdict further distribution of this harmful product. In this thesis, we study interdiction of drug distribution as multi-period maximum flow profit network interdiction on a multi-commodity flow and multi-source-sink network. The drug distribution network consists of criminal who are dynamically connected and seek to maximize the total flow profit from sources to sinks while the police aim to reduce aim to reduce total flow profit over long period of time by monitoring and interdicting criminals due to some limited budget. With respect to the real world circumstances, a mixed integer programming model has been proposed which is the converted form of a Min-Max bi-level programming model and can be solved directly on small test data. NP-completeness of the problem encouraged us to propose an algorithm based on benders decomposition to solve large scaled instances. In order to enhance the algorithm efficiency and convergence speed, some accelerator methods has applied to the basic algorithm. Computational analysis on a set of randomly generated test data demonstrate optimum policies and strategies for law enforcement activities as well as the great performance of adding Pareto optimal cut and Super Valid Inequalities in combination with multi-cut L-shape method and approximate solution of master problem as an enhanced Benders decomposition algorithm
- Keywords:
- Bilevel Programming ; Mixed Integer Programming ; Benders Decomposition ; Multi-Commodity Network Flow ; Interdiction Network ; Maximum Flow Profit Interdiction ; Multi Source-Sink Network
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