Vehicle Routing Problems (VRP) deal with the delivery of vehicles to multiple destinations (or customers). The objective of VRP is to minimize the total travel cost (e.g., time). This thesis investigates and develops algorithms to solve VRP in time-dependent large road networks. An efficient and effective time-dependent shortest path algorithm is developed. Experiment results show that the arc labeling algorithm is more space efficient compared to the classic node labeling algorithm. This thesis also develops assignment algorithms in order to minimize the maximum travel cost while minimizing the total travel cost. Several methods are implemented to investigate the factors that affect computation efficiency of VRP, including road network size and structure, and computer programming. The applicability of Genetic Algorithms is also studied. Computer programs of algorithms are developed in several software environments including General Algebraic Modeling System (GAMS; GAMS Development Corporation, 2013), MATLAB, Microsoft Excel 2013, and Microsoft Visual Studio 2013. The results show that VRP in a time-dependent large road network can be solved efficiently and effectively using the algorithms and methods developed in this thesis.
|Commitee:||Fries, Ryan, Ko, Hoo Sang|
|School:||Southern Illinois University at Edwardsville|
|Department:||Mechanical and Industrial Engineering|
|School Location:||United States -- Illinois|
|Source:||MAI 54/02M(E), Masters Abstracts International|
|Keywords:||Algorithms, Arc labeling, Genetic algorithms, Parallel computing, Vehicle Routing Problems|
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