Today, in the trucking industry, dispatchers perform the tasks of cargo assignment, and driver scheduling. The growing number of containers processed at marine centers and the increasing traffic congestion in metropolitan areas adjacent to marine ports, necessitates the investigation of more efficient and reliable ways to handle the increasing cargo traffic. In this report, it is shown that the problem of container movement by trucks can be modeled as a 'multi-Traveling Salesmen Problems with Time Windows' (m- TSPTW). A two-phase exact algorithm based on dynamic programming is proposed that will find the best routes for a fleet of trucks. Since the m-TSPTW problem is Nondeterministic Polynomial (NP) hard, the computational time for large size problems becomes very high. For the case of medium to large size problems, we develop two computationally feasible methods: (1) a hybrid methodology consisting of dynamic programming in conjunction with genetic algorithms, and (2) a heuristic insertion method. Furthermore, since the cargo movement in a traffic network is a dynamic problem, we use the heuristic insertion method to add newly arriving customers to the set of customers with advanced requests. Computational results demonstrate the efficiency of the hybrid method for static problems and the insertion method for the dynamic ones.
Dynamic Optimization of Cargo Movement by Trucks in Metropolitan Areas with Adjacent Ports
2002
48 pages
Report
Keine Angabe
Englisch
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