| dc.description.abstract | The cross-dock system is the result of efforts to maximize costs and competitiveness in
the face of a wide range of competitors. Truck-to-truck scheduling is well known, but
it's not used much. This is mainly because major difficulties have not been successfully
solved while taking into account practical limitations carefully. The real problem of
truck scheduling at a multi-door, multi-terminal network with inventory constraints and
processing capacity limitations is the main focus of this study. To reduce errors, an
accurate mathematical model is created using mixed integer linear programming
(MILP). IBM ILOG CPLEX Optimization Studio is used to solve the model, which is
influenced by the Reservation scheduling model using Slack. Besides, another important
problem of cross-dock is the routing problem. In the Vehicle Routing Problem (VRP),
the goal is to find optimal routes for multiple vehicles visiting a set of locations. The
goal is to find optimal routes, which to minimize the length of the longest single route
among all vehicles. This is the right definition if the goal is to complete all deliveries as
soon as possible. Metaheuristics, specifically the Tabu Search (TS) algorithm, are used
to process a larger, more complex data set and are suitable for the complexity of the
problem feasibility assessment. For small data sets, the performance of CPLEX and
metaheuristics will be compared. The objective of this paper is to describe the tabu
search metaheuristic for the scheduling and vehicle routing problem with time windows.
A comparision between CPLEX and Metaheuristics can provide a broader view of the
cross-dock model From this comparison, it can be concluded that the current algorithm
performs quite well, outperforming the following algorithms in some experimental
problems. Another aim of this paper is to show the great influence on the results of the
type of objective function used, even though the travel time between customers is
numerically equal to the distance. | en_US |
