The transportation of goods is the last and most important component of a logistics system. In less-than-truckload (LTL) trucking industry, an efficient vehicle route and schedule for pickup and delivery in city operations is essential for realizing increased profits and for ensuring customer satisfaction.; The city operations in a LTL environment has time windows and precedence relationship restrictions when a route has both pickup and delivery. This is in addition to the capacity and maximum touring time for the vehicles.; The focus of this research is to develop a dynamic vehicle routing and scheduling computer software for decision making at the operational level. The user-friendly software allows the user to dynamically change the data and also to handle multiple demands. The basis for the software is the tabu search metaheuristic, which is applied in conjunction with the insertion and savings based exchange heuristic. These heuristics are executed sequentially until there are no further improvements in the solution. The software handles problem sizes of up to 200 customers.; Comparison of our results with optimal and best tabu solutions for 100 customers test problems without precedence relationship restriction shows that our results are within 10 to 38% of other solutions.
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