Truckload Carrier Selection, Routing and Cost Optimization (original) (raw)
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Production Engineering Archives, 2020
This study describes a pickup and delivery vehicle routing problem, considering time windows in reality. The problem of tractor truck routes is formulated by a mixed integer programming model. Besides this, three algorithms - a guided local search, a tabu search, and simulated annealing - are proposed as solutions. The aims of our study are to optimize the number of internal tractor trucks used, and create optimal routes in order to minimize total logistics costs, including the fixed and variable costs of an internal vehicle group and the renting cost of external vehicles. Besides, our study also evaluates both the quality of solutions and the time to find optimal solutions to select the best suitable algorithm for the real problem mentioned above. A novel mathematical model is formulated by OR tools for Python. Compared to the current solution, our results reduced total costs by 18%, increased the proportion of orders completed by internal vehicles (84%), and the proportion of orde...
A note on the truck and trailer routing problem
Expert Systems with Applications, 2010
This study considers the relaxed truck and trailer routing problem (RTTRP), a relaxation of the truck and trailer routing problem (TTRP). TTRP is a variant of the well studied vehicle routing problem (VRP). In TTRP, a fleet of trucks and trailers are used to service a set of customers with known demands. Some customers may be serviced by a truck pulling a trailer, while the others may only be serviced by a single truck. This is the main difference between TTRP and VRP. The number of available trucks and available trailers is limited in the original TTRP but there are no fixed costs associated with the use of trucks or trailers. Therefore, it is reasonable to relax this fleet size constraint to see if it is possible to further reduce the total routing cost (distance). In addition, the resulting RTTRP can also be used to determine a better fleet mix. We developed a simulated annealing heuristic for solving RTTRP and tested it on 21 existing TTRP benchmark problems and 36 newly generated TTRP instances.
Solving the truck and trailer routing problem based on a simulated annealing heuristic
Computers & Operations Research, 2009
In this study, we consider the application of a simulated annealing (SA) heuristic to the truck and trailer routing problem (TTRP), a variant of the vehicle routing problem (VRP). In the TTRP, some customers can be serviced by either a complete vehicle (that is, a truck pulling a trailer) or a single truck, while others can only be serviced by a single truck for various reasons. SA has seen widespread applications to various combinatorial optimization problems, including the VRP. However, to our best knowledge, it has not been applied to the TTRP. So far, all the best known results for benchmark TTRP instances were obtained using tabu search (TS). We applied SA to the TTRP and obtained 17 best solutions to the 21 benchmark TTRP benchmark problems, including 11 new best solutions. Moreover, the computational time required by the proposed SA heuristic is less than those reported in prior studies. The results suggest that SA is competitive with TS on solving the TTRP.
Vehicle routing problem: recent literature review of its variants
International Journal of Operational Research, 2018
The vehicle routing problem is the most studied combinatorial optimisation problem. The purpose of this study is to provide an overview of the research to date in vehicle routing problem variants. The literature is reviewed with a focus on research in three major variants of the vehicle routing problem, namely capacitated vehicle routing problem, mixed depot vehicle routing problem and vehicle routing problem with pickup and delivery. Journal articles from three academic databases, namely Taylor and Francis, Elsevier and Emerald, are selected and reviewed. Ample literature is available on this problem so to restrict the scope, we screened the journal articles using the above mentioned variants precisely, excluding those that are in combination with other variants. This review takes a closer look at 117 research articles selected from various journals. By presenting the past literature, we hope to motivate further research in the field.
A simulated annealing heuristic for the truck and trailer routing problem with time windows
Expert Systems with Applications, 2011
In this study, we consider the application of a simulated annealing (SA) heuristic to the truck and trailer routing problem with time windows (TTRPTW), an extension of the truck and trailer routing problem (TTRP). TTRP is a variant of the well-known well-studied vehicle routing problem (VRP). In TTRP, some customers can be serviced by either a complete vehicle (that is, a truck pulling a trailer) or a single truck, while others can only be serviced by a single truck for various reasons. In some TTRP applications, each customer has a predetermined time window for taking services. This problem is called the truck and trailer routing problem with time windows. It can be easily verified that the vehicle routing problem with time windows (VRPTW) is a special case of TTRPTW. Thus TTRPTW belongs to the class of NP-hard problems and it is natural to tackle this problem with heuristics approaches. Simulated annealing (SA) has seen widespread applications to various combinatorial optimization problems, including the VRP. Therefore, we developed an SA based heuristic to solve TTRPTW. To our best knowledge, there are no benchmark instances for TTRPTW in the literature. Therefore we converted 12 Solomon's VRPTW benchmark problems into 36 TTRPTW benchmark problems and tested our SA heuristic on them. Computational study indicates that SA is capable of producing high quality solutions to TTRPTW within reasonable time.
2015
Vehicle Routing Problem (VRP) is one of the most challenging problems in combinatorial optimization. Objective of VRP is to find minimum length route starts and ends in a depot. There are some additional constraints such as more than one depot, service time, time window, capacity of vehicle, and many more. These are cause of VRP variants. Vehicle Routing Problem with Time Windows (VRPTW) is a variant of VRP with some additional constrains, that are number of requests may not exceed the vehicle capacity, as well as travel time and service time may not exceed the time window. Multi Depot Vehicle Routing Problem (MDVRP) has number of depots serving all customers, a number of vehicles distributing goods to customers with a minimum distance of distribution route without exceeding the capacity of the vehicle. Many researches have presented algorithms to solve VRPTW and MDVRP. This article discusses solution characteristics of VRPTW and MDVRP algorithms, and their performance. VRPTW algori...
Optimization of Vehicle Routing in Simultaneous Pickup and Delivery Service: A Case study
International Journal of Advances in Scientific Research and Engineering
In this case study, considered the vehicle routing problem with pickup and delivery which is a generalization of the capacitated vehicle routing problem (CVRP). The vehicle routing problem with pickup and delivery (VRPPD) arises whenever pickup demand and delivery demand is to be satisfied by the same vehicle. The problem is encountered in many real life situations. In this paper problem arises from the distribution of beverages and collection of recyclable containers. It can be modeled as a variant of the vehicle routing problem with a heterogeneous vehicle fleet, capacity and volume constraints, and an objective function combining routing distance or minimizing the total travel distance to serve customers located to different locations. Three construction heuristics and an improvement procedure are developed for the problem and designing a set of routes with minimum cost to serve a delivery of beverages and a collection of recyclable material with a fleet of vehicles. The aim of this paper is to develop a vehicle routing Problem (VRP) model that addresses simultaneous pickup and delivery in the beverage distribution. To this effect, a mathematical model is adopted and fitted with real data collected from MOHA Soft drinks Summit Plant located in Ethiopia, and solved using Clark-Wright saving algorithm. The form-to-distance is computed from the data collected from Google Earth and the customer's data from the MOHA. The findings of the study show that the model is feasible and showed an improvement as compared to the current performances of the plant with respect to product distribution and collection and the total distance covered is minimized about 27.79%. The average performances of the model show that on average 5 routes are required to serve customers' demands.
Single-Commodity Vehicle Routing Problem with Pickup and Delivery Service
Mathematical Problems in Engineering, 2008
We present a novel variation of the vehicle routing problem (VRP). Single commodity cargo with pickup and delivery service is considered. Customers are labeled as either cargo sink or cargo source, depending on their pickup or delivery demand. This problem is called a single commodity vehicle routing problem with pickup and delivery service (1-VRPPD). 1-VRPPD deals with multiple vehicles and is the same as the single-commodity traveling salesman problem (1-PDTSP) when the number of vehicles is equal to 1. Since 1-VRPPD specializes VRP, it is hard in the strong sense. Iterative modified simulated annealing (IMSA) is presented along with greedy random-based initial solution algorithm. IMSA provides a good approximation to the global optimum in a large search space. Experiment is done for the instances with different number of customers and their demands. With respect to average values of IMSA execution times, proposed method is appropriate for practical applications.
Heuristics for the routing of trucks with double container loads
2012
This research addresses a problem motivated by a real case study. A carrier must plan the routes of trucks in order to serve importers and exporters. What is original in this vehicle routing problem is the impossibility to separate trucks and containers during customer service and the opportunity to carry up to two containers per truck. Customers may demand more than one container and may be visited more than once. Moreover, according to the carrier’s policy, importers must be served before exporters. In order to address this Vehicle Routing Problem with backhaul and splits, a linear integer programming model is proposed. This research aims to show to what extent an exact algorithm of a state of the art solver can be used to solve this model. Moreover, since some instances are too difficult to solve for the exact algorithm, a number of heuristics is proposed and compared to this algorithm. Finally, the heuristics are compared to the real decisions of the carrier who has motivated th...