scholarly journals Clustering and heuristics algorithm for the vehicle routing problem with time windows

2022 ◽  
Vol 13 (2) ◽  
pp. 165-184 ◽  
Author(s):  
Andrés Felipe León Villalba ◽  
Elsa Cristina González La Rotta
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
High Performance ◽  
Nearest Neighbor ◽  
Time Windows ◽  
Data Set ◽  
Routing Problem ◽  
Clustering Techniques ◽  
Time Periods ◽  
Heuristics Algorithm

This article presents a novel algorithm based on the cluster first-route second method, which executes a solution through K-means and Optics clustering techniques and Nearest Neighbor and Local Search 2-opt heuristics, for the solution of a vehicle routing problem with time windows (VRPTW). The objective of the problem focuses on reducing distances, supported by the variables of demand, delivery points, capacities, time windows and type of fleet in synergy with the model's taxonomy, based on data referring to deliveries made by a logistics operator in Colombia. As a result, good solutions are generated in minimum time periods after fulfilling the agreed constraints, providing high performance in route generation and solutions for large customer instances. Similarly, the algorithm demonstrates efficiency and competitiveness compared to other methods detailed in the literature, after being benchmarked with the Solomon instance data set, exporting even better results.

Particle Swarm Optimization for Vehicle Routing Problem with Time Windows

2004 ◽  
Vol 471-472 ◽  
pp. 801-805 ◽  
Author(s):  
Yan Wei Zhao ◽  
B. Wu ◽  
W.L. Wang ◽  
Ying Li Ma ◽  
W.A. Wang ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Nearest Neighbor ◽  
Time Windows ◽  
Particle Swarm ◽  
Main Theme ◽  
Nearest Neighbor Algorithm ◽  
Swarm Optimization ◽  
Routing Problem

The investigation of the performance of the Particle Swarm Optimization (PSO) method for Vehicle Routing Problem with Time Windows is the main theme of the paper. “Exchange minus operator” is constructed to compute particle’s velocity. We use Saving algorithm, Nearest Neighbor algorithm, and Solomon insertion heuristics for parameter initialization and apply the “Routing first and Cluster second” strategy for solution generation. By PSO, customers are sorted in an ordered sequence for vehicle assignment and Nearest Neighbor algorithm is used to optimize every vehicle route. In our experiments, two different PSO algorithms (global and local), and three construct algorithms are investigated for omparison. Computational results show that global PSO algorithm with Solomon insertion heuristics is more efficiency than the others.

scholarly journals A mixed-integer linear programming model for the selective full-truckload multi-depot vehicle routing problem with time windows

2021 ◽  
Vol 10 (4) ◽  
pp. 471-486 ◽  
Author(s):  
Karim EL Bouyahyiouy ◽  
Adil Bellabdaoui
Keyword(s):  
Linear Programming ◽  
Vehicle Routing ◽  
Integer Linear Programming ◽  
Vehicle Routing Problem ◽  
Mixed Integer Linear Programming ◽  
Programming Model ◽  
Time Windows ◽  
Mixed Integer ◽  
Data Set ◽  
Routing Problem

This article has studied a full truckload transportation problem in the context of an empty return scenario, particularly an order selection and vehicle routing problem with full truckload, multiple depots and time windows (SFTMDVRPTW). The aim is to develop a solution where a set of truck routes serves a subset of selected transportation demands from a number of full truckload orders to maximize the total profit obtained from those orders. Each truck route is a chain of selected demands to serve, originating at a departure point and terminating at an arriving point of trucks in a way that respects the constraints of availability and time windows. It is not mandatory to serve all orders, and only the profitable ones are selected. In this study, we have formulated the SFTMDVRPTW as a mixed-integer linear programming (MILP) model. Finally, Computational results are conducted on a new data set that contains thirty randomly generated problem instances ranging from 16 to 30 orders using the CPLEX software. The findings prove that our model has provided good solutions in a reasonable time.

scholarly journals Sequential Routing-Loading Algorithm for Optimizing One-Door Container Closed-Loop Logistics Operations

2020 ◽  
Vol 19 (2) ◽  
pp. 122
Author(s):  
Paulina Kus Ariningsih ◽  
Titi Iswari ◽  
Kevin Djoenneady Poetra ◽  
Yoon Mac Kinley Aritonang
Keyword(s):  
Big Data ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Main Tool ◽  
Large Data ◽  
Data Set ◽  
Container Loading ◽  
Routing Problem ◽  
Routing Optimization

One-door container type of vehicle is the main tool for urban logistics in Indonesia which may take the form of truck, car, or motorcycle container. The operations would be more effective when it is performed through pickup-delivery or forward-reverse at a time. However, there is difficulty to optimize the operation of routing and container loading processes in such a system. This article is proposing an improvement for algorithm for sequential routing- loading process which had been tested in the small datasets but not yet tested in the case of big data set and vehicle routing problem with time windows. The improvement algorithm is tested in big data set with the input of the vehicle routing problem with time windows (VRP-TW) using the solution optimization of the Simulated Annealing process with restart point procedure (SA-R) for the routing optimization and Genetic Algorithm (GA) to optimize the container loading algorithm. The large data sets are hypothetical generated data for 800-2500 single-sized products, 4 types of container capacity, and 100-400 consumer spots. As result, the performance of the proposed algorithm in terms of cost is influenced by the number of spots to be visited by the vehicle and the vehicle capacity. Limitations and further analysis are also described in this article.

scholarly journals Metaheuristics for The Solution of Dynamic Vehicle Routing Problem With Time Windows (DVRPTW) With Travel Time Variable

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Nurlita Gamayanti
Keyword(s):  
Travel Time ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Nearest Neighbor ◽  
Time Windows ◽  
New Order ◽  
Metaheuristic Algorithm ◽  
Dynamic Vehicle Routing ◽  
Dynamic Vehicle Routing Problem ◽  
Routing Problem

This research is focusing on the development of metaheuristic algorithm to solve Dynamic Vehicle Routing Problem With Time Windows (DVRPTW) for the service provider of Inter-city Courier. The algorithm is divided into two stages which is static stage and dynamic stage. In the static stage, modified Ant Colony System is developed and in the dynamic stage, Insertion Heuristic is developed. In DVRPTW, vehicle’s routes are raised dynamically based on real time information, for example the reception of new order. To test the performances of the developed metaheuristic algorithm, the author compares the developed algorithm with the nearest neighbor algorithm and with the combination between the nearest neighbor and insertion heuristics algorithm. Experiment is done using Chen’s standard data test. The developed metaheuristic algorithm was applied on the network data of the roads in Surabaya, where the routes generated not only determine the order that the consumer must visit but also determine the routes that must be passed. After the experiment, the author conclude that the developed algorithm generates a better travel time total than the nearest neighbor and the combination between the nearest neighbor and insertion heuristics and can also generate route dynamically to respond to the new order well.

scholarly journals Heuristic Approach For Robust Counterpart Open Capacitated Vehicle Routing Problem With Time Windows

2021 ◽  
Vol 6 (2) ◽  
pp. 53-57
Author(s):  
Evi Yuliza ◽  
Fitri Maya ◽  
Siti Suzlin Supadi
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Nearest Neighbor ◽  
Time Windows ◽  
Heuristic Approach ◽  
Routing Problem ◽  
Capacitated Vehicle Routing Problem ◽  
Robust Counterpart ◽  
Engine Failure ◽  
Capacitated Vehicle

Garbage is one of the environmental problems. The process of transporting garbage sometimes occurs delays such as congestion and engine failure. Robust optimization model called a robust counterpart open capacitated vehicle routing problem (RCOCVRP) with time windows was formulated to get over this delays. This model has formulated with the limitation of vehicle capacity and time windows with an uncertainty of waste volume and travel time. The RCOCVRP model with time windows is solved by a heuristic approach. The heuristic approach used to solve the RCOCVRP model with time windows uses the nearest neighbor and the cheapest insertion heuristic algorithm. The RCOCVRP with time windows model is implemented on the problem of transporting waste in Sako sub-district. The solutions of these two heuristic approaches are compared and analyzed. The RCOCVRP model with time windows to optimize the route problems of waste transport vehicles that is solved using the cheapest insertion heuristics algorithm is more effective than the nearest neighbor method.

A hybrid algorithm for electric vehicle routing problem with nonlinear charging

2021 ◽  
pp. 1-20
Author(s):  
Jiawen Deng ◽  
Junqing Li ◽  
Chengyou Li ◽  
Yuyan Han ◽  
Qingsong Liu ◽  
...  
Keyword(s):  
Vehicle Routing ◽  
Electric Vehicle ◽  
Vehicle Routing Problem ◽  
Hybrid Algorithm ◽  
High Performance ◽  
Time Windows ◽  
Routing Problem ◽  
Battery Degradation ◽  
Encoding Method ◽  
Charging Stations

This paper investigates the electric vehicle routing problem with time windows and nonlinear charging constraints (EVRPTW-NL), which is more practical due to battery degradation. A hybrid algorithm combining an improved differential evolution and several heuristic (IDE) is proposed to solve this problem, where the weighted sum of the total trip time and customer satisfaction value is minimized. In the proposed algorithm, a special encoding method is presented that considers charging stations features. Then, a battery charging adjustment (BCA) strategy is integrated to decrease the charging time. Furthermore, a novel negative repair strategy is embedded to make the solution feasible. Finally, several instances are generated to examine the effectiveness of the IDE algorithm. The high performance of the IDE algorithm is shown in comparison with two efficient algorithms.

scholarly journals A hybrid ant colony algorithm based on multiple strategies for the vehicle routing problem with time windows

2021 ◽  
Author(s):  
Hongguang Wu ◽  
Yuelin Gao ◽  
Wanting Wang ◽  
Ziyu Zhang
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Ant Colony Algorithm ◽  
Time Window ◽  
Time Windows ◽  
Ant Colony ◽  
Routing Problem ◽  
Multiple Strategies ◽  
Hard Time ◽  
Mutation Operation

AbstractIn this paper, we propose a vehicle routing problem with time windows (TWVRP). In this problem, we consider a hard time constraint that the fleet can only serve customers within a specific time window. To solve this problem, a hybrid ant colony (HACO) algorithm is proposed based on ant colony algorithm and mutation operation. The HACO algorithm proposed has three innovations: the first is to update pheromones with a new method; the second is the introduction of adaptive parameters; and the third is to add the mutation operation. A famous Solomon instance is used to evaluate the performance of the proposed algorithm. Experimental results show that HACO algorithm is effective against solving the problem of vehicle routing with time windows. Besides, the proposed algorithm also has practical implications for vehicle routing problem and the results show that it is applicable and effective in practical problems.

scholarly journals The last-mile vehicle routing problem with delivery options

OR Spectrum ◽  
2021 ◽  
Author(s):  
Christian Tilk ◽  
Katharina Olkis ◽  
Stefan Irnich
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Resource Constraints ◽  
Time Window ◽  
Time Windows ◽  
Service Level ◽  
Optimal Solutions ◽  
Routing Problem ◽  
Common Location ◽  
Delivery Options

AbstractThe ongoing rise in e-commerce comes along with an increasing number of first-time delivery failures due to the absence of the customer at the delivery location. Failed deliveries result in rework which in turn has a large impact on the carriers’ delivery cost. In the classical vehicle routing problem (VRP) with time windows, each customer request has only one location and one time window describing where and when shipments need to be delivered. In contrast, we introduce and analyze the vehicle routing problem with delivery options (VRPDO), in which some requests can be shipped to alternative locations with possibly different time windows. Furthermore, customers may prefer some delivery options. The carrier must then select, for each request, one delivery option such that the carriers’ overall cost is minimized and a given service level regarding customer preferences is achieved. Moreover, when delivery options share a common location, e.g., a locker, capacities must be respected when assigning shipments. To solve the VRPDO exactly, we present a new branch-price-and-cut algorithm. The associated pricing subproblem is a shortest-path problem with resource constraints that we solve with a bidirectional labeling algorithm on an auxiliary network. We focus on the comparison of two alternative modeling approaches for the auxiliary network and present optimal solutions for instances with up to 100 delivery options. Moreover, we provide 17 new optimal solutions for the benchmark set for the VRP with roaming delivery locations.

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