scholarly journals Vehicle routing problem with time constraints

2015 ◽  
Vol 11 (4) ◽  
Author(s):  
Farhana Johar ◽  
Chris Potts ◽  
Julia Bennell
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Heuristic Algorithms ◽  
Time Constraints ◽  
Neighborhood Search ◽  
Benchmark Problems ◽  
Routing Problem ◽  
Significant Saving ◽  
Constructive Heuristic ◽  
Initial Feasible Solution

This paper addresses the Vehicle Routing Problem (VRP) with time constraints which been solved by several heuristic algorithms. The problem starting at the depot where the customer orders which associated with due date determined by customer, are released with different point of time. Ideally, to avoid any lateness in delivery process, the orders need to be delivered as soon as it released and available at the depot. However, this may increase the traveling cost because one vehicle needs to go and come back to depot for the other deliveries which this can be saved by batching the deliveries. Therefore, the study will focus on minimizing the tradeoff between traveling and tardiness costs.  Literatures show that implementing the heuristic algorithms for solving various instances of VRPs manage to minimize the distribution cost within the reasonable computing times. An initial feasible solution was generated using a constructive heuristic. The solution then was improved by several metaheuristic algorithms were developed for solving the problem studied; Variable Neighborhood Search, Large Neighborhood Search and Tabu Search. To cater with the problem studied, a modification to the benchmark problems of Solomon has been done. The performance of the algorithms can be seen through the comparison of the solution obtained.  The results showed that there is a significant saving in producing the least cost solution and manually constructed routes are very ineffective.

scholarly journals Solving Practical Vehicle Routing Problem with Time Windows Using Metaheuristic Algorithms

1970 ◽  
Vol 24 (4) ◽  
pp. 343-351 ◽  
Author(s):  
Filip Taner ◽  
Ante Galić ◽  
Tonči Carić
Keyword(s):  
Vehicle Routing ◽  
Real World ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Iterated Local Search ◽  
Metaheuristic Algorithms ◽  
Benchmark Problems ◽  
Routing Problem ◽  
Constructive Heuristics ◽  
Initial Feasible Solution

This paper addresses the Vehicle Routing Problem with Time Windows (VRPTW) and shows that implementing algorithms for solving various instances of VRPs can significantly reduce transportation costs that occur during the delivery process. Two metaheuristic algorithms were developed for solving VRPTW: Simulated Annealing and Iterated Local Search. Both algorithms generate initial feasible solution using constructive heuristics and use operators and various strategies for an iterative improvement. The algorithms were tested on Solomon’s benchmark problems and real world vehicle routing problems with time windows. In total, 44 real world problems were optimized in the case study using described algorithms. Obtained results showed that the same distribution task can be accomplished with savings up to 40% in the total travelled distance and that manually constructed routes are very ineffective.

scholarly journals Time-dependent vehicle routing problem with backhaul with FIFO assumption: Variable neighborhood search and mat-heuristic variable neighborhood search algorithms

2021 ◽  
pp. 15-36 ◽  
Author(s):  
Esmaeil Akhondi Bajegani ◽  
Naser Mollaverdi ◽  
Mahdi Alinaghian
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Variable Neighborhood Search ◽  
Heuristic Algorithms ◽  
Time Dependent ◽  
Superior Performance ◽  
Neighborhood Search ◽  
Test Problems ◽  
Routing Problem ◽  
Study Results

This paper presents a mathematical model for a single depot, time-dependent vehicle routing problem with backhaul considering the first in first out (FIFO) assumption. As the nature of the problem is NP-hard, variable neighborhood search (VNS) meta-heuristic and mat-heuristic algorithms have been designed. For test problems with large scales, obtained results highlight the superior performance of the mat-heuristic algorithm compared with that of the other algorithm. Finally a case study at the post office of Khomeini-Shahr town, Iran, was considered. Study results show a reduction of roughly 19% (almost 45 min) in the travel time of the vehicle.

scholarly journals A hybrid metaheuristic for solving asymmetric distance-constrained vehicle routing problem

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Ha-Bang Ban ◽  
Phuong Khanh Nguyen
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Natural Extension ◽  
Solution Space ◽  
Neighborhood Search ◽  
Np Hard ◽  
Routing Problem ◽  
Hybrid Metaheuristic ◽  
Asymmetric Distance ◽  
Constrained Vehicle Routing

AbstractThe Asymmetric Distance-Constrained Vehicle Routing Problem (ADVRP) is NP-hard as it is a natural extension of the NP-hard Vehicle Routing Problem. In ADVRP problem, each customer is visited exactly once by a vehicle; every tour starts and ends at a depot; and the traveled distance by each vehicle is not allowed to exceed a predetermined limit. We propose a hybrid metaheuristic algorithm combining the Randomized Variable Neighborhood Search (RVNS) and the Tabu Search (TS) to solve the problem. The combination of multiple neighborhoods and tabu mechanism is used for their capacity to escape local optima while exploring the solution space. Furthermore, the intensification and diversification phases are also included to deliver optimized and diversified solutions. Extensive numerical experiments and comparisons with all the state-of-the-art algorithms show that the proposed method is highly competitive in terms of solution quality and computation time, providing new best solutions for a number of instances.

scholarly journals A Modified Harmony Search Algorithm for Solving the Dynamic Vehicle Routing Problem with Time Windows

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Shifeng Chen ◽  
Rong Chen ◽  
Jian Gao
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Search Algorithm ◽  
Time Windows ◽  
Harmony Search ◽  
Population Diversity ◽  
Benchmark Problems ◽  
Dynamic Vehicle Routing ◽  
Dynamic Vehicle Routing Problem ◽  
Routing Problem

The Vehicle Routing Problem (VRP) is a classical combinatorial optimization problem. It is usually modelled in a static fashion; however, in practice, new requests by customers arrive after the initial workday plan is in progress. In this case, routes must be replanned dynamically. This paper investigates the Dynamic Vehicle Routing Problem with Time Windows (DVRPTW) in which customers’ requests either can be known at the beginning of working day or occur dynamically over time. We propose a hybrid heuristic algorithm that combines the harmony search (HS) algorithm and the Variable Neighbourhood Descent (VND) algorithm. It uses the HS to provide global exploration capabilities and uses the VND for its local search capability. In order to prevent premature convergence of the solution, we evaluate the population diversity by using entropy. Computational results on the Lackner benchmark problems show that the proposed algorithm is competitive with the best existing algorithms from the literature.

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