The time dependent vehicle routing problem with time windows: Benchmark problems, an efficient solution algorithm, and solution characteristics

2012 ◽  
Vol 48 (3) ◽  
pp. 616-636 ◽  
Author(s):  
Miguel Andres Figliozzi
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Efficient Solution ◽  
Time Windows ◽  
Solution Algorithm ◽  
Time Dependent ◽  
Benchmark Problems ◽  
Routing Problem

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.

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.

On-Line Vehicle Routing with Time Windows: Optimization-Based Heuristics Approach for Freight Demands Requested in Real-Time

1998 ◽  
Vol 1617 (1) ◽  
pp. 171-178 ◽  
Author(s):  
How-Ming Shieh ◽  
Ming-Der May
Keyword(s):  
Local Search ◽  
Vehicle Routing ◽  
Real Time ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Benchmark Problems ◽  
Routing Problem ◽  
Anytime Algorithm ◽  
Search Heuristics ◽  
On Line

The problem of the on-line version of the vehicle routing problem with time windows (VRPTW) differs from the traditional off-line problem in the dynamical arrival of requests and the execution of the partial tour during the run time. The study develops an on-line optimization-based heuristic that combined the concepts of the “on-line algorithm,” “anytime algorithm,” and local search heuristics to solve the on-line version of VRPTW. The solution heuristic is evaluated with modified Solomon’s problems. By comparing with these benchmark problems, the different results between on-line and off-line algorithms are indicated.

A Hybrid Algorithm for the Multi-Objective Time Dependent Vehicle Routing Problem

2014 ◽  
Vol 505-506 ◽  
pp. 1071-1075
Author(s):  
Yi Sun ◽  
Yue Chen ◽  
Chang Chun Pan ◽  
Gen Ke Yang
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Hybrid Algorithm ◽  
Time Windows ◽  
Time Dependent ◽  
Ant Colony System ◽  
Optimal Solutions ◽  
Test Results ◽  
Routing Problem ◽  
Traffic Conditions

This paper presents a real road network case based on the time dependent vehicle routing problem with time windows (TDVRPTW), which involves optimally routing a fleet of vehicles with fixed capacity when traffic conditions are time dependent and services at customers are only available in their own time tables. A hybrid algorithm based on the Genetic Algorithm (GA) and the Multi Ant Colony System (MACS) is introduced in order to find optimal solutions that minimize two hierarchical objectives: the number of tours and the total travel cost. The test results show that the integrated algorithm outperforms both of its traditional ones in terms of the convergence speed towards optimal solutions.

scholarly journals TDGVRPSTW of Fresh Agricultural Products Distribution: Considering Both Economic Cost and Environmental Cost

2021 ◽  
Vol 11 (22) ◽  
pp. 10579
Author(s):  
Daqing Wu ◽  
Chenxiang Wu
Keyword(s):  
Genetic Algorithm ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Economic Cost ◽  
Agricultural Products ◽  
Time Dependent ◽  
Environmental Cost ◽  
Routing Problem ◽  
Measure Function

The time-dependent vehicle routing problem of time windows of fresh agricultural products distribution have been studied by considering both economic cost and environmental cost. A calculation method for road travel time across time periods is designed in this study. A freshness measure function of agricultural products and a measure function of carbon emission rate are employed by considering time-varying vehicle speeds, fuel consumptions, carbon emissions, perishable agricultural products, customers’ time windows, and minimum freshness. A time-dependent green vehicle routing problem with soft time windows (TDGVRPSTW) model is formulated. The object of the TDGVRPSTW model is to minimize the sum of economic cost and environmental cost. According to the characteristics of the model, a new variable neighborhood adaptive genetic algorithm is designed, which integrates the global search ability of the genetic algorithm and the local search ability of the variable neighborhood descent algorithm. Finally, the experimental data show that the proposed approaches effectively avoid traffic congestions, reduce total distribution costs, and promote energy conservation and emission reduction.

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