Scheduling problems and traveling salesman: the genetic edge recombination
Proceedings of the third international conference on Genetic algorithms
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem
Annals of Operations Research - Special issue on Tabu search
An introduction to genetic algorithms
An introduction to genetic algorithms
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Evolutionary Optimization in Dynamic Environments
Evolutionary Optimization in Dynamic Environments
Applying Population Based ACO to Dynamic Optimization Problems
ANTS '02 Proceedings of the Third International Workshop on Ant Algorithms
Real-Time Dispatching of Guided and Unguided Automobile Service Units with Soft Time Windows
ESA '02 Proceedings of the 10th Annual European Symposium on Algorithms
Drive: Dynamic Routing of Independent Vehicles
Operations Research
Parallel Tabu Search for Real-Time Vehicle Routing and Dispatching
Transportation Science
Diversion Issues in Real-Time Vehicle Dispatching
Transportation Science
Notes on dynamic vehicle routing - the state of the art -
Notes on dynamic vehicle routing - the state of the art -
A reactive method for real time dynamic vehicle routing problem
ICTAI '00 Proceedings of the 12th IEEE International Conference on Tools with Artificial Intelligence
The Granular Tabu Search and Its Application to the Vehicle-Routing Problem
INFORMS Journal on Computing
Multi-Objective Genetic Algorithms for Vehicle Routing Problem with Time Windows
Applied Intelligence
Dynamic Vehicle Routing Based on Online Traffic Information
Transportation Science
Exploiting Knowledge About Future Demands for Real-Time Vehicle Dispatching
Transportation Science
Dynamic vehicle routing with stochastic requests
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
The Vehicle Routing Problem with Real-Time Travel Times
Proceedings of the 2008 conference on Techniques and Applications for Mobile Commerce: Proceedings of TAMoCo 2008
ANTS'10 Proceedings of the 7th international conference on Swarm intelligence
Flexible variable neighborhood search in dynamic vehicle routing
EvoApplications'11 Proceedings of the 2011 international conference on Applications of evolutionary computation - Volume Part I
i-KNOW '11 Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies
Portable autonomous walk calibration for 4-legged robots
Applied Intelligence
On the impact of real-time information on field service scheduling
Decision Support Systems
Performance evaluation of evolutionary heuristics in dynamic environments
Applied Intelligence
A Flexible and Adaptive Hyper-heuristic Approach for (Dynamic) Capacitated Vehicle Routing Problems
Fundamenta Informaticae - Emergent Computing
A Multi-Agent Taxi Dispatching System
International Journal of Agent Technologies and Systems
Multi-environmental cooperative parallel metaheuristics for solving dynamic optimization problems
The Journal of Supercomputing
Cooperative particle swarm optimization for multiobjective transportation planning
Applied Intelligence
Hi-index | 0.00 |
Many difficult combinatorial optimization problems have been modeled as static problems. However, in practice, many problems are dynamic and changing, while some decisions have to be made before all the design data are known. For example, in the Dynamic Vehicle Routing Problem (DVRP), new customer orders appear over time, and new routes must be reconfigured while executing the current solution. Montemanni et al. [1] considered a DVRP as an extension to the standard vehicle routing problem (VRP) by decomposing a DVRP as a sequence of static VRPs, and then solving them with an ant colony system (ACS) algorithm.This paper presents a genetic algorithm (GA) methodology for providing solutions for the DVRP model employed in [1]. The effectiveness of the proposed GA is evaluated using a set of benchmarks found in the literature. Compared with a tabu search approach implemented herein and the aforementioned ACS, the proposed GA methodology performs better in minimizing travel costs.