Parallel savings based heuristics for the delivery problem
Operations Research
Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem
Annals of Operations Research - Special issue on Tabu search
A tabu search heuristic for the vehicle routing problem
Management Science
A Subpath Ejection Method for the Vehicle Routing Problem
Management Science
A tabu search algorithm for the vehicle routing problem
Computers and Operations Research
Classical heuristics for the capacitated VRP
The vehicle routing problem
Metaheuristics for the capacitated VRP
The vehicle routing problem
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Artficial Immune Systems and Their Applications
Artficial Immune Systems and Their Applications
Artificial Immune Systems: A New Computational Intelligence Paradigm
Artificial Immune Systems: A New Computational Intelligence Paradigm
A Savings Based Ant System For The Vehicle Routing Problem
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
A genetic algorithm for the vehicle routing problem
Computers and Operations Research
A backtracking adaptive threshold accepting algorithm for the vehicle routing problem
Systems Analysis Modelling Simulation
The Granular Tabu Search and Its Application to the Vehicle-Routing Problem
INFORMS Journal on Computing
D-Ants: savings based ants divide and conquer the vehicle routing problem
Computers and Operations Research
Very large-scale vehicle routing: new test problems, algorithms, and results
Computers and Operations Research
Solving the vehicle routing problem with adaptive memory programming methodology
Computers and Operations Research
Expanding Neighborhood GRASP for the Traveling Salesman Problem
Computational Optimization and Applications
A general heuristic for vehicle routing problems
Computers and Operations Research
Active-guided evolution strategies for large-scale capacitated vehicle routing problems
Computers and Operations Research
Active guided evolution strategies for large-scale vehicle routing problems with time windows
Computers and Operations Research
Journal of Global Optimization
A review of particle swarm optimization. Part I: background and development
Natural Computing: an international journal
A hybrid genetic algorithm for the capacitated vehicle routing problem
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Expert Systems with Applications: An International Journal
Multi-basin particle swarm intelligence method for optimal calibration of parametric Lévy models
Expert Systems with Applications: An International Journal
Hybrid particle swarm optimization for vehicle routing problem with time windows
MAMECTIS/NOLASC/CONTROL/WAMUS'11 Proceedings of the 13th WSEAS international conference on mathematical methods, computational techniques and intelligent systems, and 10th WSEAS international conference on non-linear analysis, non-linear systems and chaos, and 7th WSEAS international conference on dynamical systems and control, and 11th WSEAS international conference on Wavelet analysis and multirate systems: recent researches in computational techniques, non-linear systems and control
Multiple Phase Neighborhood Search-GRASP for the Capacitated Vehicle Routing Problem
Expert Systems with Applications: An International Journal
Application of particle swarm optimization and perceptual map to tourist market segmentation
Expert Systems with Applications: An International Journal
Software framework for vehicle routing problem with hybrid metaheuristic algorithms
ACC'11/MMACTEE'11 Proceedings of the 13th IASME/WSEAS international conference on Mathematical Methods and Computational Techniques in Electrical Engineering conference on Applied Computing
Expert Systems with Applications: An International Journal
An improved hybrid particle swarm optimization algorithm for fuzzy p-hub center problem
Computers and Industrial Engineering
EvoCOP'13 Proceedings of the 13th European conference on Evolutionary Computation in Combinatorial Optimization
Computers and Industrial Engineering
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Hi-index | 12.06 |
Usually in a genetic algorithm, individual solutions do not evolve during their lifetimes: they are created, evaluated, they may be selected as parents to new solutions and they are destroyed. However, research into memetic algorithms and genetic local search has shown that performance may be improved if solutions are allowed to evolve during their own lifetimes. We propose that this solution improvement phase can be assisted by knowledge stored within the parent solutions, effectively allowing parents to teach their offspring how to improve their fitness. In this paper, the evolution of each individual of the total population, which consists of the parents and the offspring, is realized with the use of a Particle Swarm Optimizer where each of them has to improve its physical movement following the basic principles of Particle Swarm Optimization until it will obtain the requirements to be selected as a parent. Thus, the knowledge of each of the parents, especially of a very fit parent, has the possibility to be transferred to its offspring and to the offspring of the whole population, and by this way the proposed algorithm has the possibility to explore more effectively the solution space. These ideas are applied in a classic combinatorial optimization problem, the vehicle routing problem, with very good results when applied to two classic benchmark sets of instances.