Swarm intelligence
A genetic algorithm for the vehicle routing problem
Computers and Operations Research
D-Ants: savings based ants divide and conquer the vehicle routing problem
Computers and Operations Research
Computers and Operations Research
Optimization using particle swarms with near neighbor interactions
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
A hybrid genetic algorithm for the vehicle routing problem with simultaneous pickup and delivery
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Application of PSO-RBF neural network in network intrusion detection
IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
Expert Systems with Applications: An International Journal
ANTS'10 Proceedings of the 7th international conference on Swarm intelligence
Bio-inspired metaheuristics for the vehicle routing problem
ACS'09 Proceedings of the 9th WSEAS international conference on Applied computer science
A new geometric shape-based genetic clustering algorithm for the multi-depot vehicle routing problem
Expert Systems with Applications: An International Journal
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
A genetic algorithm for the simultaneous delivery and pickup problems with time window
Computers and Industrial Engineering
Vehicle routing problem with uncertain demands: An advanced particle swarm algorithm
Computers and Industrial Engineering
New best solutions to VRPSPD benchmark problems by a perturbation based algorithm
Expert Systems with Applications: An International Journal
Computers and Operations Research
Computers and Industrial Engineering
Evaluation of vehicle routing problem with time windows by using metaheuristics algorithm
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
Bio-inspired multi-agent systems for reconfigurable manufacturing systems
Engineering Applications of Artificial Intelligence
Vehicle routing problem with time windows based on adaptive bacterial foraging optimization
ICIC'12 Proceedings of the 8th international conference on Intelligent Computing Theories and Applications
A hybrid meta-heuristic algorithm for optimization of crew scheduling
Applied Soft Computing
Computers and Industrial Engineering
Optimization of the material flow in a manufacturing plant by use of artificial bee colony algorithm
Expert Systems with Applications: An International Journal
Journal of Intelligent Manufacturing
A Genetic Algorithm-based optimization model for supporting green transportation operations
Expert Systems with Applications: An International Journal
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This paper proposes a formulation of the vehicle routing problem with simultaneous pickup and delivery (VRPSPD) and a particle swarm optimization (PSO) algorithm for solving it. The formulation is a generalization of three existing VRPSPD formulations. The main PSO algorithm is developed based on GLNPSO, a PSO algorithm with multiple social structures. A random key-based solution representation and decoding method is proposed for implementing PSO for VRPSPD. The solution representation for VRPSPD with n customers and m vehicles is a (n+2m)-dimensional particle. The decoding method starts by transforming the particle to a priority list of customers to enter the route and a priority matrix of vehicles to serve each customer. The vehicle routes are constructed based on the customer priority list and vehicle priority matrix. The proposed algorithm is tested using three benchmark data sets available from the literature. The computational result shows that the proposed method is competitive with other published results for solving VRPSPD. Some new best known solutions of the benchmark problem are also found by the proposed method. Scope and Purpose: This paper applies a real-value version of particle swarm optimization (PSO) algorithm for solving the vehicle routing problem with simultaneous pickup and delivery (VRPSPD). The VRPSPD formulation is reformulated and generalized from three existing formulations in the literature. The purposes of this paper are to explain the mechanism of the PSO for solving VRPSPD and to demonstrate the effectiveness of the proposed method.