A vehicle routing problem with stochastic demand
Operations Research
Mathematics of Operations Research
Robust Solutions to Uncertain Semidefinite Programs
SIAM Journal on Optimization
Evolutionary Optimization Versus Particle Swarm Optimization: Philosophy and Performance Differences
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
Particle swarm optimization-based algorithms for TSP and generalized TSP
Information Processing Letters
A particle swarm optimization algorithm for the multiple-level warehouse layout design problem
Computers and Industrial Engineering
Analysis of the publications on the applications of particle swarm optimisation
Journal of Artificial Evolution and Applications - Regular issue
A particle swarm optimization for the vehicle routing problem with simultaneous pickup and delivery
Computers and Operations Research
Computers and Industrial Engineering
A hybrid differential evolution algorithm to vehicle routing problem with fuzzy demands
Journal of Computational and Applied Mathematics
Optimization using particle swarms with near neighbor interactions
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
Robust solutions of uncertain linear programs
Operations Research Letters
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The Vehicle Routing Problem (VRP) has been thoroughly studied in the last decades. However, the main focus has been on the deterministic version where customer demands are fixed and known in advance. Uncertainty in demand has not received enough consideration. When demands are uncertain, several problems arise in the VRP. For example, there might be unmet customers' demands, which eventually lead to profit loss. A reliable plan and set of routes, after solving the VRP, can significantly reduce the unmet demand costs, helping in obtaining customer satisfaction. This paper investigates a variant of an uncertain VRP in which the customers' demands are supposed to be uncertain with unknown distributions. An advanced Particle Swarm Optimization (PSO) algorithm has been proposed to solve such a VRP. A novel decoding scheme has also been developed to increase the PSO efficiency. Comprehensive computational experiments, along with comparisons with other existing algorithms, have been provided to validate the proposed algorithms.