A Genetic Algorithm for the Multidimensional Knapsack Problem
Journal of Heuristics
Inver-over Operator for the TSP
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
New Genetic Local Search Operators for the Traveling Salesman Problem
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
Ant Colony Optimization
Fuzzy Discrete Particle Swarm Optimization for Solving Traveling Salesman Problem
CIT '04 Proceedings of the The Fourth International Conference on Computer and Information Technology
Some issues of designing genetic algorithms for traveling salesman problems
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Particle Swarn Optimization with Fast Local Search for the Blind Traveling Salesman Problem
HIS '05 Proceedings of the Fifth International Conference on Hybrid Intelligent Systems
A hybrid particle swarm optimization for job shop scheduling problem
Computers and Industrial Engineering
A discrete version of particle swarm optimization for flowshop scheduling problems
Computers and Operations Research
Population structure and particle swarm performance
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Population structure and particle swarm performance
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Don't push me! Collision-avoiding swarms
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Particle swarm optimization-based algorithms for TSP and generalized TSP
Information Processing Letters
A discrete particle swarm optimization algorithm for the no-wait flowshop scheduling problem
Computers and Operations Research
The traveling salesman: computational solutions for TSP applications
The traveling salesman: computational solutions for TSP applications
Heuristic information based improved fuzzy discrete PSO method for solving TSP
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Apply the particle swarm optimization to the multidimensional knapsack problem
ICAISC'06 Proceedings of the 8th international conference on Artificial Intelligence and Soft Computing
Particle swarm for the traveling salesman problem
EvoCOP'06 Proceedings of the 6th European conference on Evolutionary Computation in Combinatorial Optimization
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
A Cooperative approach to particle swarm optimization
IEEE Transactions on Evolutionary Computation
Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients
IEEE Transactions on Evolutionary Computation
Comprehensive learning particle swarm optimizer for global optimization of multimodal functions
IEEE Transactions on Evolutionary Computation
An anticentroid-oriented particle swarm algorithm for numerical optimization
AICI'10 Proceedings of the 2010 international conference on Artificial intelligence and computational intelligence: Part II
Diversity Guided Evolutionary Programming: A novel approach for continuous optimization
Applied Soft Computing
Ordinal optimization based approach to the optimal resource allocation of grid computing system
Mathematical and Computer Modelling: An International Journal
SDE: a stochastic coding differential evolution for global optimization
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Adaptive differential evolution with optimization state estimation
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Differential evolution algorithm with PCA-based crossover
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Enhance differential evolution with random walk
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Adaptive genetic algorithm based on density distribution of population
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
A strategy adaptive genetic algorithm for solving the travelling salesman problem
SEMCCO'12 Proceedings of the Third international conference on Swarm, Evolutionary, and Memetic Computing
Space-based initialization strategy for particle swarm optimization
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
A set-based locally informed discrete particle swarm optimization
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Minimizing control variation in nonlinear optimal control
Automatica (Journal of IFAC)
Multi-objective mobile app recommendation: A system-level collaboration approach
Computers and Electrical Engineering
Distributed Query Plan Generation using Particle Swarm Optimization
International Journal of Swarm Intelligence Research
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Particle swarm optimization (PSO) is predominately used to find solutions for continuous optimization problems. As the operators of PSO are originally designed in an n-dimensional continuous space, the advancement of using PSO to find solutions in a discrete space is at a slow pace. In this paper, a novel setbased PSO (S-PSO) method for the solutions of some combinatorial optimization problems (COPs) in discrete space is presented. The proposed S-PSO features the following characteristics. First, it is based on using a set-based representation scheme that enables S-PSO to characterize the discrete search space of COPs. Second, the candidate solution and velocity are defined as a crisp set, and a set with possibilities, respectively. All arithmetic operators in the velocity and position updating rules used in the original PSO are replaced by the operators and procedures defined on crisp sets, and sets with possibilities in S-PSO. The S-PSO method can thus follow a similar structure to the original PSO for searching in a discrete space. Based on the proposed S-PSO method, most of the existing PSO variants, such as the global version PSO, the local version PSO with different topologies, and the comprehensive learning PSO (CLPSO), can be extended to their corresponding discrete versions. These discrete PSO versions based on S-PSO are tested on two famous COPs: the traveling salesman problem and the multidimensional knapsack problem. Experimental results show that the discrete version of the CLPSO algorithm based on S-PSO is promising.