Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
P-Complete Approximation Problems
Journal of the ACM (JACM)
Swarm intelligence
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Tabu Search
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
QAPLIB – A Quadratic Assignment ProblemLibrary
Journal of Global Optimization
FANT: Fast ant system
Solving Project Scheduling Problems by Minimum Cut Computations
Management Science
Ant Colony Optimization
Handbook of Scheduling: Algorithms, Models, and Performance Analysis
Handbook of Scheduling: Algorithms, Models, and Performance Analysis
The Traveling Salesman Problem: A Computational Study (Princeton Series in Applied Mathematics)
The Traveling Salesman Problem: A Computational Study (Princeton Series in Applied Mathematics)
Minimum Interference Channel Assignment in Multiradio Wireless Mesh Networks
IEEE Transactions on Mobile Computing
A probabilistic memetic framework
IEEE Transactions on Evolutionary Computation
Paper: Robust taboo search for the quadratic assignment problem
Parallel Computing
No free lunch theorems for optimization
IEEE Transactions on Evolutionary Computation
Image segmentation using evolutionary computation
IEEE Transactions on Evolutionary Computation
Data mining with an ant colony optimization algorithm
IEEE Transactions on Evolutionary Computation
Ant colony optimization for resource-constrained project scheduling
IEEE Transactions on Evolutionary Computation
Ant colony optimization for routing and load-balancing: survey and new directions
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Information Sciences: an International Journal
Flexible job shop scheduling problem by chemical-reaction optimization algorithm
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing
A novel chemistry based metaheuristic optimization method for mining of classification rules
Expert Systems with Applications: An International Journal
Chemical reaction optimization with greedy strategy for the 0-1 knapsack problem
Applied Soft Computing
Journal of Parallel and Distributed Computing
Particle swarm optimization with increasing topology connectivity
Engineering Applications of Artificial Intelligence
A hybrid algorithm based on particle swarm and chemical reaction optimization
Expert Systems with Applications: An International Journal
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We encounter optimization problems in our daily lives and in various research domains. Some of them are so hard that we can, at best, approximate the best solutions with (meta-) heuristic methods. However, the huge number of optimization problems and the small number of generally acknowledged methods mean that more metaheuristics are needed to fill the gap. We propose a new metaheuristic, called chemical reaction optimization (CRO), to solve optimization problems. It mimics the interactions of molecules in a chemical reaction to reach a low energy stable state. We tested the performance of CRO with three nondeterministic polynomial-time hard combinatorial optimization problems. Two of them were traditional benchmark problems and the other was a real-world problem. Simulation results showed that CRO is very competitive with the few existing successful metaheuristics, having outperformed them in some cases, and CRO achieved the best performance in the real-world problem. Moreover, with the No-Free-Lunch theorem, CRO must have equal performance as the others on average, but it can outperform all other metaheuristics when matched to the right problem type. Therefore, it provides a new approach for solving optimization problems. CRO may potentially solve those problems which may not be solvable with the few generally acknowledged approaches.