Co-evolving parasites improve simulated evolution as an optimization procedure
CNLS '89 Proceedings of the ninth annual international conference of the Center for Nonlinear Studies on Self-organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks on Emergent computation
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Genetic AlgorithmsNumerical Optimizationand Constraints
Proceedings of the 6th International Conference on Genetic Algorithms
A Cooperative Coevolutionary Approach to Function Optimization
PPSN III Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature
Comparison between Genetic Algorithms and Particle Swarm Optimization
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
Search Space Reduction in QoS Routing
ICDCS '99 Proceedings of the 19th IEEE International Conference on Distributed Computing Systems
Co-evolutionary particle swarm optimization to solve min-max problems
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Two techniques for fast computation of constrained shortest paths
IEEE/ACM Transactions on Networking (TON)
Solving shortest path problem using particle swarm optimization
Applied Soft Computing
Comparison among five evolutionary-based optimization algorithms
Advanced Engineering Informatics
A genetic algorithm for shortest path routing problem and the sizing of populations
IEEE Transactions on Evolutionary Computation
Routing subject to quality of service constraints in integrated communication networks
IEEE Network: The Magazine of Global Internetworking
A scalable algorithm for finding delay-constraint least-cost end-to-end path
ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part II
A scalable method for DCLC problem using hierarchical MDP model
Computer Communications
| Hi-index | 0.01 |
This paper presents a co-evolutionary particle swarm optimization (PSO) algorithm, hybridized with noising metaheuristics, for solving the delay constrained least cost (DCLC) path problem, i.e., shortest-path problem with a delay constraint on the total "cost" of the optimal path. The proposed algorithm uses the principle of Lagrange relaxation based aggregated cost. It essentially consists of two concurrent PSOs for solving the resulting minimization-maximization problem. The main PSO is designed as a hybrid PSO-noising metaheuristics algorithm for efficient global search to solve the minimization part of the DCLC-Lagrangian relaxation by finding multiple shortest paths between a source-destination pair. The auxiliary/second PSO is a co-evolutionary PSO to obtain the optimal Lagrangian multiplier for solving the maximization part of the Lagrangian relaxation problem. For the main PSO, a novel heuristics-based path encoding/decoding scheme has been devised for representation of network paths as particles. The simulation results on several networks with random topologies illustrate the efficiency of the proposed hybrid algorithm for the constrained shortest path computation problems.