A distributed adaptive optimization spiking neural P system for approximately solving combinatorial optimization problems.
Jianping DongGexiang ZhangBiao LuoQiang YangDequan GuoHaina RongMing ZhuKang ZhouPublished in: Inf. Sci. (2022)
Keyphrases
- combinatorial optimization problems
- discrete optimization
- combinatorial optimization
- optimization problems
- continuous optimization problems
- bio inspired
- knapsack problem
- metaheuristic
- neuron model
- traveling salesman problem
- spike trains
- hebbian learning
- spiking neural networks
- branch and bound
- job shop scheduling
- ant colony optimization
- spiking neurons
- biologically plausible
- estimation of distribution algorithms
- branch and bound algorithm
- network architecture
- simulated annealing
- job shop scheduling problem
- shortest path problem
- min cost
- evolutionary algorithm
- exact algorithms
- learning rules
- biologically inspired
- feed forward
- cost function
- neural network
- neural models
- optimization methods
- basal ganglia
- benchmark problems
- quadratic programming
- vehicle routing problem