MOGSABAT: a metaheuristic hybrid algorithm for solving multi-objective optimisation problems.
Iraq TariqH. A. AlsattarA. A. ZaidanB. B. ZaidanM. R. Abu BakarR. T. MohammedOsamah Shihab AlbahriM. A. AlsalemAhmed Shihab AlbahriPublished in: Neural Comput. Appl. (2020)
Keyphrases
- hybrid algorithm
- metaheuristic
- optimisation problems
- particle swarm
- multi objective
- particle swarm optimization
- simulated annealing
- tabu search
- combinatorial optimization
- ant colony optimization
- evolutionary algorithm
- hybrid algorithms
- genetic algorithm
- evolutionary computation
- optimization method
- optimisation algorithm
- optimization problems
- benchmark problems
- pso algorithm
- differential evolution
- particle swarm optimisation
- particle swarm optimization pso
- ant colony optimisation
- premature convergence
- particle swarm optimization algorithm
- swarm intelligence
- optimization algorithm
- optimal solution
- multi objective optimization
- global optimization
- hybrid method
- vehicle routing problem
- solution space
- objective function
- nature inspired
- artificial bee colony algorithm
- benchmark instances
- search capabilities
- multiobjective optimization
- convergence speed
- nsga ii
- initial population
- optimization methods
- bi objective
- genetic programming
- fitness function
- traveling salesman problem
- evolution strategy
- branch and bound
- initial solution
- genetic algorithm ga
- global search
- test problems
- np hard
- solution quality
- job shop scheduling problem
- mutation operator
- estimation of distribution algorithms
- artificial bee colony
- ant colony optimization algorithm
- feasible solution
- search procedure