A Pareto-based collaborative multi-objective optimization algorithm for energy-efficient scheduling of distributed permutation flow-shop with limited buffers.
Chao LuYuanxiang HuangLeilei MengLiang GaoBiao ZhangJiajun ZhouPublished in: Robotics Comput. Integr. Manuf. (2022)
Keyphrases
- multi objective
- optimization algorithm
- energy efficient
- scheduling problem
- flowshop
- wireless sensor networks
- evolutionary algorithm
- unrelated parallel machines
- multi objective optimization
- energy consumption
- multiple objectives
- job shop
- multiobjective optimization
- setup times
- sensor networks
- sequence dependent setup times
- single machine
- differential evolution
- parallel machines
- optimization method
- energy efficiency
- processing times
- manufacturing cell
- base station
- objective function
- particle swarm optimization
- artificial bee colony
- genetic algorithm
- tabu search
- np hard
- distributed systems
- precedence constraints
- routing protocol
- pareto optimal solutions
- special case
- particle swarm optimization pso
- sensor nodes
- pareto optimal
- data transmission
- peer to peer
- resource allocation
- evolutionary computation
- metaheuristic
- optimization problems
- nsga ii
- fitness function