Solving the multi-objective flexible job shop scheduling problem with a novel parallel branch and bound algorithm.
José Carlos Soto MonterrubioBernabé DorronsoroHéctor J. Fraire H.Laura Cruz ReyesClaudia Gómez SantillánNelson Rangel-ValdezPublished in: Swarm Evol. Comput. (2020)
Keyphrases
- multi objective
- branch and bound algorithm
- combinatorial optimization
- lower bound
- finding an optimal solution
- evolutionary algorithm
- branch and bound
- variable ordering
- multi objective optimization
- objective function
- optimization algorithm
- upper bound
- optimal solution
- integer variables
- np hard
- test problems
- search tree
- lower bounding
- particle swarm optimization
- randomly generated problems
- precedence constraints
- multiple objectives
- genetic algorithm
- lagrangian relaxation
- mixed integer linear programming
- bi objective
- nsga ii
- simulated annealing
- upper bounding
- search algorithm
- single machine scheduling problem
- optimization problems
- maximum clique
- scheduling problem
- weighted max sat
- branch and bound method
- strongly np hard
- column generation
- multi objective evolutionary algorithms
- max sat
- linear program
- traveling salesman problem
- search space