A genetic algorithm for family and job scheduling in a flowline-based manufacturing cell
ICC&IE-94 Selected papers from the 16th annual conference on Computers and industrial engineering
Group scheduling on two cells with intercell movement
Computers and Operations Research
The ant colony optimization meta-heuristic
New ideas in optimization
Two-machine flowshop group scheduling problem
Computers and Operations Research
Ant Colony Optimization
Ant colony optimization for multi-objective flow shop scheduling problem
Computers and Industrial Engineering
Computers and Operations Research
Total flow time minimization in a flowshop sequence-dependent group scheduling problem
Computers and Operations Research
Computers and Industrial Engineering - Special issue: Group technology/cellular manufacturing
Expert Systems with Applications: An International Journal
Two-machine group scheduling problems in discrete parts manufacturing with sequence-dependent setups
Computers and Operations Research
Scheduling groups of jobs in the two-machine flow shop
Mathematical and Computer Modelling: An International Journal
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In this paper, cellular manufacturing scheduling problems are studied. The objective is to minimize makespan (Cmax) considering part family in the manufacturing cell flow line where the setup times are sequence dependent. Minimizing Cmax will result in the increment of output rate and the speed of manufacturing systems which is the main goal of such systems. This problem is solved using Ant Colony Optimization (ACO), Genetic Algorithm (GA) operators, and local search technique. To show the validity of proposed approach, it is compared with a tailor-made heuristic algorithm, called SVS. The obtained results indicate that the proposed method is quite fast and efficient.