A comparative evaluation of heuristic line balancing techniques
Management Science
Optimally balancing large assembly lines with `FABLE'
Management Science
Eureka: a hybrid system for assembly line balancing
Management Science
A Hybrid Genetic Algorithm for Assembly Line Balancing
Journal of Heuristics
Ant Algorithms for Assembly Line Balancing
ANTS '02 Proceedings of the Third International Workshop on Ant Algorithms
Ant Colony Optimization
Beam-ACO applied to assembly line balancing
ANTS'06 Proceedings of the 5th international conference on Ant Colony Optimization and Swarm Intelligence
The hyper-cube framework for ant colony optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
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Assembly line balancing problems are concerned with the distribution of work required to assemble a product in mass or series production among a set of work stations on an assembly line. The specific problem considered here is known as the time and space constrained simple assembly line balancing problem. Among several possible objectives we consider the one of minimizing the number of necessary work stations. This problem is denoted by TSALBP-1 in the literature. For tackling this problem we propose an extended version of our Beam-ACO approach published in [3]. Beam-ACO algorithms are hybrid techniques that result from combining ant colony optimization with beam search. The experimental results show that our algorithm is able to find 128 new best solutions in 269 possible cases.