An Effective Hybrid Ant Colony Optimization for Permutation Flow-Shop Scheduling

ABSTRACT

This paper proposes a hybrid ant colony optimization algorithm to solve the permutation flow-shop scheduling (PFS). The hybridization of ant colony optimization (ACO) with path relinking (PR), which combines the advantages of two individual algorithms, is the key innovative aspect of the approach. Path relinking (PR) can be interpreted as an evolutionary method where the high quality solutions are generated by introducing features of the guiding solution gradually into the initial solution. Moreover, the effective hybrid algorithm is a method to integrate intensification and diversification in the search, and it adopts the criterion function restricting the frequencies of using the PR procedure to improve the convergence speed. Finally, the proposed algorithm is applied to PFS benchmark problems. The experimental results have shown that the hybrid method yields better results to solve the permutation flow-shop scheduling than well-known existing methods in terms of solution quality.

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