Abstract
This paper presents a novel hybrid ant colony optimization approach (ACO&PR) to solve the permutation flow-shop scheduling (PFS). The main feature of this hybrid algorithm is to hybridize the solution construction mechanism of the ACO with path relinking (PR), an evolutionary method, which introduces progressively attributes of the guiding solution into the initial solution to obtain the high quality solution. Moreover, the hybrid algorithm considers both solution diversification and solution quality, and it adopts the dynamic updating strategy of the reference set to accelerate the convergence towards high-quality regions of the search space. Finally, the experimental results for benchmark PFS instances have shown that our proposed method is very efficient to solve the permutation flow-shop scheduling compared with the best existing methods in terms of solution quality.
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