Abstract
Flow shop scheduling problem is an important one in the real world production process. As tight constraint condition exits in just-in-time production systems, the no-wait flow shop scheduling problem (NWFSSP) is a typical research topic. In this paper, a hybrid discrete estimation of distribution algorithm (HDEDA) for NWFSSP is proposed to minimize the makespan. The proposed HDEDA utilizes the EDA and bat algorithm (BA). The probability matrix can be a view in the space distribution of the solution well by relying on the knowledge obtained from NWFSSP. The individual generated by sampling has the probability to spread throughout the entire solution space. Then, the designed step-based insertion in the BA stage attains the solution with the best makespan. All of the experiments are performed on the new hard benchmark for flow shop scheduling problems proposed by Ruiz in 2015. Through experimental comparisons, HDEDA shows better effectiveness than other algorithms.
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