Estimation of distribution algorithm for solving hybrid flow-shop scheduling problem

摘要

According to the characteristics of hybrid flow shop scheduling problem (HFSP), this paper designed encoding and decoding methods based on permutation, established a probability model to describe the problem solution space, and proposed a estimation of distribution algorithm (EDA) to solve the hybrid flow shop scheduling problem. The algorithm based on probabilistic models generates new individuals by random sampling methods and updates the probabilistic models based on the dominant population. Based on examples of numerical simulation and compared with the existing algorithm, the paper verified the effectiveness and robustness of the algorithm.