Permutation-Based Dual Genetic Algorithm Applied in Dynamic Sequencing Optimizations

An attribute-based dual scheme is presented for extending the genetic algorithm with dual mechanism to solve order-encoding dynamic optimization problems, within the proposed permutation-based dual genetic algorithm; the concept of permutation in Group theory is introduced to represent the attribute. To maintain diversity as well as guarantee searching precision, the learning operator and incomplete-dual operator are designed using some characteristics of permutation. It has been applied to the dynamic single machine total weighted tardiness problem that has variational duedates, and satisfactory results have been achieved.