Hybrid genetic algorithm with adaptive local search for precedence-constrained sequencing problems

Precedence-constrained sequencing problem (PCSP) is to locate the optimal sequence with the shortest traveling time among all feasible sequences. A number of industrial models for the PCSP have been constructed. This paper proposes a new concept of hybrid genetic algorithm (HGA) with adaptive local search so that the PCSP should be effectively solved. By the use of the adaptive local search, a local search method is adaptively adapted into the genetic algorithm loop. Several types of the PCSP are presented and analyzed to compare the efficiency among the proposed HGA approach and other competing conventional approaches. Finally, it is proved that the proposed HGA approach outperforms the other competing conventional approaches.