A discrete oppositional multi-verse optimization algorithm for multi-skill resource constrained project scheduling problem

Abstract

In this paper, a discrete oppositional multi-verse optimization (DOMVO) algorithm is proposed to address multi-skill resource constrained project scheduling problem (MS-RCPSP). Firstly, the black/white holes phase in DOMVO algorithm is designed by integrating path relinking technique. Secondly, two improved path relinking methods are presented and embedded into the proposed scheme to enhance search abilities. Thirdly, the opposition-based learning (OBL) method is employed as a hybrid strategy to improve the quality of solutions. Moreover, a repair-based decoding scheme is developed to generate schedules more efficiently. Additionally, the design-of-experiment (DOE) method is carried out to investigate the influence of parameters setting. Finally, the effectiveness of DOMVO is evaluated on the intelligent multi-objective project scheduling environment (iMOPSE) benchmark dataset and the computational comparisons indicate the superiority of the proposed DOMVO over the state-of-the-art algorithms in solving MS-RCPSP.