Solving the bi-objective personnel assignment problem using particle swarm optimization ?
A particle swarm optimization (PSO) algorithm combined with the random-key (RK) encoding scheme (named as PSORK) for solving a bi-objective personnel assignment problem (BOPAP) is presented. The main contribution of this work is to improve the f1_f2 heuristic algorithm which was proposed by Huang et al. [3]. The objective of the f1_f2 heuristic algorithm is to get a satisfaction level (SL) value which is satisfied to the bi-objective values f1, and f2 for the personnel assignment problem. In this paper, PSORK algorithm searches the solution of BOPAP space thoroughly. The experimental results show that the solution quality of BOPAP based on the proposed method is far better than that of the f1_f2 heuristic algorithm.
bi-objective personnel assignment problem particle swarm optimization random-key encoding scheme