Activity assigning of fourth party logistics by particle swarm optimization-based preemptive fuzzy integer goal programming

This paper proposes modified particle swarm optimization to solve the problem of activity assignment of fourth party logistics (4PL) with preemptive structure. In practice, decision makers must consider goals of different importance when they encounter 4PL decision problems. Previous studies have adopted weighted fuzzy goal programming to design optimization problems. However, it is difficult for decision makers to determine proper weights. This paper proposes a decision making method based on preemptive fuzzy goal programming and a modified PSO. The proposed method does not require weights, and prevents results without feasible solutions caused by improper resource setting. Furthermore, this paper proposes a modified PSO with mutation operator extension. Numerical analysis shows that proposed modified PSOs prevent algorithms from caving prematurely into local optimums.