A new ant colony optimization for minimizing total tardiness on parallel machines scheduling

Abstract

Scheduling jobs on parallel machines to minimize total tardiness (P//T) plays an important role in real applications. The problem of P//T has been proved to be NP-hard, and the complexity of computation increases heavily with the growing of the number of machines. First, a graphical model to describe P//T is constructed in this paper, so that ACO (Ant Colony Optimization) can be applied to resolve the problem. Secondly, a modified ACO algorithm is developed in which some new computation rules are developed to improve the efficiency. Finally, data experiments are processed, which demonstrates that the approaches proposed in this paper can achieve comparable results to some currently popular algorithms.