Approximate-Backbone Guided Fast Ant Algorithms to QAP
求解QAP问题的近似骨架导向快速蚁群算法

Quadratic Assignment Problem (QAP) is one of the classical combinatorial optimization problems and is known for its diverse applications. This paper presents a new fast ant heuristic for the QAP, the approximatebackbone guided fast ant colony algorithm (ABFANT). The main idea is to fix the approximatebackbone which is the intersection of several local optimal permutations to the QAP. After fixing it, the authors can smooth the search space of the QAP instance without losing the search capability, and then solve the instance using the known fast ant colony algorithm (FANT) which is one of the best heuristics to the QAP in the much smoother search space. Comparisons of ABFANT and FANT within a given iteration number are performed on the publicly available QAP instances from QAPLIB. The result demonstrates that ABFANT significantly outperforms FANT.Furthermore, this idea is general and applicable to other heuristics of the QAP.