Resource leveling optimization based on clonal cuckoo search algorithm
Song Yu-jia · Jisuanji yingyong yanjiu · 2014
Resource leveling problem is a NP-Hard problem,and this paper proposed a new chonal cuckoo search algorithm to efficiently to solve it.First,the algorithm executed population expansion based on individual's fitness.Then,it employed the Levy mutation operator to realize the clonal population's update.At last,it embedded a non-uniform mutation operator to make a balance between exploration and exlpoiton.The case study illustrates that the clonal cuckoo search algorithm outperforms PSO algorithm,DE algorithm and basic cuckoo search algorithm when consider solution quality and covergence speed as the main mertric of performance.