An Improved Cuckoo Search Algorithm under Bottleneck-Degree-Based Search Guidance for Large-Scale Inter-Cell Scheduling Optimization

Author:

Yang Peixuan1,Liu Qiong1,Xiong Shuping1

Affiliation:

1. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China

Abstract

In order to deal with problems of reduced searching efficiency and poor quality of algorithms for large-scale inter-cell scheduling problems, an improved cuckoo search algorithm under bottleneck-degree-based search guidance is proposed. A large-scale inter-cell scheduling optimization model aiming at minimizing makespan is established. A tabu search is adopted to replace the local search strategy of the cuckoo search algorithm. The bottleneck degree of a complex network model for an inter-cell scheduling problem is used to guide the design of the neighborhood structure of the tabu search. The proposed algorithm is validated by numerical examples. The results show that the convergent speed and qualities of solutions of the proposed algorithm are improved. It is verified that the proposed search guidance based on a complex network’s bottleneck degree could improve the searching ability and convergence speed of the algorithm for large-scale inter-cell scheduling optimization problems.

Funder

National Key R&D Program of China

Publisher

MDPI AG

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