journal article·2024-01-24Open access

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

Peixuan Yang, Qiong Liu, Shuping Xiong

Applied Sciences· Volume 14· Issue 3

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.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Metaheuristic Optimization Algorithms Research · Scheduling and Optimization Algorithms · Vehicle Routing Optimization Methods

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

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

Funding

National Key R&D Program of China

References (40)

Show source-provided references
1. Solving large scale industrial production scheduling problems with complex constraints: An overview of the state-of-the-art10.1016/j.procs.2022.12.301 ↗
2. Metaheuristics in large-scale global continues optimization: A survey10.1016/j.ins.2014.10.042 ↗
3. A three-layer chromosome genetic algorithm for multi-cell scheduling with flexible routes and machine sharing10.1016/j.ijpe.2017.12.003 ↗
4. A divide-and-conquer strategy with particle swarm optimization for the job shop schedule problem10.1080/03052150903369845 ↗
5. Decomposition approaches for the efficient solution of short-term schedule problems10.1016/S0098-1354(03)00051-6 ↗
6. Problem Decomposition and Multi-shot ASP Solving for Job-shop Scheduling10.1017/S1471068422000217 ↗
7. A splitting-up approach to simplify job-shop schedule problems10.1080/00207543.1992.9728461 ↗
8. Study on constraint scheduling algorithm for job shop problems with multiple constraint machines10.1080/00207540701324143 ↗
9. Sannomiya, N., and Lima, H. (1999, January 12–15). Genetic algorithm approach to an optimal scheduling problem for a large-scale complex manufacturing system. Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, Tokyo, Japan.
10. A short-term scheduling problem in the paper-converting industry10.1016/S0098-1354(99)80214-2 ↗
11. Solving a large-scale industrial scheduling problem using MILP combined with a heuristic procedure10.1016/S0377-2217(01)00140-0 ↗
12. Decomposition methods for manufacturing system scheduling: A survey10.1109/JAS.2017.7510805 ↗
13. An integrated search heuristic for large-scale flexible job shop scheduling problems10.1016/j.cor.2013.06.010 ↗
14. Integrating machine layout, transporter allocation and worker assignment into job-shop scheduling solved by an improved non-dominated sorting genetic algorithm10.1016/j.cie.2023.109169 ↗
15. A Competitive Swarm Optimizer for Large Scale Optimization10.1109/TCYB.2014.2322602 ↗
16. Improved Genetic Algorithm Approach Based on New Virtual Crossover Operators for Dynamic Job Shop Scheduling10.1109/ACCESS.2020.3040345 ↗
17. Adaptive genetic algorithm for two-stage hybrid flow-shop scheduling with sequence-independent setup time and no-interruption requirement10.1016/j.eswa.2022.118068 ↗
18. A review on swarm intelligence and evolutionary algorithms for solving flexible job shop scheduling problems10.1109/JAS.2019.1911540 ↗
19. A hybrid algorithm with a new neighborhood structure for job shop scheduling problems10.1016/j.cie.2022.108205 ↗
20. Hybrid genetic algorithm with variable neighborhood search for flexible job shop scheduling problem in a machining system10.1016/j.eswa.2022.119359 ↗
21. A hybrid cuckoo search algorithm in parallel batch processing machines with unequal job ready times10.1016/j.cie.2018.07.001 ↗
22. Biological networks: The tinkerer as an engineer10.1126/science.1089072 ↗
23. Molecular networks: The top-down view10.1126/science.1089118 ↗
24. The structure and function of complex networks10.1137/S003614450342480 ↗
25. Emergence of scaling in random networks10.1126/science.286.5439.509 ↗
26. Complex networks and simple models in biology
27. Public Opinion Evolution Based on Complex Networks
28. Dynamics and control of state-dependent networks for probing genomic organization10.1073/pnas.1113249108 ↗
29. Identification of key machines in complex production networks10.1016/j.procir.2015.12.006 ↗
30. Pang, H., and Jiang, X. (2017, January 9–10). Solution of Flexible Job Shop Scheduling Problem Based on Ant Colony Algorithm and Complex Network. Proceedings of the 10th International Symposium on Computational Intelligence and Design, Hangzhou, China.10.1109/ISCID.2017.225 ↗
31. Improved small world genetic algorithm for intercell scheduling in network environment
32. Yang, X.S., and Deb, S. (2009, January 9–11). Cuckoo search via Lévy flight. Proceedings of the World Congress on Nature & Biologically Inspired Computing, Coimbatore, India.10.1109/NABIC.2009.5393690 ↗
33. Genetic Algorithms and Random Keys for Sequencing and Optimization10.1287/ijoc.6.2.154 ↗
34. Fast accurate algorithm for numerical simulation of Lévy stable stochastic processes10.1103/PhysRevE.49.4677 ↗
35. Engineering a Memetic Algorithm from Discrete Cuckoo Search and Tabu Search for Cell Assignment of Hybrid Nanoscale CMOL Circuits10.1142/S0218126616500237 ↗
36. Tabu Search: A Tutorial
37. Bottleneck identification in job-shop based on network structure characteristic
38. A study of scheduling under the theory of constraints10.1016/j.ijpe.2015.03.015 ↗
39. Modified bottleneck-based heuristic for large-scale job-shop scheduling problems with a single bottleneck10.1016/S1004-4132(07)60129-7 ↗
40. Restart particle swarm optimization with velocity modulation: A scalability test10.1007/s00500-010-0648-1 ↗