期刊
IEEE TRANSACTIONS ON FUZZY SYSTEMS
卷 29, 期 11, 页码 3234-3248出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TFUZZ.2020.3016225
关键词
Job shop scheduling; Heuristic algorithms; Artificial intelligence; Fuzzy logic; Uncertainty; Optimization; Cloning; Artificial immune system (AIS); energy consumption; flexible job shop; type-2 fuzzy processing time
资金
- National Science Foundation of China [61773192, 61803192]
- Shandong Province Higher Educational Science and Technology Program [J17KZ005, ZR2018ZB0419]
- Taishan Scholar Project of Shandong Province [TSQN201812092]
- Key Research and Development Program of Shandong Province [2019GGX101072]
- Youth Innovation Technology Project of Higher School in Shandong Province [2019KJN005]
This article proposes an improved artificial immune system (IAIS) algorithm to solve a special case of the flexible job shop scheduling problem (FJSP), where the processing time of each job is a nonsymmetric triangular interval T2FS (IT2FS) value. The algorithm shows enhanced abilities in handling high levels of uncertainty and asymmetric triangular interval values. Through novel affinity calculation methods, problem-specific initialization heuristics, local search approaches, and population diversity heuristics, the algorithm demonstrates improved exploitation and exploration capabilities.
In practical applications, particularly in flexible manufacturing systems, there is a high level of uncertainty. A type-2 fuzzy logic system (T2FS) has several parameters and an enhanced ability to handle high levels of uncertainty. This article proposes an improved artificial immune system (IAIS) algorithm to solve a special case of the flexible job shop scheduling problem (FJSP), where the processing time of each job is a nonsymmetric triangular interval T2FS (IT2FS) value. First, a novel affinity calculation method considering the IT2FS values is developed. Then, four problem-specific initialization heuristics are designed to enhance both quality and diversity. To enhance the exploitation abilities, six local search approaches are conducted for the routing and scheduling vectors, respectively. Next, a simulated annealing method is embedded to accept antibodies with low affinity, which can enhance the exploration abilities of the algorithm. Moreover, a novel population diversity heuristic is presented to eliminate antibodies with high crowding values. Five efficient algorithms are selected for a detailed comparison, and the simulation results demonstrate that the proposed IAIS algorithm is effective for IT2FS FJSPs.
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