This paper addresses a serial-batching scheduling problem where the jobs with arbitrary release times are scheduled on parallel machines with the objective to minimize the makespan. The effects of learning and deterioration are considered simultaneously, and each job’s actual processing time depends on the sum of previous jobs’ processing times and the position of the current job. Each machine can process up to \( c \) jobs in the manner of serial batch, i.e., one after another with a setup time for each batch. Structural properties are identified for the special cases of the studied problem. Based on these derived structural properties, we propose a novel hybrid SC-VNS algorithm to solve the studied problem, which combines Society and Civilization (SC) algorithm with Variable Neighborhood Search (VNS). Computational experiments are conducted to evaluate the performance of the proposed hybrid algorithm and some other well-known algorithms. The results demonstrate that the proposed hybrid SC-VNS algorithm performs quite better than the compared algorithms in terms of the solution quality and the required running time.
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This work is supported by the National Natural Science Foundation of China (Nos. 71922009, 71871080, 71601065, 71690235, 71690230), and Innovative Research Groups of the National Natural Science Foundation of China (71521001), the Humanities and Social Sciences Foundation of the Chinese Ministry of Education (No. 15YJC630097), Base of Introducing Talents of Discipline to Universities for Optimization and Decision-making in the Manufacturing Process of Complex Product (111 project), the Project of Key Research Institute of Humanities and Social Science in University of Anhui Province, Open Research Fund Program of Key Laboratory of Process Optimization and Intelligent Decision-making and Ministry of Education Engineering Research Center for Intelligent Decision-making and Information Systems Technologies (Hefei University of Technology), Ministry of Education.
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Pei, J., Song, Q., Liao, B. et al. Parallel-machine serial-batching scheduling with release times under the effects of position-dependent learning and time-dependent deterioration. Ann Oper Res 298, 407–444 (2021). https://doi.org/10.1007/s10479-020-03555-2
- Parallel machines
- Release times
- Learning effect
- Deteriorating jobs