An Integer Batch Scheduling Model for a Single Machine with Simultaneous Learning and Deterioration Effects to Minimize Total Actual Flow Time

2nd International Manufacturing Engineering Conference; 3rd Asia-Pacific Conference on Manufacturing Systems

Yusriski, R.^1 ; Sukoyo^1 ; Samadhi, T.M.A.A.^1 ; Halim, A.H.^1

Department of Industrial Engineering and Management, Institut Teknologi Bandung, 40132, Indonesia^1

关键词: Batch-scheduling;    Decision variables;    Enumeration method;    Lagrange relaxation;    Manufacturing industries;    Optimal solutions;    Scheduling periods;    Single- machines;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/114/1/012073/pdf
DOI  :  10.1088/1757-899X/114/1/012073

来源: IOP

【 摘 要 】

In the manufacturing industry, several identical parts can be processed in batches, and setup time is needed between two consecutive batches. Since the processing times of batches are not always fixed during a scheduling period due to learning and deterioration effects, this research deals with batch scheduling problems with simultaneous learning and deterioration effects. The objective is to minimize total actual flow time, defined as a time interval between the arrival of all parts at the shop and their common due date. The decision variables are the number of batches, integer batch sizes, and the sequence of the resulting batches. This research proposes a heuristic algorithm based on the Lagrange Relaxation. The effectiveness of the proposed algorithm is determined by comparing the resulting solutions of the algorithm to the respective optimal solution obtained from the enumeration method. Numerical experience results show that the average of difference among the solutions is 0.05%.