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A trapezoidal fuzzy flow shop scheduling framework integrating job block heuristics to reduce waiting time | ||
| Iranian Journal of Fuzzy Systems | ||
| دوره 23، شماره 5، آذر و دی 2026، صفحه 185-203 اصل مقاله (877.78 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22111/ijfs.2026.53655.9496 | ||
| نویسندگان | ||
| B. Goyal* 1؛ D. Gupta2؛ R. Rani3 | ||
| 1General Shivdev Singh Diwan Gurbachan Singh Khalsa College Patiala | ||
| 2Department of Mathematics, Maharishi Markandeshwar (Deemed to be University) Mullana | ||
| 3Chandigarh Group of Colleges Jhanjeri, Chandigarh Engineering College, Department of Applied Sciences, Mohali | ||
| چکیده | ||
| This study addresses a two-machine flow shop scheduling problem with uncertain processing durations represented as trapezoidal fuzzy numbers, which are converted to crisp values using Yager’s ranking index. Job-block formation is introduced to reduce sequencing complexity and suppress waiting on the second machine, and new theorems establish how block aggregation influences waiting-time behavior. A structured heuristic generates the sequence with minimum total waiting time of jobs. Extensive computational experiments on specially structured instances demonstrate consistent improvements in waiting time. Statistical analysis, including paired t-tests and Wilcoxon signed-rank tests, confirms that the proposed heuristic achieves significant reductions compared to classical rules and recent heuristics across multiple job sizes (p < 0.01), supporting the superiority of the method. The results highlight the practical effectiveness of integrating fuzzy modelling, crisp conversion, and block-based sequencing, providing a theoretically grounded and empirically validated approach for modern production environments with imprecise processing times. | ||
| کلیدواژهها | ||
| Trapezoidal؛ specially structured؛ flow shop scheduling؛ fuzzy processing time؛ job-block formation؛ waiting time minimization؛ heuristic | ||
| مراجع | ||
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