An improved KTNS algorithm for the job sequencing and tool switching problem
Abstract
We outline a new Max Pipe Construction Algorithm (MPCA) with the purpose to reduce the CPU time for the classic Keep Tool Needed Soonest (KTNS) algorithm. The KTNS algorithm is applied to compute the objective function value for the given sequence of jobs in all exact and approximating algorithms for solving the Job Sequencing and Tool Switching Problem (SSP). Our MPCA outperforms the KTNS algorithm by at least an order of magnitude in terms of CPU times. Since all exact and heuristic algorithms for solving the SSP spend most of their CPU time on applying the KTNS algorithm we show that our MPCA solves the entire SSP on average 59 times faster for benchmark instances of D compared to current state of the art heuristics.
Keywords
Cite
@article{arxiv.2205.06042,
title = {An improved KTNS algorithm for the job sequencing and tool switching problem},
author = {Mikhail Cherniavskii and Boris Goldengorin},
journal= {arXiv preprint arXiv:2205.06042},
year = {2022}
}
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Presented online at The 51st Annual Meeting of the Southeast Decision Sciences Institute, February 16 - 18, 2022 Jacksonville, FL