An improved KTNS algorithm for the job sequencing and tool switching problem

TL;DR

This paper introduces a new Max Pipe Construction Algorithm (MPCA) that significantly reduces CPU time for the KTNS algorithm, leading to faster solutions for the Job Sequencing and Tool Switching Problem.

Contribution

The paper presents an improved MPCA that outperforms the traditional KTNS algorithm by at least an order of magnitude in CPU time, enhancing the efficiency of solving SSP.

Findings

MPCA reduces CPU time for KTNS by at least tenfold.

MPCA enables solving SSP instances 59 times faster on average.

The approach improves the efficiency of all algorithms relying on KTNS.

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.