A four-Phase Meta-Heuristic Algorithm for Solving Large Scale Instances of the Shift Minimization Personnel Task Scheduling Problem

Abstract

The Shift minimization personnel task scheduling problem (SMPTSP) is a known NP-hard problem. The present paper introduces a novel four-phase meta-heuristic approach for solving the Shift minimization personnel task scheduling problem which consists of an optimal assignment of jobs to multi-skilled employees, such that a minimal number of employees is used and no job is left unassigned. The computational results show that the proposed approach is able to find very good solutions in a very short time. The approach was tested and validated on the benchmarks from existing literature, managing to find very good solutions.