A heuristic procedure for personnel task rescheduling with time-resource-quality trade-offs. (August 2022)

• Record Type: Journal Article
• Authors: Borgonjon, Tessa; Maenhout, Broos
• Is Part Of: Computers & industrial engineering. Volume 170(2022)
• Publication Date: 2022-08
• Subjects: Heuristic optimisation -- Personnel task rescheduling -- Time-resource-quality trade-off; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2022.108254
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: Multi-mode personnel task rescheduling problem. Time-resource-quality trade-offs. Two-stage heuristic based on local improvement and solution merging. Abstract: In this paper, we consider the personnel task rescheduling problem with multiple discrete activity modes following time-resource-quality trade-offs. Due to operational uncertainty, announced baseline schedules may become infeasible and the need for rescheduling arises. To restore feasibility, changes are required to either the resource schedule or the service level impacting the task delivery. In this study, we explore in particular the recovery action to change the operation modes of individual activities, instigating a trade-off between time, quality and assigned resources. We propose a two-stage heuristic procedure targeted at finding high-quality solutions in an efficient manner. The first stage improves an initial schedule by exploiting different local improvement steps. The second stage merges different high-quality solutions via mathematical programming by combining task-worker assignment patterns identified in multiple visited schedules. The performance of the proposed procedure and the corresponding acceleration strategies is demonstrated by a range of computational experiments, benchmarking the two-stage procedure with other optimisation procedures and validating algorithm design choices. Furthermore, we evaluate the value of having the possibility to select one out of multiple operation modes for schedule recovery and the impact of different mode settings.