Investigating constraint programming and hybrid methods for real world industrial test laboratory scheduling

Tobias Geibinger (), Florian Mischek () and Nysret Musliu ()
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Tobias Geibinger: TU Wien
Florian Mischek: TU Wien
Nysret Musliu: TU Wien

Journal of Scheduling, 2024, vol. 27, issue 6, No 6, 607-622

Abstract: Abstract In this paper we deal with a complex real world scheduling problem closely related to the well-known Resource-Constrained Project Scheduling Problem (RCPSP). The problem concerns industrial test laboratories in which a large number of tests are performed by qualified personnel using specialised equipment, while respecting deadlines and other constraints. We present different constraint programming models and search strategies for this problem. Furthermore, we propose a Very Large Neighborhood Search approach based on our CP methods. Our models are evaluated using CP solvers and a MIP solver both on real-world test laboratory data and on a set of generated instances of different sizes based on the real-world data. Further, we compare the exact approaches with VLNS and a Simulated Annealing heuristic. We could find feasible solutions for all instances and several optimal solutions and we show that using VLNS we can improve upon the results of the other approaches.

Keywords: RCPSP; Resource constrained project scheduling problem; Project scheduling; Constraint programming; VLNS; Very large neighborhood search (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10951-024-00821-0

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