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In this paper we deal with a complex real world scheduling problem closelyrelated to the well-known Resource-Constrained Project Scheduling Problem(RCPSP). The problem concerns industrial test laboratories in which a largenumber of tests has to be performed by qualified personnel using specialisedequipment, while respecting deadlines and other constraints. We presentdifferent constraint programming models and search strategies for this problem.Furthermore, we propose a Very Large Neighborhood Search approach based on ourCP methods. Our models are evaluated using CP solvers and a MIP solver both onreal-world test laboratory data and on a set of generated instances ofdifferent sizes based on the real-world data. Further, we compare the exactapproaches with VLNS and a Simulated Annealing heuristic. We could findfeasible solutions for all instances and several optimal solutions and we showthat using VLNS we can improve upon the results of the other approaches.

Investigating Constraint Programming and Hybrid Methods for Real World Industrial Test Laboratory Scheduling