Hybridizing constraint programming and meta-heuristics for multi-mode resource-constrained multiple projects scheduling Problem

Abstract

The Multi-Mode Resource-Constrained Multiple Projects Scheduling Problem (MMRCMPSP) is an important combinatorial optimization problem for both real-world situations in industry and academic research. Its objective is to find the best schedule for activities across multiple projects that can be executed in different modes. The schedule must consider shared resource availability and satisfy precedence and time constraints. To tackle this problem, we propose a hybrid approach that combines constraint programming (CP) with meta-heuristic algorithms. We introduce and assess a CP model that incorporates all MMRCMPSP constraints. By leveraging the strengths of CP and meta-heuristics, our approach yields new upper bounds for various MMRCMPSP benchmark instances. Additionally, we evaluate our method using existing benchmark instances for single-project scheduling problems with multiple modes and provide improved solutions for many of them.