Parallelization of a metaheuristic algorithm for complex inventory management and control problems: A computational study using OpenMP and OpenACC technologies
The author explores the theoretical background of metaheuristics, specifically Variable Neighborhood Search (VNS), alongside parallel programming architectures before implementing a parallelized Variable Neighborhood Descent (VND) algorithm for a multi-product dynamic lot-sizing problem. Computational experiments reveal that both OpenMP and OpenACC significantly reduce execution time, achieving a speedup of approximately 3.3 times over the serial version. However, because the applied parallelization strategy focused strictly on accelerating computations rather than expanding the search space, the overall quality of the final solutions remained unchanged.