USING PARALLEL BRANCH-AND-BOUND ALGORITHM ON GPUs FOR OPTIMAL DESIGN OF MULTI-PRODUCT BATCH PLANTS

In this paper, we propose a novel implementation of the branch-andbound algorithm on a system with GPUs (Graphics Processing Units) using the Compute Unified Device Architecture (CUDA) approach. The developed implementation is used for solving a real-world problem – the optimal selection of the chemical equipment for multi-product batch plants. We propose two implementations for the searching algorithm – an iterative and a recursive one – and we describe their optimizations, as well as compare them to each other. We report experimental results about the speedup of our GPU-based implementations as compared to the sequential CPU version.