Optimal Batch Plants Design on Parallel Systems: A Comparative Study

摘要

We report a comparative study on the development of high-performance software for solving the problem of optimal design of multiproduct batch plants on modern parallel systems. We analyze two main algorithmic approaches to optimization - branch-and-bound and metaheuristic-based - and we develop and compare their parallel implementations on a variety of parallel architectures: multi-core CPU, GPU, and clusters. Our experiments on a real-world case study - optimization of chemical-engineering systems - demonstrate the trade-offs between the run time performance and the quality of solutions achieved by different algorithms on various parallel architectures.