Multi-Objective Parameter-less Population Pyramid for Solving Industrial Process Planning Problems
This work addresses a specific industrial process planning problem, but it is incremental as it extends an existing single-objective method to multi-objective scenarios.
The authors tackled a multi-objective industrial process planning problem, which is NP-hard, by proposing a multi-objective version of the Parameter-less Population Pyramid (P3) method, and their approach outperformed competing methods for this practical problem and typical benchmarks.
Evolutionary methods are effective tools for obtaining high-quality results when solving hard practical problems. Linkage learning may increase their effectiveness. One of the state-of-the-art methods that employ linkage learning is the Parameter-less Population Pyramid (P3). P3 is dedicated to solving single-objective problems in discrete domains. Recent research shows that P3 is highly competitive when addressing problems with so-called overlapping blocks, which are typical for practical problems. In this paper, we consider a multi-objective industrial process planning problem that arises from practice and is NP-hard. To handle it, we propose a multi-objective version of P3. The extensive research shows that our proposition outperforms the competing methods for the considered practical problem and typical multi-objective benchmarks.