# Multi-Objective Parameter-less Population Pyramid for Solving Industrial Process Planning Problems

arXiv: https://arxiv.org/abs/2009.08929 · HTML: https://mlsanity.com/paper/2009.08929/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Sep 2020.

## Built on by (most cited first, 1 of 1)

- [Seeking and leveraging alternative variable dependency concepts in gray-box-elusive bimodal land-use allocation problems](https://mlsanity.com/paper/2504.11882/) (2025)

## Abstract (arXiv)

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.