Spatial-domain fitness landscape analysis for combinatorial optimization
From MaRDI portal
Publication:2200693
DOI10.1016/j.ins.2018.09.019zbMath1443.90298OpenAlexW2890029885WikidataQ58934846 ScholiaQ58934846MaRDI QIDQ2200693
Rongrong Zhou, Hui Lu, Zongming Fei, Chongchong Guan
Publication date: 22 September 2020
Published in: Information Sciences (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.ins.2018.09.019
Cites Work
- Unnamed Item
- Measuring epistasis in fitness landscapes: the correlation of fitness effects of mutations
- A discrete gravitational search algorithm for solving combinatorial optimization problems
- Analysis of the similarities and differences of job-based scheduling problems
- Nonstandard utilities for lexicographically decomposable orderings
- A novel artificial bee colony algorithm with an adaptive population size for numerical function optimization
- Models and matheuristics for the unrelated parallel machine scheduling problem with additional resources
- Adaptive feasible and infeasible tabu search for weighted vertex coloring
- Routing and scheduling in a flexible job shop by tabu search
- Unrelated parallel-machine scheduling problems with multiple rate-modifying activities
- The Complexity of Flowshop and Jobshop Scheduling
- Neutrality in fitness landscapes.
This page was built for publication: Spatial-domain fitness landscape analysis for combinatorial optimization