ArticleBiomimetics (Basel, Switzerland)2024
A Crisscross-Strategy-Boosted Water Flow Optimizer for Global Optimization and Oil Reservoir Production.
Article in Biomimetics (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 6 citations in OpenAlex.
- CCESC: A Crisscross-Enhanced Escape Algorithm for Global and Reservoir Production Optimization.Biomimetics (Basel, Switzerland) · 2025Article
- Crisscross Moss Growth Optimization: An Enhanced Bio-Inspired Algorithm for Global Production and Optimization.Biomimetics (Basel, Switzerland) · 2025Article
- Gaussian barebone mechanism and wormhole strategy enhanced moth flame optimization for global optimization and medical diagnostics.PloS one · 2025Article
- An Enhanced Tree-Seed Algorithm for Function Optimization and Production Optimization.Biomimetics (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The growing intricacies in engineering, energy, and geology pose substantial challenges for decision makers, demanding efficient solutions for real-world production. The water flow optimizer (WFO) is an advanced metaheuristic algorithm proposed in 2021, but it still faces the challenge of falling into local optima. In order to adapt WFO more effectively to specific domains and address optimization problems more efficiently, this paper introduces an enhanced water flow optimizer (CCWFO) designed to enhance the convergence speed and accuracy of the algorithm by integrating a cross-search strategy. Comparative experiments, conducted on the CEC2017 benchmarks, illustrate the superior global optimization capability of CCWFO compared to other metaheuristic algorithms. The application of CCWFO to the production optimization of a three-channel reservoir model is explored, with a specific focus on a comparative analysis against several classical evolutionary algorithms. The experimental findings reveal that CCWFO achieves a higher net present value (NPV) within the same limited number of evaluations, establishing itself as a compelling alternative for reservoir production optimization.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.