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Two Parameter-Tuned Multi-Objective Evolutionary-Based Algorithms for Zoning Management in Marine Spatial Planning
03 Oct 2022
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About: The article was published on 03 Oct 2022. and is currently open access. The article focuses on the topics: Zoning & Marine spatial planning.
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Citations
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A Land Use Planning Literature Review: Literature Path, Planning Contexts, Optimization Methods, and Bibliometric Methods
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Nature-Based Secondary Resource Recovery under Climate Change Uncertainty: A Robust Multi-Objective Optimisation Methodology
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References
A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimisation: NSGA-II
Kalyanmoy Deb,Samir Agrawal,Amrit Pratap,T. Meyarivan +3 more
- 18 Sep 2000
TL;DR: Simulation results on five difficult test problems show that the proposed NSGA-II, in most problems, is able to find much better spread of solutions and better convergence near the true Pareto-optimal front compared to PAES and SPEA--two other elitist multi-objective EAs which pay special attention towards creating a diverse Paretimal front.
Pymoo: Multi-Objective Optimization in Python
Julian Blank,Kalyanmoy Deb +1 more
TL;DR: This work develops pymoo, a multi-objective optimization framework in Python that addresses practical needs, such as the parallelization of function evaluations, methods to visualize low and high-dimensional spaces, and tools for multi-criteria decision making.
1.5K
Multi-attribute decision making: A simulation comparison of select methods
TL;DR: This study investigates the performance of eight methods for solving multi-attribute decision making problems (MADM) using a decision matrix input of N criteria weights and ratings of L alternatives on each criterion, and investigates similarities and differences in the behavior of these methods.
1K
Multi-objective Optimisation Using Evolutionary Algorithms: An Introduction
Kalyanmoy Deb
- 01 Jan 2011
TL;DR: This chapter provides a brief introduction to its operating principles and outline the current research and application studies of evolutionary multi-objective optmisation (EMO).
Response Surface Methodology: A Retrospective and Literature Survey
Raymond H. Myers,Douglas C. Montgomery,G. Geoffrey Vining,Connie M. Borror,Scott M. Kowalski +4 more
TL;DR: This review paper focuses on RSM activities since 1989, and discusses current areas of research and mention some areas for future research.
699