Results 81 to 90 of about 188,919 (293)
The computational complexity of rationalizing Pareto optimal choice behavior. [PDF]
We consider a setting where a coalition of individuals chooses one or several alternatives from each set in a collection of choice sets. We examine the computational complexity of Pareto rationalizability.
Demuynck, Thomas
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Agribusiness, EarlyView.Abstract Outsourcing pest and disease control (PDC) has grown rapidly worldwide, especially in developing countries. Although numerous studies have investigated various advantages of outsourcing PDC, little is known about its impact on pesticide expenditure.
Pengcheng Wang +2 more
wiley +1 more source
Sensitivity of Pareto Solutions in Multiobjective Optimization. [PDF]
The paper presents a sensitivity analysis of Pareto solutions on the basis of the Karush-Kuhn-Tucker (KKT) necessary conditions applied to nonlinear multiobjective programs (MOP) continuously depending on a parameter.
Balbás, Alejandro +2 more
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Advanced Intelligent Discovery, EarlyView.Bayesian optimization enabled the design of PA56 system with just 8 wt% additives, achieving limiting oxygen index 30.5%, tensile strength 80.9 MPa, and UL‐94 V‐0 rating. Without prior knowledge, the algorithm uncovered synergistic effects between aluminum diethyl‐phosphinate and nanoclay.
Burcu Ozdemir +4 more
wiley +1 more source
Elite Multi-Criteria Decision Making—Pareto Front Optimization in Multi-Objective Optimization
AlgorithmsOptimization is a process of minimizing or maximizing a given objective function under specified constraints. In multi-objective optimization (MOO), multiple conflicting functions are optimized within defined criteria.
Adarsh Kesireddy, F. Antonio Medrano
doaj +1 more source
Existence of a Pareto optimal social interaction outcome with non-binary preferences [PDF]
We prove the existence of a Pareto optimal state of a society with non-binary personal preferences. To our knowledge, this is the weakest set of conditions under which the existence of a Pareto optimal state has been proven.
Berdellima, Arian, Naqvi, Nadeem
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Deep Learning‐Assisted Design of Mechanical Metamaterials
Advanced Intelligent Discovery, EarlyView.This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong +5 more
wiley +1 more source
Applied SciencesBi-objective optimization seeks to obtain Pareto optimal solutions that balance two trade-off objectives, providing guidance for decision making in various fields, particularly in the field of transportation. The novelty of this study lies in two aspects.
Hongyu Zhang +3 more
doaj +1 more source
Advanced Intelligent Discovery, EarlyView.Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova +4 more
wiley +1 more source
A local search-based bi-objective optimization considering distance constraints
Nihon Kikai Gakkai ronbunshu, 2014 Conflicting interrelationships among objective functions are often encountered in real-world engineering design problems. If such exist in a multiobjective optimization problem, no unique solution can simultaneously minimize all of the objective ...
Yuki SATO +3 more
doaj +1 more source