Search · four archives
Search · four archives
21 papers · ranked by Valyu relevance
Arun Kumar Tripathy
Three approaches of second order mixed type duality are introduced for a nondifferentiable multiobjective fractional programming problem in which the numerator and denominator of objective function contain square root of positive semidefinite quadratic form. Also, the necessary and sufficient conditions of efficient…
Berhanu Belay, Adane Abebaw, Omar A. Alzubi
This manuscript presents a technique for solving a multiple-objective probabilistic fractional programming problem with discrete random variables. A multiple-objective probabilistic mathematical model is constructed with fractional objectives. In the model, some parameters of coefficients and right hand side parameters…
Jiawei Chen, Luyu Liu, Yibing Lv, Debdas Ghosh + 1 more
Constrained Multiobjective Fractional Programming Problems Authors: ['Jiawei Chen' 'Luyu Liu' 'Yibing Lv' 'Debdas Ghosh' 'Jen‐Chih Yao'] Abstract This paper investigates constrained nonsmooth multiobjective fractional programming problem (NMFP) in real Banach spaces. It derives a quotient calculus rule for computing…
Yacine Chaiblaine, Mustapha Moulaï, Yasmine Cherfaoui
In this paper, an exact method is proposed to optimize two fractional linear functions over the efficient set of a fractional multiobjective linear problem (MOILF P). This type of problems is encountered when there are two decision makers and each has his own utility function that he wants to optimize over the…
Moustaid Mohamed Bilal, Laghdir Mohamed, Dali Issam, Rikouane Ahmed
In this paper, in the absence of any constraint qualifications, we develop sequential necessary and sufficient optimality conditions for a constrained multiobjective fractional programming problem characterizing a Henig proper efficient solution in terms of the ǫ-subdifferentials and the subdifferentials of the…
Hasan Dalman
This paper proposes a fuzzy goal programming based on Taylor series for solving decentralized bilevel multiobjective fractional programming (DBLMOFP) problem. In the proposed approach, all of the membership functions are associated with the fuzzy goals of each objective at the both levels and also the fractional…
Songsong Liu, Spyridon Gerontas, David Gruber, Richard Turner + 2 more
'Nigel J. Titchener‐Hooker' 'Lazaros G. Papageorgiou'] This work addresses rapid resin selection for integrated chromatographic separations when conducted as part of a high-throughput screening exercise during the early stages of purification process development. An optimization-based decision support framework is…
Hasan Dalman
This paper presents an interactive fuzzy goal programming (FGP) approach for solving multiobjective nonlinear programming problems (MONLPP) with interval type 2 fuzzy numbers (IT2 FNs). The cost and time of the objective functions, the resources, and the requirements of each kind of resources are taken to be…
S. Narayanamoorthy, S. Kalyani
An approach is presented to solve a fuzzy transportation problem with linear fractional fuzzy objective function. In this proposed approach the fractional fuzzy transportation problem is decomposed into two linear fuzzy transportation problems. The optimal solution of the two linear fuzzy transportations is solved by…
Radu Ioan Boţ, Ernö Robert Csetnek
In this paper, we propose two proximal-gradient algorithms for fractional programming problems in real Hilbert spaces, where the numerator is a proper, convex and lower semicontinuous function and the denominator is a smooth function, either concave or convex. In the iterative schemes, we perform a proximal step with…
Julius Bauß, Michael Stiglmayr
> While branch and bound based algorithms are a standard approach to solve single-objective (mixed-)integer optimization problems, multi-objective branch and bound methods are only rarely applied compared to the predominant objective space methods. In this paper we propose modifications to increase the performance of…
Nicola Hallmann, Catalina Guerra-Cornejo, Karl Burgess, Charlotte Merzbacher + 1 more
The optimization of culture media is critical for improving the efficiency and cost of cellular production systems. Traditional approaches often rely on extensive experimental trials or statistical methods, which can be both costly and time-consuming. Here, we present gsMOBO, a computational approach for media design…
Marc Griesemer, Ali Navid
Multi-objective Optimization (MO) is an important tool for quantitative examination of the trade-offs faced by biological organisms. Using genome-scale constraint-based models of metabolism (GSMs), Multi-Objective Flux Analysis (MOFA) allows MO analyses of trade-offs among key biological tasks. The leading software…
David Bassen, Michael Vilkhovoy, Mason Minot, Jonathan T Butcher + 1 more
Ensemble modeling is a well established approach for obtaining robust predictions and for simulating course grained population behavior in deterministic mathematical models. In this study, we present a multiobjective based technique to estimate model ensembles, the Pareto Optimal Ensemble Technique in the Julia…
Jiyizhe Zhang, Daria Semochkina, Naoto Sugisawa, David Woods + 1 more
Multi-objective Bayesian optimization (MOBO) has shown to be a promising tool for reaction development. However, noise is usually unavoidable during experiments and makes it challenging to find reliable solutions. In this study, we focus on finding a set of optimal reaction conditions using multi-objective Euclidian…
Andre KY Low, Flore Mekki-Berrada, Aleksandr Ostudin, Jiaxun Xie + 7 more
The development of automated high-throughput experimental platforms has enabled fast sampling of high-dimensional decision spaces. To reach target properties efficiently, these platforms are increasingly paired with intelligent experimental design. When solving optimization problems, Bayesian-based optimizers are often…
Paul Bello, Pedro Gallardo, Lorena Pradenas, Jacques A. Ferland + 1 more
Childhood obesity is an undeniable reality and has shown a rapid growth in many countries. Obesity at an early age not only increases the risks of chronic diseases but also produces a problem for the whole healthcare system. One way to alleviate this problem is to provide each patient with an appropriate menu that can…
Authors not listed
Optimizing the synthesis conditions of advanced materials is challenging, especially when outcomes are subject to inherent experimental uncertainties. Bayesian optimization is a popular tool for accelerating materials discovery, but its standard risk-neutral framework overlooks the variability of outcomes under…
Sterling Baird, Jason R. Hall, Taylor D. Sparks
Would you rather search for a line inside a cube or a point inside a square? Physics-based simulations and wet-lab experiments often have symmetries (degeneracies) that allow reducing problem dimensionality or search space, but constraining these degeneracies is often unsupported or difficult to implement in many…
Shetty Nihal Naveen, B. Karthik Udupa, Ashil A. Shetty
Multi-objective optimization in drug discovery faces a fundamental limitation: the assumption that all relevant optimization criteria can be predefined. Traditional approaches using fixed objective sets often miss critical molecular trade-offs that emerge during the optimization process. We present AMODO-EO (Adaptive…
Riley Hickman, Malcolm Sim, Sergio Pablo-García, Ivan Woolhouse + 6 more
Self-driving laboratories (SDLs) are next-generation research and development platforms for closed-loop, autonomous experimentation that combine ideas from artificial intelligence, robotics, and high-performance computing. A critical component of SDLs is the decision-making algorithm used to prioritize experiments to…