23 papers · ranked by Valyu relevance
Julio R. Banga, Sebastian Säger
Living organisms exhibit remarkable adaptations across all scales, from molecules to ecosystems. We believe that many of these adaptations correspond to optimal solutions driven by evolution, training, and underlying physical and chemical laws and constraints. While some argue against such optimality principles due to…
Barbara Schnitzer, Linnea Österberg, Marija Cvijovic
Flux balance analysis (FBA) is a powerful tool to study genome-scale models of the cellular metabolism, based on finding the optimal flux distributions over the network. While the objective function is crucial for the outcome, its choice, even though motivated by evolutionary arguments, has not been directly connected…
Rachel Gaffney, Magnus Rattray, Jean-Marc Schwartz, Kate Meeson
There are huge variations in metabolic complexity between the different kingdoms of life. Whilst it has been shown that some simple, unicellular organisms such as E. coli direct their energetic resources towards maximising proliferation, the metabolic goals of more complex organisms are unclear. This is an especially…
James Morrissey, Mariana Monteiro, Michael Betenbaugh, Cleo Kontoravdi
Metabolism reflects evolutionary priorities that govern how cells allocate resources. In mammalian cells, metabolic objectives are layered and context-dependent, making it difficult to pinpoint the priorities that underlie observed phenotypes. Here, we introduce ObjFind-M, an inverse optimization framework that infers…
Wolfgang Rannetbauer, Simon Hubmer, Carina Hambrock, Ronny Ramlau
Achieving both high quality and cost-efficiency are two critical yet often conflicting objectives in manufacturing and maintenance processes. Quality standards vary depending on the specific application, while cost-effectiveness remains a constant priority. These competing objectives lead to multi-objective…
Neeraj Dhanraj Bokde
Multi-Objective Optimization Authors: ['Neeraj Dhanraj Bokde'] Abstract The Jaya R package offers a robust and versatile implementation of the parameter-free Jaya optimization algorithm, suitable for solving both single-objective and multi-objective optimization problems. By integrating advanced features such as…
Zoran Jakšić, Swagata Devi, Olga Jakšić, Koushik Guha + 3 more
The application of artificial intelligence in everyday life is becoming all-pervasive and unavoidable. Within that vast field, a special place belongs to biomimetic/bio-inspired algorithms for multiparameter optimization, which find their use in a large number of areas. Novel methods and advances are being published at…
D. Tarunika, Ashish Sharma
Multi-objective optimization problems (MOPs) demand algorithms that effectively balance convergence, diversity, and computational efficiency. To address this challenge, a novel Multi-Objective Human Evolutionary Optimization Algorithm (MOHEOA) is proposed, inspired by the dynamics of human societal evolution. MOHEOA…
Akiyoshi Sannai, Yasunari Hikima, Ken Kobayashi, Akinori Tanaka + 1 more
'Naoki Hamada'] In this paper, we propose a strategy to construct a multi-objective optimization algorithm from a single-objective optimization algorithm by using the Bézier simplex model. Also, we extend the stability of optimization algorithms in the sense of Probability Approximately Correct (PAC) learning and…
Doaa El-Nagar, Ibrahim Zeidan, Mohamed Issa
The Multi-Objective Sinh-Cosh Optimization Algorithm (MOSCHO) is presented in this article based on the memorized technique. MOSCHO is an extension version of the recently proposed Sinh-Cosh optimizer for multiple objective optimizations. The memorized local optimum is integrated with the global optimal solution to…
Sowmya Ravichandran, Premkumar Manoharan, Deepak Kumar Sinha, Pradeep Jangir + 2 more
Focusing on practical engineering applications, this study introduces the Multi-Objective Resistance-Capacitance Optimization Algorithm (MORCOA), a new approach for multi-objective optimization problems. MORCOA uses the transient response behaviour of resistance-capacitance circuits to navigate complex optimization…
Alina Selega, Kieran R. Campbell
Many practical applications require optimization of multiple, computationally expensive, and possibly competing objectives that are well-suited for multi-objective Bayesian optimization (MOBO) procedures. However, for many types of biomedical data, measures of data analysis workflow success are often heuristic and…
Shannon Bonke, Giovanni Trezza, Luca Bergamasco, Hongwei Song + 4 more
The sunlight-driven reduction of CO2 into fuels and platform chemicals is a promising approach to enable a circular economy. However, established optimisation approaches are poorly suited to multi-variable multi-metric photocatalytic systems because they aim to optimise one performance metric while sacrificing the…
Riley Hickman, Priyansh Parakh, Austin Cheng, Qianxiang Ai + 3 more
Experiment planning algorithms are a required component of autonomous platforms for scientific discovery. Selecting a suitable optimization algorithm for a novel application is an important yet difficult choice a researcher has to make based on past empirical performance on similar tasks. To facilitate the evaluation…
Sandhya Rani Gaddam, Sarada Jayan, Pentakota Ravi, Bilal Alatas + 1 more
'Anand Paul'] Lead generation is the process of gaining potential customers’ interest to increase future sales, and it is an essential part of many businesses’ (amusement parks, theme parks, clubs, etc.) sales processes as their membership is more expensive. The main objective of these businesses is to increase the…
Noor A. Rashed, Yossra H. Ali, Tarik A. Rashid, Ahmed Salih
Algorithms, Applications, and Trends for Solving Complex Real-World Problems Authors: ['Noor A. Rashed' 'Yossra H. Ali' 'Tarik A. Rashid' 'Ahmed Salih'] Multi-Objective Optimization (MOO) techniques have become increasingly popular in recent years due to their potential for solving real-world problems in various…
M.Z. Naser, Mohammad Khaled al-Bashiti, Arash Teymori Gharah Tapeh, Armin Dadras Eslamlou + 6 more
Optimization Algorithms and Metaheuristics with Mathematical and Visual Descriptions Authors: ['M.Z. Naser' '\u202c\u202c\u202cMohammad Khaled al-Bashiti' 'Arash Teymori Gharah Tapeh' 'Armin Dadras Eslamlou' 'Ahmed Z. Naser' 'Venkatesh Kodur' 'Rami Hawileeh' 'Jamal A. Abdalla' 'Nima Khodadadi' 'Amir H. Gandomi'] In the…
Authors not listed
Solving optimization problems, especially for nonlinear and constrained systems, is a challenge. Decades of specialized algorithms have been developed for general and special cases of root finding, minimization (including constraints), for parameter estimation, and mapping connected spaces. These approaches typically…
Adrian L. Hauber, Marcus Rosenblatt, Jens Timmer
Ordinary differential equations are frequently employed for mathematical modeling of biological systems. The identification of mechanisms that are specific to certain cell types is crucial for building useful models and to gain insights into the underlying biological processes. Regularization techniques have been…
Domagoj Dorešić, Stephan Grein, Jan Hasenauer
Quantitative dynamical models facilitate the understanding of biological processes and the prediction of their dynamics. The parameters of these models are commonly estimated from experimental data. Yet, experimental data generated from different techniques do not provide direct information about the state of the…
Cesare Carissimo, Marcin Korecki
Optimization is about finding the best available object with respect to an objective function. Mathematics and quantitative sciences have been highly successful in formulating problems as optimization problems, and constructing clever processes that find optimal objects from sets of objects. As computers have become…
Riley Hickman, Matteo Aldeghi, Alán Aspuru-Guzik
Model-based optimization strategies, such as Bayesian optimization (BO), have been deployed across the natural sciences in design and discovery campaigns due to their sample efficiency and flexibility. The combination of such strategies with automated laboratory equipment and/or high-performance computing in a…
Seyed Mahdi Shavarani, Mahmoud Golabi, Richard Allmendinger, Lhassane Idoumghar
Drifts in Interactive Evolutionary Multi-Objective Optimization Authors: ['Seyed Mahdi Shavarani' 'Mahmoud Golabi' 'Richard Allmendinger' 'Lhassane Idoumghar'] Abstract—Evolutionary Multi-Objective Optimization Algorithms (EMOAs) are widely employed to tackle problems with multiple conflicting objectives. Recent…