11 papers · ranked by Valyu relevance
Moshe Sipper, Ryan J. Urbanowicz, Jason H. Moore
Finding the objective (i.e., goal or global optimum) in machine learning (ML) and related domains, such as evolutionary algorithms (EAs), invariably involves the definition of an objective function, which is the function we want to minimize or maximize . Any objective function implicitly defines an optimization…
Marko Miladinović, Predrag Zivadinovic
We introduce an application for executing and testing different unconstrained optimization algorithms. The application contains a library of various test functions with pre-defined starting points. A several known classes of methods as well as different classes of line search procedures are covered. Each method can be…
Charalampos P. Triantafyllidis, Lazaros G. Papageorgiou, Marian Gheorghe
'Marian Gheorghe'] This paper presents a novel prototype platform that uses the same LaTeX mark-up language, commonly used to typeset mathematical content, as an input language for modeling optimization problems of various classes. The platform converts the LaTeX model into a formal Algebraic Modeling Language (AML)…
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…
Jiuyuan Huo, Liqun Liu
Parameter optimization of a hydrological model is intrinsically a high dimensional, nonlinear, multivariable, combinatorial optimization problem which involves a set of different objectives. Currently, the assessment of optimization results for the hydrological model is usually made through calculations and comparisons…
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…
Joshua L. Pulsipher, Weiqi Zhang, Tyler J. Hongisto, Víctor M. Zavala
'Ví\xadctor M. Zavala'] Infinite-dimensional optimization (InfiniteOpt) problems involve modeling components (variables, objectives, and constraints) that are functions defined over infinite-dimensional domains. Examples include continuous-time dynamic optimization (time is an infinite domain and components are a…
Ozden Ustun
In multiobjective optimization methods, multiple conflicting objectives are typically converted into a single objective optimization problem with the help of scalarizing functions. The conic scalarizing function is a general characterization of Benson proper efficient solutions of non-convex multiobjective problems in…
Florian Häse, Loïc M. Roch, Alán Aspuru-Guzik
Chimera enables multi-target optimization for experimentation or expensive computations, where evaluations are the limiting factor.
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…