Abstract In response to the increasing complexity of modern products, dynamic markets, and intensified competition, project‐based organizations are actively seeking methodologies to efficiently manage their expanding project portfolios. This paper analyzes the project portfolio selection problem in uncertain environments. Despite recent advances in the
Miguel Saiz +3 more
wiley +1 more source
Optimizing solar power forecasting with metaheuristic algorithms and deep learning models for photovoltaic grid connected systems. [PDF]
Mohamad Radzi PNL +5 more
europepmc +1 more source
Abstract One of the most common problems in the expansion of a company consists of deciding the most appropriate locations for their facilities. This decision problem, known as the facility location problem, has been studied from different perspectives, considering a number of different constraints.
Enrique García‐Galán +2 more
wiley +1 more source
Machine learning estimating paracetamol solubility in supercritical CO<sub>2</sub> by utilization of K-nearest neighbor regression and metaheuristic algorithms. [PDF]
Thajudeen KY +3 more
europepmc +1 more source
Abstract This paper investigates an extension of the vehicle routing problem in which, in addition to minimizing the distance traveled, the sequencing of customer visits is subject to precedence constraints that impose visiting priorities among customers.
Eduardo dos Santos Teixeira +1 more
wiley +1 more source
Optimizing solar farm interconnection networks using graph theory and metaheuristic algorithms with economic and reliability analysis. [PDF]
Ghias-Nodoushan A +3 more
europepmc +1 more source
The impact of public drop‐off boxes and autonomous delivery robots in last‐mile delivery
Abstract The growing concern over emissions from last‐mile logistics is motivating the development of innovative delivery models aimed at reducing environmental impact and traffic congestion. To this end, we propose a last‐mile delivery scheme based on both public drop‐off boxes and autonomous delivery robots.
Gianpaolo Ghiani +3 more
wiley +1 more source
Comparative optimization of PIDN and fractional order controllers for a quarter car active suspension system using recent metaheuristic algorithms. [PDF]
Özbilgin F +4 more
europepmc +1 more source
This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani +7 more
wiley +1 more source
Recent metaheuristic algorithms for solving some civil engineering optimization problems. [PDF]
Houssein EH +3 more
europepmc +1 more source

