Results 121 to 130 of about 68,989 (275)
Straddle carrier routing optimization at container terminals utilizing telemetry‐based prediction
Abstract Efficient vehicle routing and scheduling for horizontal transport means on container terminals can reduce lead times and travel distances, resulting in fuel savings and productivity gains. We apply machine learning to emulate operational processes, bridging the gap between theoretical optimization models and real‐world practices at container ...
Julian Neugebauer +3 more
wiley +1 more source
Abstract In situ synchrotron X‐ray computed tomography enables dynamic material studies. However, automated segmentation remains challenging due to complex imaging artefacts – like ring and cupping effects – and limited training data. We present a methodology for deep learning‐based segmentation by transforming high‐quality ex situ laboratory data to ...
Tristan Manchester +6 more
wiley +1 more source
Abstract Integrating the attention‐based view with the strategic leadership interfaces perspective, we propose a theoretical model of situational urgency mechanisms influencing the allocation of CEOs' attention towards responsive actions. Specifically, we theorize upon the role of humility, which leads CEOs towards embracing interfaces and makes them ...
Petrit Ademi +2 more
wiley +1 more source
Multi‐period optimal bidding strategy with energy storage
Abstract We consider a setting where a wind power producer (WPP) bids in a multi‐period ahead electricity market. The new elements we take into account are (i) the integration of electricity storage devices, (ii) the extension from single‐period to multi‐period optimal bidding, (iii) the implementation of a short‐sighted strategy versus a far‐sighted ...
Azin Khaleghi, Wouter Baar, Dario Bauso
wiley +1 more source
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
Abstract We propose the novel p‐branch‐and‐bound method for solving two‐stage stochastic programming problems whose deterministic equivalents are represented by non‐convex mixed‐integer quadratically constrained quadratic programming (MIQCQP) models. The precision of the solution generated by the p‐branch‐and‐bound method can be arbitrarily adjusted by
Nikita Belyak, Fabricio Oliveira
wiley +1 more source
Abstract In pharmaceutical industries, continuous manufacturing methods have already been well established to improve productivity and process intensification. However, to better understand the trade‐offs of continuous crystallizers over the existing batch production systems, a robust technoeconomic cost and sustainability analysis is necessary to ...
Jungsoo Rhim, Zoltan K. Nagy
wiley +1 more source
Optimal Control of Mobile Energy Storage via Knowledge‐Guided Deep Reinforcement Learning
This research proposes a Knowledge‐Guided DRL framework (KA‐DDPG) for mobile energy storage. By integrating offline optimization as expert guidance to manage hybrid action spaces and environmental uncertainties, our method achieves significantly higher arbitrage profits and superior operational stability compared to standard reinforcement learning and ...
Xinlei Cai +7 more
wiley +1 more source
Fani Boukouvala, R. Misener, C. Floudas
semanticscholar +1 more source
Local Polynomial Regression and Filtering for a Versatile Mesh‐Free PDE Solver
A high‐order, mesh‐free finite difference method for solving differential equations is presented. Both derivative approximation and scheme stabilisation is carried out by parametric or non‐parametric local polynomial regression, making the resulting numerical method accurate, simple and versatile. Numerous numerical benchmark tests are investigated for
Alberto M. Gambaruto
wiley +1 more source

