Results 141 to 150 of about 14,756 (239)

Self‐Service and Home Delivery Combined: Coordinating the Route of a Mobile Parcel Locker With the Delivery Tasks of Its Human Driver

Networks, Volume 88, Issue 2, Page 192-210, September 2026.
ABSTRACT In response to the increasing volume of parcels, last‐mile delivery innovations are exploring the integration of multiple delivery modes. The most prominent examples are delivery vans that, next to being the base for the delivery tasks of their human drivers, also function as mobile launching platforms for drones or autonomous delivery robots.
Nils Boysen, Dirk Briskorn, Stefan Schwerdfeger   +2 more
wiley   +1 more source

Production routing decisions in a two‐echelon supply chain with multiple delivery modes

International Transactions in Operational Research, Volume 33, Issue 5, Page 3385-3421, September 2026.
Abstract We study an original two‐echelon production routing problem with multiple delivery modes (2E‐PRP‐MDM). In the first echelon, the primary production facility is tasked with satisfying the demands of two distinct entities: a set of warehouses and a set of customers through direct shipments. In the second echelon, warehouses become delivery hubs,
Rachida Benfedel, Fayçal Belkaid, Nadjib Brahimi   +2 more
wiley   +1 more source

Aquila Optimization-Assisted Artificial Neural Network for Classification Problems. [PDF]

Biomimetics (Basel)
Kayhan G, Unal SH.
europepmc   +1 more source

A preference‐integrated optimization system for medical physics shift scheduling

Journal of Applied Clinical Medical Physics, Volume 27, Issue 8, August 2026.
Abstract Background Clinical shift scheduling for medical physicists is challenging given multidisciplinary roles and competing clinical, research, and service demands. Manual workflows often lack the flexibility and transparency needed for this complex field.
Benjamin S. Rosen, Zheng Zhang, Karolyn M. Hopfensperger, Kelly C. Paradis, Choonik Lee, Lana Critchfield, Ikechi Ozoemelam, Charles K. Matrosic, Christopher Kehayias, Scott W. Hadley, James M. Balter, Claire Zhang, Lise Wei, Seyyedeh Azar Oliaei Motlagh, Alexandar Moncion, Dale W. Litzenberg, Cory Knill, Maria G. Ditman, Elizabeth L. Covington, Charles S. Mayo, Sean P. Devan, Martha M. Matuszak, Joann I. Prisciandaro   +22 more
wiley   +1 more source

Data-driven flood susceptibility assessment using hybrid machine learning and optimization techniques: case of the Sedrata Watershed, NE Algeria. [PDF]

Sci Rep
Mechentel E, Dairi S, Lefkir A, Eslamian S, Abida H, Djebbar Y.   +5 more
europepmc   +1 more source

Adaptive Weighting Ensemble Approach for High‐Fidelity PM10 Forecasting via Evolutionary TCN and Bidirectional GRU

Advanced Theory and Simulations, Volume 9, Issue 8, August 2026.
A novel adaptive weighted ensemble framework integrating BiGRU, enhanced attention‐based TCN, and linear regression improves one‐hour‐ahead PM10 forecasting by jointly capturing sequential dependencies, multi‐scale temporal patterns, and residual linear relationships.
Huseyin Cagan Kilinc, Huseyin Yildirim Dalkilic, Adem Yurtsever, Sinan Ates, Sefa Nur Yeşilyurt   +4 more
wiley   +1 more source

WS-SSA: workflow scheduling in cloud computing using salp swarm algorithm. [PDF]

Sci Rep
Sharawy AA, Sakr RH, Eladrosy W, Alrahmawy MF.   +3 more
europepmc   +1 more source

Resource Allocation for Content Distribution Using Optimized Temporally‐Aware Adaptive Graph Convolutional Network in Fog Radio Access Networks

International Journal of Communication Systems, Volume 39, Issue 12, August 2026.
New multimedia applications are emerging at a rapid rate, propelling an exponential rise in mobile internet traffic and increasing the bar for next‐generation wireless networks in service quality. This indicates the rapid advancement of wireless communication technology.
Ruchi Kawatra, J. Brundha Elci, Maria Manuel Vianny D, Rajat Bhardwaj, Rakesh Kumar G, Abhijit Das   +5 more
wiley   +1 more source

An optimization-driven hierarchical deep learning approach using the Gray Langurs algorithm for data-driven seismic activity prediction. [PDF]

Sci Rep
Shabrawy M, El-Kenawy EM, Abdel-Hamid NB, Abdelsalam MM.   +3 more
europepmc   +1 more source

Categorical Boosting‐PSO: A SHAP‐Interpretable Hybrid Framework for High‐Fidelity Wax Appearance Temperature Prediction in Subsea Pipelines

Engineering Reports, Volume 8, Issue 8, August 2026.
CatBoost–PSO accurately predicts wax appearance temperature from oil density, wax content, and pour point temperature, achieving R2 = 0.9760 and RMSE = 1.8106 K. External validation, SHAP interpretation, and low computational cost support rapid wax‐risk screening for subsea pipeline flow assurance.
H. M. Rayhan Rifat, Abdullah Abduljabbar, Mysara Eissa Mohyaldinna   +2 more
wiley   +1 more source