Results 111 to 120 of about 853,756 (250)
Straddle carrier routing optimization at container terminals utilizing telemetry‐based prediction
International Transactions in Operational Research, Volume 34, Issue 1, Page 429-459, January 2027.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
The multiobjective transportation fractional programming model [PDF]
Computer Science Journal of Moldova, 2005 In this paper the multiobjective transportation problem of linear-fractional type with one nonlinear time constraint criterion is investigated. Particularly, the case of the identical denominators is studied. The concrete procedure to find the set of all
Alexandra I. Tkacenko
doaj
Machine‐Learning‐Enabled Wood with Nanopump Functionalization for Solar Interfacial Evaporation
ENERGY &ENVIRONMENTAL MATERIALS, Volume 9, Issue 6, November 2026.This study employed machine learning to design an iron‐cobalt‐carbon‐wood photothermal material, achieving high‐efficiency evaporation at 2.807 kg m−2 h−1 and excellent salt resistance. The integrated system increased the daily water production efficiency of solar distillation by 1.5 times, providing an innovative solution for sustainable seawater ...
Chaohai Wang +10 more
wiley +1 more source
Evolutionary algorithm using surrogate models for solving bilevel multiobjective programming problems. [PDF]
PLoS One, 2020 Liu Y, Li H, Li H.
europepmc +1 more source
Predicting EU Emissions Allowance Prices Using Macroeconomic Indicators and Hybrid AI Models
Journal of Forecasting, Volume 45, Issue 7, Page 3170-3190, November 2026.ABSTRACT Predicting carbon allowance prices has grown more crucial in relation to carbon market regulation, financial strategy, and environmental policy development. This study examines a hybrid forecasting system that combines deep learning with ensemble machine learning models to forecast the price fluctuations of EU Emissions Allowance (EUAs) within
Saptarshi Ganguly +2 more
wiley +1 more source
International Transactions in Operational Research, Volume 33, Issue 6, Page 4039-4071, November 2026.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
Options and Tradeoffs in Krabi's Coastal Land Use [PDF]
This paper explores the tradeoff options for optimal coastal land use in Krabi’s coastal land development zone (CLDZ). Maximizing the net private benefit and maximizing the net environmental benefits, subject to the constraints set by land availability ...
Tipparat Pongthanapanich
core
Guest Editorial: Computational Intelligence in Dynamic and Uncertain Environments
CAAI Transactions on Intelligence Technology, EarlyView.
Shouyong Jiang
wiley +1 more source
Ensuring connectedness for the maximum quasi‐clique and densest k‐subgraph problems
International Transactions in Operational Research, Volume 33, Issue 6, Page 3800-3824, November 2026.Abstract Given an undirected graph G$G$, a quasi‐clique is a subgraph of G$G$ with density at least γ$\gamma$ (0<γ≤1)$(0 < \gamma \le 1)$. Two optimisation problems can be defined for quasi‐cliques: the maximum quasi‐clique (MQC) problem, which finds a quasi‐clique with maximum vertex cardinality, and the densest k$k$‐subgraph (DKS) problem, which ...
Daniela Scherer dos Santos +3 more
wiley +1 more source
Le Matematiche, 1994 In this paper we present quantitative analysis of the stability set of the first kind of stochastic multiobjective programming problems with random coefficients in the multiobjective functions.
Abou-Said H. El-Banna +1 more
doaj