Results 111 to 120 of about 83,757 (226)
Multiobjective simulation optimization.
, 2020 This doctoral dissertation focuses on multiobjective stochastic simulation optimization, and has been developed on the on the interface of two key research fields: operations research and artificial intelligence. Operations research models are commonly applied to support decisions in complex business and industrial systems (e.g., operations management,
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Energy Science &Engineering, EarlyView.Tri‐fuel diesel–Calophyllum inophyllum biodiesel–hydrogen operation was tested over 96 points in a diesel engine. Eight performance and emission metrics feed a preference‐agnostic Bootstrapped Empirical Multiobjective Ranking and Selection methodology, revealing load‐blend‐hydrogen windows that increase efficiency, restrain smoke, and expose NOx trade ...
C. Naga Kumar +5 more
wiley +1 more source
Beyond the Metrics: Context‐Aware Calibration for Better Drain Flow Modelling
Irrigation and Drainage, EarlyView.ABSTRACT Robust hydrological and water quality modelling is essential for advancing the understanding and management of engineered agricultural subsurface drainage systems. Achieving credible model output hinges on calibration strategies that are both rigorous and context sensitive. At the field scale, accurately capturing the dynamics of nutrient load
R. Caleb Bruhn +3 more
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Citation: 'multiobjective optimization' in the IUPAC Compendium of Chemical Terminology, 5th ed.; International Union of Pure and Applied Chemistry; 2025. Online version 5.0.0, 2025. 10.1351/goldbook.11477 • License: The IUPAC Gold Book is licensed under Creative Commons Attribution-ShareAlike CC BY-SA 4.0 International for individual terms.
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Irrigation and Drainage, EarlyView.ABSTRACT Efficient irrigation scheduling is critical in sandy soils to achieve optimum yield and maximum net benefit with minimum environmental concerns. The Environmental Policy Integrated Climate (EPIC) model was used to study the impacts of autoirrigation of corn on crop yield and soil water balance during 2019–2021 at −300 and −450 kPa for loamy ...
Muhammad Tahir +3 more
wiley +1 more source
Ordered Median Traveling Salesman Problem
Networks, EarlyView.ABSTRACT This paper introduces a novel combinatorial optimization problem with ordering constraints, termed the Ordered Median Traveling Salesman Problem (OMTSP). The OMTSP integrates key elements from both the classic Traveling Salesman Problem (TSP) and the Ordered Median Location Problem.
Ivana Ljubić +3 more
wiley +1 more source
Regional Sustainability Assessment Under Risk and Uncertainty: A Water–Energy–Food Based Framework
Sustainable Development, EarlyView.ABSTRACT Regional sustainability assessment requires integrated structures that can examine the interactions between Water–Energy–Food (WEF) systems, socio‐economic risk conditions, and performance outcomes under uncertainty. This study proposes a multidimensional framework that combines a suitability index, composite sustainability indicators ...
Murat Oturakci
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Bio‐Inspired Optimisation Methods Applied to Low Carbon Power and Energy Problems: A Survey
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT Bio‐inspired optimisation methods have been widely applied to complex real‐world problems, particularly in low‐carbon power and energy systems, where optimisation tasks often involve high‐dimensional, constrained and mixed‐integer characteristics.
Tianyu Hu +4 more
wiley +1 more source
Evolutionary Dynamic Multiobjective Optimisation Assisted by Inverse Regression Tree Predictor
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT Dynamic multiobjective optimisation problems (DMOPs) are optimisation problems with multiple conflicting objectives that can change over time. Most dynamic multiobjective optimisation evolutionary algorithms (DMOEAs) attempt to estimate Pareto‐optimal sets (PS) directly in the decision space.
Kai Gao, Lihong Xu
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