Four Hessian-informed trust-region filter variants using low- and high-fidelity surrogates reduce iterations and black-box evaluations by up to an order of magnitude on 25 benchmarks and five engineering cases while lowering tuning sensitivity.
Pyomo: modeling and solving mathematical programs in Python
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DeQL is a SQL extension for decision queries that define candidate options from relations and declare variables, constraints, and objectives to compute optimal actions.
A supernetwork-based TPMS unifies ATP choices with dynamic assignment via splitting ratios for survey calibration and includes a multi-visit VRP without enumeration.
A trust-region funnel algorithm for gray-box optimization achieves global convergence to first-order critical points and performs comparably or better than the classical trust-region filter method.
citing papers explorer
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Trust-region filter algorithms utilizing Hessian information for gray-box optimization
Four Hessian-informed trust-region filter variants using low- and high-fidelity surrogates reduce iterations and black-box evaluations by up to an order of magnitude on 25 benchmarks and five engineering cases while lowering tuning sensitivity.
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DeQL: A Decision Query Language for Prescriptive Analytics over Relational Data
DeQL is a SQL extension for decision queries that define candidate options from relations and declare variables, constraints, and objectives to compute optimal actions.
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Integrating Travel Demand and Network Modelling: a Myth or Future of Transport Modelling
A supernetwork-based TPMS unifies ATP choices with dynamic assignment via splitting ratios for survey calibration and includes a multi-visit VRP without enumeration.
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A trust-region funnel algorithm for gray-box optimization
A trust-region funnel algorithm for gray-box optimization achieves global convergence to first-order critical points and performs comparably or better than the classical trust-region filter method.