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Solving optimization problems in which functions are blackboxes and variables involve different types poses significant theoretical and algorithmic challeng...
BibTeX referenceSimulation of a closed-loop dc-dc converter using a physics-informed neural network-based model
The growing reliance on power electronics introduces new challenges requiring detailed time-domain analyses with fast and accurate circuit simulation tools...
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This study investigates multi-store order delivery services where customers can order from multiple stores for home delivery. We first consider separated-ord...
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Benchmarking new optimization methods on test problems is essential for assessing their performance and tuning their parameters. Yet, few problems are avail...
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Ultra-fast delivery revolutionizes food and grocery services, with several companies advertising delivery times under 15 to 30 minutes. Motivated by the mult...
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For continuing tasks, average cost Markov decision processes have well- documented value and can be solved using efficient algorithms. However, it explici...
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Benchmarking is essential for assessing the effectiveness of optimization algorithms. This is especially true in derivative-free optimization, where target ...
BibTeX referenceScheduling ISMP 2024
Researchers around the globe attend the International Symposium on Mathematical Programming (ISMP) to share their latest results in mathematics, algorithms, ...
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Hydropower generation plays a crucial role in the global energy landscape, offering a renewable and sustainable source of electricity. Accurate forecasting o...
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Algorithm NCL was devised to solve a class of large nonlinearly constrained optimization problems whose constraints do not satisfy LICQ at a solution. It ...
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In this work, we propose improved task mapping strategies for real-time electric power system simulations on heterogeneous computing clusters, considering bo...
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This work presents a new strategy to virtual bidding based on distributionally robust optimization (DRO) using a Wasserstein distance. Virtual bidding, a mec...
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We consider fair resource allocation in sequential decision-making environments modeled as weakly coupled Markov decision processes, where resource constrain...
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This paper proposes a two-phase optimization framework for short-term hydropower scheduling in the day-ahead electricity market using profile block bids grou...
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Multiobjective blackbox optimization deals with problems where the objective and constraint functions are the outputs of a numerical simulation. In this cont...
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The p
-median problem is a classical location problem where the goal is to select p
facilities while minimizing the sum of distances from each loc...
Local search methods start from a feasible solution and improve it by successive minor modifications until a solution that cannot be further improved is enco...
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Motivated by a real-world application at a large international pharmaceutical company, we tackle an integrated location-inventory-transportation problem unde...
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This paper introduces a new approach to nurse scheduling that integrates employee well-being into the decision-making process. A random forest regressor is t...
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We propose a multi-precision extension of the Quadratic Regularization (R2) algorithm that enables it to take advantage of low-precision computations, and by...
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