Solving optimization problems in which functions are blackboxes and variables involve different types poses significant theoretical and algorithmic challeng...

The growing reliance on power electronics introduces new challenges requiring detailed time-domain analyses with fast and accurate circuit simulation tools...

This study investigates multi-store order delivery services where customers can order from multiple stores for home delivery. We first consider separated-ord...

Benchmarking new optimization methods on test problems is essential for assessing their performance and tuning their parameters. Yet, few problems are avail...

Ultra-fast delivery revolutionizes food and grocery services, with several companies advertising delivery times under 15 to 30 minutes. Motivated by the mult...

For continuing tasks, average cost Markov decision processes have well- documented value and can be solved using efficient algorithms. However, it explici...

Benchmarking is essential for assessing the effectiveness of optimization algorithms. This is especially true in derivative-free optimization, where target ...

Researchers around the globe attend the International Symposium on Mathematical Programming (ISMP) to share their latest results in mathematics, algorithms, ...

Hydropower generation plays a crucial role in the global energy landscape, offering a renewable and sustainable source of electricity. Accurate forecasting o...

Algorithm NCL was devised to solve a class of large nonlinearly constrained optimization problems whose constraints do not satisfy LICQ at a solution. It ...

In this work, we propose improved task mapping strategies for real-time electric power system simulations on heterogeneous computing clusters, considering bo...

This work presents a new strategy to virtual bidding based on distributionally robust optimization (DRO) using a Wasserstein distance. Virtual bidding, a mec...

We consider fair resource allocation in sequential decision-making environments modeled as weakly coupled Markov decision processes, where resource constrain...

This paper proposes a two-phase optimization framework for short-term hydropower scheduling in the day-ahead electricity market using profile block bids grou...

Multiobjective blackbox optimization deals with problems where the objective and constraint functions are the outputs of a numerical simulation. In this cont...

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...

Motivated by a real-world application at a large international pharmaceutical company, we tackle an integrated location-inventory-transportation problem unde...

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...

We propose a multi-precision extension of the Quadratic Regularization (R2) algorithm that enables it to take advantage of low-precision computations, and by...