This paper studies disjunctive cutting planes in Mixed-Integer Conic Programming. Building on conic duality, we formulate a cut-generating conic program for...

Data acquisition and recording in the form of databases are routine operations. The process of collecting data, however, may experience irregularities, res...

This work reviews blackbox optimization applications over the last twenty years, addressed using direct search optimization methods. Emphasis is placed on...

We consider a deterministic two-player linear-state differential game, where Player 1 uses piecewise continuous controls, while Player 2 implements impulse...

In this paper, we propose a simple oligopoly game model to represent the interactions between coalitions of countries in deploying Carbon Dioxide Removal ...

The design of key nonlinear systems often requires the use of expensive blackbox simulations presenting inherent discontinuities whose positions in the varia...

We study a new variant of the vehicle routing problem, which arises in hospital-wide scheduling of physical therapists. Multiple service locations exist for...

In this paper, we introduce a framework for new product dfiffusion that integrates consumer heterogeneity and strategic interactions at individual level. For...

We consider the iterative solution of regularized saddle-point systems. When the leading block is symmetric and positive semi-definite on an appropriate sub...

We provide eigenvalues bounds for a new formulation of the step equations in interior methods for convex quadratic optimization. The matrix of our formulati...

In this paper, we apply a flexibility based operational planning paradigm to microgrid (MG) energy dispatch. The classic energy dispatch problem with energ...

The Mars Curiosity rover is frequently sending back engineering and science data that goes through a pipeline of systems before reaching its final destinati...

Column generation (CG) algorithms are well known to suffer from convergence issues due, mainly, to the degenerate structure of their master problem and the ...

We consider an integrated optimization problem including the production, inventory, and outbound transportation decisions where a central plant fulfills the ...

Restless bandits are a class of sequential resource allocation problems concerned with allocating one or more resources among several alternative processes...

Deep learning has redefined modern standards and performance in several areas such as computer vision and natural language processing. With increasing amou...

Column generation (CG) is widely used for solving large-scale optimization problems. This article presents a new approach based on a machine learning (ML) t...

Artificial Intelligence (AI) is the next society transformation builder. Massive AI-based applications include cloud servers, cell phones, cars, and pandemic...

In time-to-event data analysis, the main object of interest is the time elapsed between the occurrence of two ordered events, say \(E_1, E_2\). Sampling fr...

We introduce a novel ensemble learning approach which combines random partitions models through Potts clustering with a non-parametric predictor such as sha...