Stefano Nasini

A Generalized Polynomial Lower Bound for the Weighted Completion Time Variance in a Single Machine

Categories Approximation Algorithms, Combinatorial Optimization, Scheduling Tags , , ,

This paper studies the single-machine problem of minimizing the weighted completion time variance (WCTV) and proposes a polynomially computable lower-bounding framework that generalizes the benchmark introduced by Nessah and Chu (2010). We first develop a generalized augmented-sequence decomposition that mathematically connects the weighted problem with the classical unweighted variance setting. Using this decomposition, we derive … Read more

Equivalence-Based Reduction and Incremental Optimization for Categorical and Ordinal Classification

Categories Data Science Algorithms, Data-Mining, Optimization in Data Science

Exact mathematical programming formulations for estimating classification rules provide guarantees of empirical optimality, but their size grows rapidly with the number of predictive features and model complexity. This paper shows that interpretable classifiers can be estimated by directly maximizing empirical classification accuracy under complexity constraints, using truncation and warm-start strategies compatible with disjunctive normal form … Read more

The Minimization of the Weighted Completion Time Variance in a Single Machine: A Specialized Cutting-Plane Approach

Categories (Mixed) Integer Linear Programming, Branch and Cut Algorithms, Scheduling

This study addresses the problem of minimizing the weighted completion time variance (WCTV) in single-machine scheduling. Unlike the unweighted version, which has been extensively studied, the weighted variant introduces unique challenges due to the absence of theoretical properties that could guide the design of efficient algorithms. We propose a mathematical programming framework based on a … Read more

A Generalized Voting Game for Categorical Network Choices

Categories Combinatorial Optimization, Data Science Algorithms, Game Theory Tags , , ,

This paper develops a unified game-theoretical framework for data classification and network discovery based on pairwise influences in multivariate categorical choices. Data points, interpreted as individuals, are connected through a signed weighted graph and take values according to a voting rule that aggregates the influence of attractive (friend-like) and repulsive (enemy-like) neighbors. The framework consists … Read more

Nash Bargaining Partitioning in Decentralized Portfolio Management

Categories Finance and Economics, Game Theory, Stochastic Programming Tags , , , ,

In the context of decentralized portfolio management, understanding how to distribute a fixed budget among decentralized intermediaries is a relevant question for financial investors. We consider the Nash bargaining partitioning for a class of decentralized investment problems, where intermediaries are in charge of the portfolio construction in heterogeneous local markets and act as risk/disutility minimizers. … Read more

An Almost Exact Multi-Machine Scheduling Solution for Homogeneous Processing

Categories (Mixed) Integer Nonlinear Programming, Combinatorial Optimization, Scheduling

In the context of job scheduling in parallel machines, we present a class of asymptotically exact binary programs for the minimization of the $\tau$-norm of completion time variances. Building on overlooked properties of the min completion time variance in a single machine and on an equivalent bilevel formulation, our approach provides an asymptotic approximation (with … Read more

Multi-market Portfolio Optimization with Conditional Value at Risk

Categories Applications - OR and Management Sciences, Cutting Plane Approaches, Integer Programming

In this paper we propose an optimization framework for multi-markets portfolio management, where a central headquarter relies upon local affiliates for the market-wise selection of investment options. Being averse to risk, the headquarter endogenously selects the maximum expected loss (conditional value at risk) for the affiliates, who respond designing portfolios and selecting management fees. In … Read more

An Almost Exact Solution to the Min Completion Time Variance in a Single Machine

Categories 0-1 Programming, Combinatorial Optimization, Scheduling Tags , , ,

We consider a single machine scheduling problem to minimize the completion time variance of n jobs. This problem is known to be NP-hard and our contribution is to establish a novel bounding condition for a characterization of an optimal sequence. Specifically, we prove a necessary and sufficient condition (which can be verified in O(n\log n)) … Read more

An integrated planning model in centralized power systems

Categories Applications - OR and Management Sciences, Network Optimization, Stochastic Programming

In the context of centralized electricity markets, we propose an integrated planning model for power pricing and network expansion, which endogenizes the scaling costs from power losses. While the substitutability pattern between pricing and expansion has been overlooked in the power flow optimization literature, this becomes particularly relevant in centralized electricity markets (where the headquarters … Read more

A specialized interior-point algorithm for huge minimum convex cost flows in bipartite networks

Categories Linear Programming, Network Optimization

The computation of the Newton direction is the most time consuming step of interior-point methods. This direction was efficiently computed by a combination of Cholesky factorizations and conjugate gradients in a specialized interior-point method for block-angular structured problems. In this work we apply this algorithmic approach to solve very large instances of minimum cost flows … Read more