Integrating Order-to-Delivery Time Sensitivity in E-Commerce Middle-Mile Consolidation Network Design

Categories Production and Logistics, Supply Chain Management, Transportation Tags , , ,

This paper proposes an approach that leverages data on customer purchasing sensitivity to quoted order-to-delivery times (ODTs) when designing middle-mile consolidation networks to maximize the profit of e-commerce retailers. Our approach integrates quoted ODT-dependent sales volume predictions into a new mixed-integer program (MIP) that simultaneously determines ODT quotes and a consolidation plan, characterized by the … Read more

Exploiting user-supplied Decompositions inside Heuristics

Categories Integer Programming Tags , , , ,

Numerous industrial fields, like supply chain management, face mixed-integer optimization problems on a regular basis. Such problems typically show a sparse structure and vary in size, as well as complexity. However, in order to satisfy customer demands, it is crucial to find good solutions to all such problems quickly. Current research often focuses on the … Read more

The Vehicle Routing Problem with Access Restrictions

Categories Applications - OR and Management Sciences, Production and Logistics, Transportation Tags , , , ,

To mitigate the negative effect of freight vehicles on urban areas, many cities have implemented road accessibility restrictions, including limited traffic zones, which restrict access to specific areas during certain times of the day. Implementing these zones creates a trade-off between the delivery cost and time, even under the assumption of equal traversal time and … Read more

Improved Rank-One-Based Relaxations and Bound Tightening Techniques for the Pooling Problem

Categories Applications - Science and Engineering Tags , , ,

The pooling problem is a classical NP-hard problem in the chemical process and petroleum industries. This problem is modeled as a nonlinear, nonconvex network flow problem in which raw materials with different specifications are blended in some intermediate tanks, and mixed again to obtain the final products with desired specifications. The analysis of the pooling … Read more

A Tailored Derivative Instrument to Mitigate the Price-and-Quantity Risk faced by Wind Power Companies

Categories Energy, Finance and Economics Tags , , , , ,

The intermittent nature of wind generation combined with the well-known volatility of electricity spot prices expose Wind Power Companies (WPCs) committed to long-term forward contracts to the so-called price-and-quantity risk. Several instruments were designed in the past years to mitigate this risk exposure. However, most of them were mainly constructed to cope with only one … Read more

Mind the \(\tilde{O}\): asymptotically better, but still impractical, quantum distributed algorithms

Categories Combinatorial Optimization, Graphs and Matroids Tags , , , ,

The CONGEST and CONGEST-CLIQUE models have been carefully studied to represent situations where the communication bandwidth between processors in a network is severely limited. Messages of only \( O(log(n)) \) bits of information each may be sent between processors in each round. The quantum versions of these models allow the processors instead to communicate and … Read more

The set partitioning problem in a quantum context

Categories (Mixed) Integer Linear Programming, Combinatorial Optimization, Integer Programming

The set partitioning problem and its decision variant (i.e., the exact cover problem) are combinatorial optimization problems that were historically crucial in the quantum optimization community. This problem is also employed in the main problem of the branch-and-price approach in many real-world optimization problems, including, but not limited to, redistricting and scheduling. Motivated by recent … Read more

Connections between Robust and Bilevel Optimization

Categories Robust Optimization Tags , ,

Robust and bilevel optimization share the common feature that they involve a certain multilevel structure. Hence, although they model something rather different when used in practice, they seem to have a similar mathematical structure. In this paper, we analyze the connections between different types of robust problems (static robust problems with and without decision-dependence of … Read more

Efficient Cross-Validation for Sparse Linear Regression

Categories (Mixed) Integer Nonlinear Programming, Data Science Algorithms

Given a high-dimensional covariate matrix and a response vector, ridge-regularized sparse linear regression selects a subset of features that explains the relationship between covariates and the response in an interpretable manner. To choose hyperparameters that control the sparsity level and amount of regularization, practitioners commonly use k-fold cross-validation. However, cross-validation substantially increases the computational cost … Read more