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Mixed Integer Linear Programs (MILPs) are essential tools for solving planning and scheduling problems across critical industries such as construction, manufacturing, and logistics. However, their widespread adoption is limited by long…

Machine Learning · Computer Science 2025-06-10 Xiaoke Wang , Batuhan Altundas , Zhaoxin Li , Aaron Zhao , Matthew Gombolay

Mixed integer linear programming (MILP) solvers expose hundreds of parameters that have an outsized impact on performance but are difficult to configure for all but expert users. Existing machine learning (ML) approaches require training on…

Machine Learning · Computer Science 2025-09-25 Connor Lawless , Yingxi Li , Anders Wikum , Madeleine Udell , Ellen Vitercik

Multi-product pipelines are a highly efficient means of transporting liquids. Traditionally used to transport petroleum, its products and derivatives, they are now being repurposed to transport liquified natural gas admixed with hydrogen of…

Optimization and Control · Mathematics 2023-12-19 Ales Wodecki , Pavel Rytir , Vyacheslav Kungurtsev , Jakub Marecek

The Big Data analytics are a logical analysis of very large scale datasets. The data analysis enhances an organization and improve the decision making process. In this article, we present Airline Delay Analysis and Prediction to analyze…

Machine Learning · Computer Science 2020-02-25 Ripon Patgiri , Sajid Hussain , Aditya Nongmeikapam

Mixed integer predictive control deals with optimizing integer and real control variables over a receding horizon. The mixed integer nature of controls might be a cause of intractability for instances of larger dimensions. To tackle this…

Optimization and Control · Mathematics 2010-03-16 Dario Bauso

This case-study aims at a comparison of the service quality of time-tabled buses as compared to on-demand ridepooling cabs in the late evening hours in the city of Wuppertal, Germany. To evaluate the service quality of ridepooling as…

Discrete Mathematics · Computer Science 2023-11-21 Hayk Asatryan , Daniela Gaul , Hanno Gottschalk , Kathrin Klamroth , Michael Stiglmayr

Using a Markov Chain Monte Carlo optimization algorithm and a computer simulation, I find the passenger ordering which minimizes the time required to board the passengers onto an airplane. The model that I employ assumes that the time that…

Physics and Society · Physics 2009-09-17 Jason H. Steffen

Decentralized planning in uncertain environments is a complex task generally dealt with by using a decision-theoretic approach, mainly through the framework of Decentralized Partially Observable Markov Decision Processes (DEC-POMDPs).…

Artificial Intelligence · Computer Science 2014-01-17 Raghav Aras , Alain Dutech

We address the multi-satellite scheduling problem with limited observation capacities that arises from the need to observe a set of targets on the Earth's surface using imaging resources installed on a set of satellites. We define and…

Optimization and Control · Mathematics 2018-12-10 Xiaoyu Chen , Gerhard Reinelt , Guangming Dai , Andreas Spitz

Multiple Air Vehicles (AVs) to prosecute geographically dispersed targets is an important optimization problem. Associated multiple tasks viz., target classification, attack and verification are successively performed on each target. The…

Artificial Intelligence · Computer Science 2015-03-17 Arindam Chaudhuri , Dipak Chatterjee , Ritesh Rajput

In this paper, we study the problem of gathering data from large-scale wireless sensor networks using multiple unmanned air vehicles (UAVs) to gather data at designated rendezvouses, where the goal is to maximize the network lifetime.…

Networking and Internet Architecture · Computer Science 2021-08-25 Chi-Hieu Nguyen , Khanh-Van Nguyen

High-level decision-making for dynamical systems often involves performance and safety specifications that are activated or deactivated depending on conditions related to the system state and commands. Such decision-making problems can be…

Optimization and Control · Mathematics 2025-04-04 Andrea Ghezzi , Armin Nurkanović , Avishai Weiss , Moritz Diehl , Stefano Di Cairano

The railway timetables are designed in an optimal manner to maximize the capacity usage of the infrastructure concerning different objectives besides avoiding conflicts. The real-time railway traffic management problem occurs when the…

Optimization and Control · Mathematics 2024-10-28 László Lindenmaier , István Ferenc Lövétei , Szilárd Aradi

Cutting planes for mixed-integer linear programs (MILPs) are typically computed in rounds by iteratively solving optimization problems, the so-called separation. Instead, we reframe the problem of finding good cutting planes as a continuous…

Optimization and Control · Mathematics 2023-07-10 Didier Chételat , Andrea Lodi

Large-scale ride-hailing systems often combine real-time routing at the individual request level with a macroscopic Model Predictive Control (MPC) optimization for dynamic pricing and vehicle relocation. The MPC relies on a demand forecast…

Artificial Intelligence · Computer Science 2021-11-08 Enpeng Yuan , Pascal Van Hentenryck

In this paper, we consider the network slicing problem which attempts to map multiple customized virtual network requests (also called services) to a common shared network infrastructure and allocate network resources to meet diverse…

Information Theory · Computer Science 2022-03-01 Wei-Kun Chen , Ya-Feng Liu , Yu-Hong Dai , Zhi-Quan Luo

Intermodal logistics typically include the successive stages of intermodal shipment and last-mile delivery. We investigate this problem under a novel Logic-Based Benders Decomposition, which exploits the staged nature of the problem to…

Optimization and Control · Mathematics 2022-10-12 Ioannis Avgerinos , Ioannis Mourtos , Georgios Zois

In this paper, we investigate the constraint typology of mixed-integer linear programming MILP formulations. MILP is a commonly used mathematical programming technique for modelling and solving real-life scheduling, routing, planning,…

Artificial Intelligence · Computer Science 2021-03-02 Vicky Mak-Hau , John Yearwood , William Moran

Airline disruption management traditionally seeks to address three problem dimensions: aircraft scheduling, crew scheduling, and passenger scheduling, in that order. However, current efforts have, at most, only addressed the first two…

Artificial Intelligence · Computer Science 2021-12-21 Kolawole Ogunsina , Daniel DeLaurentis

With the rapid development of airlines, airports today become much busier and more complicated than previous days. During airlines daily operations, assigning the available gates to the arriving aircrafts based on the fixed schedule is a…

Artificial Intelligence · Computer Science 2009-03-17 Chendong Li
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