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33rd International Joint Conference on Artificial Intelligence, IJCAI 2024

作者： Černý, Jakub Ling, Chun Kai Kroer, Christian Iyengar, Garud Department of Industrial Engineering and Operations Research Columbia University United States

ISBN: (纸本)9781956792041

Security games model strategic interactions in adversarial real-world *** applications often involve extremely large but highly structured strategy sets (e.g., selecting a distribution over all patrol routes in a given graph).In this paper, we represent each player's strategy space using a layered graph whose paths represent an exponentially large strategy *** formulation entails not only classic pursuit-evasion games, but also other security games, such as those modeling anti-terrorism and logistical *** study two-player zero-sum games under two distinct utility models: linear and binary *** show that under linear utilities, Nash equilibrium can be computed in polynomial time, while binary utilities may lead to situations where even computing a best-response is computationally *** this end, we propose a practical algorithm based on incremental strategy generation and mixed integer linear *** show through extensive experiments that our algorithm efficiently computes ϵ-equilibrium for many games of *** find that target values and graph structure often have a larger influence on running times as compared to the size of the graph per se. © 2024 International Joint Conferences on Artificial Intelligence. All rights reserved.

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A folding preprocess for the max k-cut problem

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Optimization Letters 2025年第5期19卷 899-917页

作者： Fakhimi, Ramin Validi, Hamidreza Hicks, Illya V. Terlaky, Tamás Zuluaga, Luis F. Department of Industrial and Systems Engineering Lehigh University Bethlehem United States Department of Industrial Manufacturing & Systems Engineering Texas Tech University Lubbock United States Department of Computational Applied Mathematics & Operations Research Rice University Houston United States

Given graph G=(V,E) with vertex set V and edge set E, the max k-cut problem seeks to partition the vertex set V into at most k subsets that maximize the weight (number) of edges with endpoints in different parts. This paper proposes a graph folding procedure (i.e., a procedure that reduces the number of the vertices and edges of graph G) for the weighted max k-cut problem that may help reduce the problem’s dimensionality. While our theoretical results hold for any k≥2, our computational results show the effectiveness of the proposed preprocess only for k=2 and on two sets of instances. Furthermore, we observe that the preprocess improves the performance of a MIP solver on a set of large-scale instances of the max cut problem. © The Author(s) 2025.

关键词： Network theory (graphs)

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Flow Is Best, Fast and Scalable: The Incremental Parametric Cut for Maximum Density and Other Ratio Subgraph Problems 16

Flow Is Best, Fast and Scalable: The Incremental Parametric ...

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16th International Conference on Knowledge Discovery and Information Retrieval, KDIR 2024 as part of 16th International Joint Conference on Knowledge Discovery, Knowledge engineering and Knowledge Management, IC3K 2024

作者： Hochbaum, Dorit S. Department of Industrial Engineering and Operations Research University of California Berkeley United States

ISBN: (纸本)9789897587160

The maximum density subgraph, or densest subgraph, problem has numerous applications in analyzing graph and community structures in social networks, DNA networks and financial networks. The densest subgraph problem has been the subject of study since the early 80s and polynomial time flow-based algorithms are known, yet research in the last couple of decades has been focused on developing heuristic methods for solving the problem claiming that flow computations are computationally prohibitive. We introduce here a new polynomial time algorithm, the incremental parametric cut algorithm (IPC) that solves the maximum density subgraph problem and many other max or min ratio problems in the complexity of a single minimum-cut. A characterization of all these efficiently solvable ratio problems is given here as problems with monotone integer programming formulations. IPC is much more efficient than the parametric cut algorithm since instead of generating all breakpoints it explores only a tiny fraction of those breakpoints. Compared to the heuristic methods, IPC not only guarantees optimality, but also runs orders of magnitude faster than the heuristic methods, as shown in an accompanying experimental study. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Heuristic methods

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Optimizing Shipper Transportation: Analyzing Allocation Policies for In-House and Outsourced Rail Rakes using Simulation Modeling 51

Optimizing Shipper Transportation: Analyzing Allocation Poli...

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51st International Conference on Computers and industrial engineering, CIE 2024

作者： Karwasra, Kritika Rangaraj, Narayan Department of Industrial Engineering and Operations Research IIT Bombay Maharashtra Mumbai400076 India

Rail transport is highly effective for moving bulk commodities such as cement and steel over medium to long distances. Despite its potential, rail freight's share in overall logistics remains small due to service unreliability. Due to delayed services, there is uncertainty in rail fleet availability that again causes delayed shipments to customers. To increase the reliance on rail transport, companies (shipper) have started investing in their own rail fleet (sets of wagons and sets of containers). These fleets are maintained and operated by the companies, and the actual movement is handled by railway operators, often at reduced transportation costs. However, acquiring and maintaining such fleets requires substantial capital investment. To mitigate this, companies are increasingly adopting a "make-and-buy" strategy, where they procure a limited number of in-house railway rakes and use them alongside outsourced railway rakes. Along with maintaining and operating an in-house railway fleet, this mixed fleet scenario adds a layer of difficulty to fleet management at the shippers' end, requiring careful coordination to optimize fleet utilization, improve operational efficiency, and reduce cost. In this study, we address the fleet management challenges faced by shippers and provide a comprehensive framework for optimizing the use of mixed rail fleet resources. For this, a simulation model was developed for the shipper's facility to analyze the impact of various fleet allocation strategies on total transportation costs. The results provide valuable insights into how optimizing fleet allocation decisions can effectively reduce transportation costs. © 2024 Computers and industrial engineering. All rights reserved.

关键词： Fleet operations

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Positive-Unlabeled Learning Using Pairwise Similarity and Parametric Minimum Cuts 16

Positive-Unlabeled Learning Using Pairwise Similarity and Pa...

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作者： Nitayanont, Torpong Hochbaum, Dorit S. Department of Industrial Engineering and Operations Research University of California BerkeleyCA United States

ISBN: (纸本)9789897587160

Positive-unlabeled (PU) learning is a binary classification problem where the labeled set contains only positive class samples. Most PU learning methods involve using a prior π on the true fraction of positive samples. We propose here a method based on Hochbaum’s Normalized Cut (HNC), a network flow-based method, that partitions samples, both labeled and unlabeled, into two sets to achieve high intra-similarity and low inter-similarity, with a tradeoff parameter to balance these two goals. HNC is solved, for all tradeoff values, as a parametric minimum cut problem on an associated graph producing multiple optimal partitions, which are nested for increasing tradeoff values. Our PU learning method, called 2-HNC, runs in two stages. Stage 1 identifies optimal data partitions for all tradeoff values, using only positive labeled samples. Stage 2 first ranks unlabeled samples by their likelihood of being negative, according to the sequential order of partitions from stage 1, and then uses the likely-negative along with positive samples to run HNC. Among all generated partitions in both stages, the partition whose positive fraction is closest to the prior π is selected. An experimental study demonstrates that 2-HNC is highly competitive compared to state-of-the-art methods. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Contrastive Learning

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Optimal Contract Design for End-of-Life Care Payments 63

Optimal Contract Design for End-of-Life Care Payments

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Jiang, Muyan Chen, Ying Chen, Xin Lavaei, Javad Aswani, Anil University of California Department of Industrial Engineering & Operations Research BerkeleyCA94720 United States

ISBN: (纸本)9798350316339

A large fraction of total healthcare expenditure occurs due to end-of-life (EOL) care, which means it is important to study the problem of more carefully incentivizing necessary versus unnecessary EOL care because this has the potential to reduce overall healthcare spending. This paper introduces a principal-agent model that integrates a mixed payment system of fee-for-service and pay-for-performance in order to analyze whether it is possible to better align healthcare provider incentives with patient outcomes and cost-efficiency in EOL care. The primary contributions are to derive optimal contracts for EOL care payments using a principal-agent framework under three separate models for the healthcare provider, where each model considers a different level of risk tolerance for the provider. We derive these optimal contracts by converting the underlying principal-agent models from a bilevel optimization problem into a single-level optimization problem that can be analytically solved. Our results are demonstrated using a simulation where an optimal contract is used to price intracranial pressure monitoring for traumatic brain injuries. © 2024 IEEE.

关键词： Cost effectiveness

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LARGE LANGUAGE MODEL ASSISTED EXPERIMENT DESIGN WITH GENERATIVE HUMAN-BEHAVIOR AGENTS

LARGE LANGUAGE MODEL ASSISTED EXPERIMENT DESIGN WITH GENERAT...

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2024 Winter Simulation Conference, WSC 2024

作者： Liu, Haoyu Tang, Yifu Zhang, Zizhao Zheng, Zeyu Zhu, Tingyu Department of Industrial Engineering and Operations Research University of California Berkeley BerkeleyCA United States

ISBN: (纸本)9798331534202

Experiment design, despite its wide use in the fields such as economics, sociology and business operations, can sometimes encounter challenges or ethical issues when getting real human beings involved. On the other hand, the development of large language models (LLM) such as ChatGPT has empowered the development of generative agents with believable human behavior. This work develops an implementation framework to use LLM-empowered generative agents to assist experiment design where it is prohibitive to involve real human beings. © 2024 IEEE.

关键词： Chatbots

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STATISTICAL INFERENCE FOR FISHER MARKET EQUILIBRIUM 11

STATISTICAL INFERENCE FOR FISHER MARKET EQUILIBRIUM

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11th International Conference on Learning Representations, ICLR 2023

作者： Liao, Luofeng Gao, Yuan Kroer, Christian Department of Industrial Engineering and Operations Research Columbia University United States

Statistical inference under market equilibrium effects has attracted increasing attention recently. In this paper we focus on the specific case of linear Fisher markets. They have been widely use in fair resource allocation of food/blood donations and budget management in large-scale Internet ad auctions. In resource allocation, it is crucial to quantify the variability of the resource received by the agents (such as blood banks and food banks) in addition to fairness and efficiency properties of the systems. For ad auction markets, it is important to establish statistical properties of the platform's revenues in addition to their expected values. To this end, we propose a statistical framework based on the concept of infinite-dimensional Fisher markets. In our framework, we observe a market formed by a finite number of items sampled from an underlying distribution (the "observed market") and aim to infer several important equilibrium quantities of the underlying long-run market. These equilibrium quantities include individual utilities, social welfare, and pacing multipliers. Through the lens of sample average approximation (SAA), we derive a collection of statistical results and show that the observed market provides useful statistical information of the long-run market. In other words, the equilibrium quantities of the observed market converge to the true ones of the long-run market with strong statistical guarantees. These include consistency, finite sample bounds, asymptotics, and confidence. As an extension we discuss revenue inference in quasilinear Fisher markets. © 2023 11th International Conference on Learning Representations, ICLR 2023. All rights reserved.

关键词： Resource allocation

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Formulation and Solution Approach for Uncertain Multi-Objective Material Requirement Planning Problem with Multi-Mode Demand, Overtime Production, and Outsourcing Possibilities

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Journal of Systems Science and Systems engineering 2025年第1期34卷 1-28页

作者： Sadegh Niroomand Dragan Pamucar Ali Mahmoodirad Department of Industrial Engineering Firouzabad Higher Education CenterShiraz University of TechnologyShirazIran Department of Operations Research and Statistics Faculty of Organizational SciencesUniversity of BelgradeBelgradeSerbia Department of Industrial Engineering and Management Yuan Ze UniversityTaoyuan CityTaiwanChina Department of Mechanics and Mathematics Western Caspian UniversityBakuAzerbaijan Department of Mathematics Babol BranchIslamic Azad UniversityBabolIran

Material requirement planning is a type of production planning problems that is used to plan about a final product, its sub-assemblies, and its raw parts simultaneously by considering time phased demands of the final product. In this study a multi-product material requirement planning problem with limited manufacturing resources is considered. As an important novelty, a multi-mode demand strategy is considered in this problem where the total customers’ satisfaction degrees of the selected demand modes is maximized. Furthermore, three types of capacities such as regular, over time, and outsourcing capacities are considered for such system as another novelty. The problem is formulated as a bi-objective model to maximize total profit and total satisfaction degree of the customers simultaneously. To respect the uncertain nature of the problem, it is formulated in a belief-degree based uncertain form. This is for the first time in the literature of material requirement planning that this type of uncertainty is considered. The uncertain problem is converted to a crisp form using some techniques such as expected value model and chance constrained model. Then, a new hybrid form of the fuzzy programming approach is developed to solve the bi-objective crisp formulations. A case study from the petroleum industries of Iran is used to perform the required computational experiments. The required experiments are done, and possible comparisons are made on the obtained results. Furthermore, some managerial insights are given in order to be used in the production system of the case study. According to the obtained results, the proposed hybrid fuzzy programming approach is superior to existing approaches in at least 38 percent of the experiments.

关键词： Material requirement planning multi-mode demand belief-degree based uncertainty multi-objective optimization fuzzy programming approach

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Securing Legacy Interfaces of 5G Short Message Service Function (SMSF) 17

Securing Legacy Interfaces of 5G Short Message Service Funct...

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17th International Conference on COMmunication Systems and NETworkS, COMSNETS 2025

作者： Kamran, Rashmi Taksande, Pradnya Jha, Pranav Hanawal, Manjesh Chaporkar, Prasanna Indian Institute of Technology Department of Electrical Engineering Bombay India Indian Institute of Technology Department of Industrial Engineering and Operations Research Bombay India

ISBN: (纸本)9798331531195

Network Functions (NFs) in the 5th Generation (5G) mobile communication system face many security-related challenges. Usage of legacy interfaces/protocols is one of them. The Short Message Service Function (SMSF) in the 5G core is the key network function supporting the short message service (SMS) delivery over Non-Access Stratum (NAS) to User Equipment (UE). SMS over NAS is an old service, in existence since the 2nd Generation (2G) mobile communication systems. Therefore, the SMSF in 5G core may need to interface with legacy network elements/functions via non-service based (legacy) interfaces. Typically these legacy interfaces are based on Diameter and/or Mobile Application Part (MAP) protocols. It is essential to secure SMSF records and data (SMS) in transit over these legacy interfaces, as they may contain critical information such as UE identifiers, UE contexts and sensitive financial data. In this work, we present our contributions to 3rd Generation Partnership Project (3GPP)'s Release 19 5G standards, which include the security threats security-related requirements for SMSF's Diameter and MAP-based legacy interfaces as well as mechanisms to protect SMSF from these threats. These contributions were recently included in 3GPP 5G standards and Indian Telecom Security Assurance Requirements. © 2025 IEEE.

关键词： 5G mobile communication systems

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