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A Flexible Framework for Polynomial-Time Resource Allocation in Streaming Multiflow Wireless Networks

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2012年第3期11卷 952-963页

作者： Middleton, Gareth Aazhang, Behnaam Lilleberg, Jorma Rice Univ Ctr Multimedia Commun Houston TX 77251 USA Univ Oulu Ctr Wireless Commun Oulu Finland Renesas Mobile Oulu Finland

We present a wide-area, multiflow ad-hoc network model leveraging information-theoretic rate control, emphasizing interfering rather than colliding transmissions. We seek to allocate resources in this network by optimizing scheduling, routing and power control to solve the max-min throughput problem for all flows involved. In general, our time-slotted, fully-interfering model leads to an NP-hard problem. Further, the rate-control element of the mixed-integer program results in a non-convex problem in the continuous domain. The complexity of the joint problem makes an optimal solution prohibitively difficult to find, leading us to propose a two-pronged approach to determine a near-optimal resource allocation. First, we propose a novel decomposition technique, breaking the joint problem into a sequence of more tractable subproblems. Second, we present a data structure serving multiple purposes: it compactly represents network conditions as they evolve with time, and also serves as the basis for our cubic-time dynamic programming algorithms used to solve and catalog the subproblems. The result is a schedule, route, and power allocation for all data frames involved. We demonstrate the performance of our techniques on the max-min throughput problem, while also showing that they are sufficiently general to apply to a wide variety of optimality criteria in which decisions over transmission schedules and packet routing must be made.

关键词： Resource allocation scheduling routing mixed-integer programming

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Valid inequalities and separation for capacitated fixed charge flow problems

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DISCRETE APPLIED MATHEMATICS 2000年第3期98卷 265-274页

作者： Stallaert, J Univ Texas Austin TX 78712 USA

This paper discusses a simple procedure to derive network inequalities for capacitated fixed charge network problems. Properties of the fractional extreme points of the LP relaxation are used to construct a class of inequalities and to construct a computational heuristic procedure for generating violated cutting planes. Computational results confirm the usefulness of the procedure. (C) 2000 Elsevier Science B.V. All rights reserved.

关键词： capacitated fixed charge networks mixed-integer programming polyhedral cuts network design

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Integrated reliability centered distribution system planning - Cable routing and switch placement

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ENERGY REPORTS 2021年 7卷 3099-3115页

作者： Zarkovic, Sanja Duvnjak Shayesteh, Ebrahim Hilber, Patrik KTH Royal Inst Technol Sch Elect Engn & Comp Sci Dept Electromagnet Engn Stockholm Sweden Swedish Natl Grid Stockholm Sweden

Distribution utilities aim to operate and plan their network in a secure and economical way. The prime focus of this work is to assist utilities by developing a new integrated approach which considers the impacts of system reliability in distribution system planning (DSP). This approach merges different problems together and solves them in a two-stage process, as follows: 1. cable routing and optimal location and number of switching devices (circuit breakers and reclosers);2. optimal location and number of tie switches. Moreover, the possibility of installing different cable options, with different prices and capacities, is included. The optimization algorithm is designed using mixed-integer programming (MIP). The developed algorithm analytically evaluates relationships between different components in the system and dynamically updates reliability indices, failure rate and restoration time, of every node in the system. This approach has been tested on two distribution systems. Despite the complexity and the exhaustiveness of the problem, MIP converges and provides the optimal solution for every studied scenario. The results show that an integrated approach enables utilities to obtain more comprehensive solutions. Moreover, by understanding the impact of parameter variation enables utilities to categorize their priorities in the decision making process and optimally invest in distribution network with respect to reliability. (C) 2021 The Authors. Published by Elsevier Ltd.

关键词： Cable routing Distribution system planning mixed-integer programming Network configuration Optimal switch placement Power system reliability Sectionalizers Tie switches

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Enabling demand response for optimal deployment of multi-carrier microgrids incorporating incentives

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IET RENEWABLE POWER GENERATION 2022年第3期16卷 547-564页

作者： Azimian, Mahdi Amir, Vahid Javadi, Saeid Siano, Pierluigi Alhelou, Hassan Haes Islamic Azad Univ Kashan Branch Dept Elect & Comp Engn Kashan Iran Univ Salerno Dept Management & Innovat Syst Salerno Italy Univ Coll Dublin Sch Elect & Elect Engn Dublin Ireland

Customer multi-carrier microgrid deployments' techno-economic viability and assists investors in deciding whether or not to invest in multi-carrier microgrid installations equipped with smart demand-side technologies are inspected here. The solution of the proposed model determines the optimal mix and size of distributed energy resources, and identifies the ideal participation rate of potential responsive customers within the multi-carrier microgrid. The objective of the proposed model is to minimize the overall deployment cost comprising the investment and replacement of distributed energy resources, demand-side smart measurement and informing appliances, loan payoff, operation, maintenance, peak demand charge, energy demand shifting reward or penalty, emission, and unserved energy while ensuring the desired levels of reliability and online reserve. The model also considers incentive policies to encourage customers to install demand-side smart technologies to participate in demand response programs actively. The planning problem is formulated by mixed-integer programming. The proposed model is applied to an industrial zone as an aggregate load. Numerical simulations exhibit the model's efficacy and scrutinize in-depth, the effect of a variety of factors on multi-carrier microgrid planning results, including the extents of the capital investment fund and loan in addition to demand response enabling technology cost.

关键词： investment demand response programs distributed power generation incentive policies deployment cost peak demand charge demand-side smart technologies multicarrier microgrid installations response enabling technology cost power generation economics integer programming distributed energy resources power generation planning smart demand-side technologies demand-side smart measurement multicarrier microgrid planning results unserved energy mixed-integer programming potential responsive customers energy demand customer multicarrier microgrid deployments demand side management optimal deployment power generation reliability ideal participation rate capital investment fund

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Prediction of Sepsis Related Mortality: An Optimization Approach

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IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS 2021年第11期25卷 4207-4216页

作者： Agor, Joseph K. Paramita, Ni Luh Putu S. P. Ozaltn, Osman Y. Oregon State Univ Sch Mech Ind & Mfg Engn Corvallis OR 97331 USA North Carolina State Univ Operat Res Grad Program Raleigh NC 27695 USA North Carolina State Univ Edward P Fitts Dept Ind & Syst Engn Raleigh NC 27695 USA

Sepsis is a condition that progresses quickly and is a major cause of mortality in hospitalized patients. Data-driven diagnostic and therapeutic interventions are essential to ensure early diagnosis and appropriate care. The Sequential Organ Failure Assessment (SOFA) score is widely utilized in clinical practice to assess septic patients for organ dysfunction. The SOFA score uses points between 0 and 4 to quantify the level of dysfunction in six organ systems. These points are determined based on expert opinion and not informed by data, thus their usefulness can vary among different medical institutions depending on the targeted use. In this study, we propose multiple strategies to adjust the SOFA score using mixed-integer programming to improve the in-hospital mortality prediction of septic patients based on Electronic Health Records (EHRs). We use the same variables and threshold values of the original SOFA score in each strategy. Thus, the proposed approach takes advantage of optimization and data analysis while taking into account the medical expertise. Our results demonstrate a statistically significant improvement (p < 0.001) in the prediction of in-hospital mortality among patients susceptible to sepsis when implementing our proposed strategies. Area under the receiver operator curve (AUC) and accuracy values of 0.8928 and 0.8904 are achieved by optimizing the point values of the SOFA score.

关键词： Sepsis SOFA score optimization mixed-integer programming electronic health records

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Network Protection Against Node Attacks Based on Probabilistic Availability Measures

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IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT 2021年第3期18卷 2742-2763页

作者： Pioro, Michal Mycek, Mariusz Tomaszewski, Artur Warsaw Univ Technol Inst Telecommun PL-00665 Warsaw Poland

We consider a network security and configuration management problem of locating service controllers so as to maximize availability of services in case of targeted attacks on the network infrastructure. Assuming that the attacker has full knowledge of the network topology but can only try to predict controller locations, we model the attacker's behavior introducing a set of probabilistic network availability measures and formulating an optimization problem model that determines the potentially most dangerous attacks the attacker might launch. We also formulate a counter-part optimization model that allows the network operator to derive the optimal placement of controllers, which maximizes availability of services with respect to a given set of network attacks. We explain the models and illustrate our considerations using a running small, intuitive network example. And we also perform extensive numerical experiments with a realistic network data to evaluate and compare the potential effectiveness of different attack strategies, and the effectiveness of the counter-measures that the network operator can adopt.

关键词： Optimization Control systems Resilience Probabilistic logic Knowledge engineering Planning Network topology Resilience against large-scale attacks control nodes SDN network operator perspective attack prediction control node placement mixed-integer programming

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EUGENE: an optimization model for integrated regional solid waste management planning

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INTERNATIONAL JOURNAL OF ENVIRONMENT AND POLLUTION 1999年第2-3期12卷 280-307页

作者： Berger, C Savard, G Wizere, A Ecole Hautes Etud Commerciales Gerad Montreal PQ H3T 2A7 Canada Gerad Montreal PQ H3B 3A7 Canada Ecole Polytech Dept Math & Genie Ind Montreal PQ H3B 3A7 Canada

This paper presents a sophisticated mixed-integer linear programming model developed to help regional decision-makers in the longterm planning of solid waste management activities. The model removes practically all the limitations of earlier integrated waste management models. All the features and capabilities of the tool are described in technical and nontechnical language. The paper includes statistics from a real-world application, and some directions for future developments.

关键词： integrated solid waste management mixed-integer programming modelling optimization regional systems systems analysis

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The Commute Trip-Sharing Problem

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TRANSPORTATION SCIENCE 2020年第6期54卷 1640-1675页

作者： Hasan, Mohd Hafiz Van Hentenryck, Pascal Legrain, Antoine Univ Michigan Coll Engn Ann Arbor MI 48109 USA Georgia Inst Technol Coll Engn Atlanta GA 30332 USA Polytech Montreal Dept Math & Ind Engn Montreal PQ H3T 1J4 Canada

Parking pressure has been steadily increasing in cities as well as on university and corporate campuses. To relieve this pressure, this paper studies a carpooling platform that would match riders and drivers while guaranteeing a ride back and exploiting spatial and temporal locality. In particular, the paper formalizes the commute trip-sharing problem (CTSP) to find a routing plan that maximizes ride sharing for a set of commute trips. The CTSP is a generalization of the vehicle routing problem with routes that satisfy time-window, capacity, pairing, precedence, ride-duration, and driver constraints. The paper introduces two exact algorithms for the CTSP: a route-enumeration algorithm and a branch-and-price algorithm. Experimental results show that on a high-fidelity real-world data set of commute trips from a midsize city, both algorithms optimally solve small and medium-sized problems and produce high-quality solutions for larger problem instances. The results show that carpooling, if widely adopted, has the potential to reduce vehicle usage by up to 57% and decrease vehicle miles traveled by up to 46% while incurring only a 22% increase in average ride time per commuter for the trips considered.

关键词： ride sharing vehicle routing with time windows column generation branch and price mixed-integer programming

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The Airlift Planning Problem

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TRANSPORTATION SCIENCE 2019年第3期53卷 773-795页

作者： Bertsimas, Dimitris Chang, Allison Misic, Velibor V. Mundru, Nishanth MIT Sloan Sch Management 77 Massachusetts Ave Cambridge MA 02139 USA MIT Operat Res Ctr 77 Massachusetts Ave Cambridge MA 02139 USA MIT Lincoln Lab Lexington MA 02420 USA Univ Calif Los Angeles Anderson Sch Management Los Angeles CA USA

The U.S. Transportation Command (USTRANSCOM) is responsible for planning and executing the transportation of U.S. military personnel and cargo by air, land, and sea. The airlift planning problem faced by the air component of USTRANSCOM is to decide how requirements (passengers and cargo) will be assigned to the available aircraft fleet and the sequence of pickups and drop-offs that each aircraft will perform to ensure that the requirements are delivered with minimal delay and with maximum utilization of the available aircraft. This problem is of significant interest to USTRANSCOM because of the highly time-sensitive nature of the requirements that are typically designated for delivery by airlift, as well as the very high cost of airlift operations. At the same time, the airlift planning problem is extremely difficult to solve because of the combinatorial nature of the problem and the numerous constraints present in the problem (such as weight restrictions and crew rest requirements). In this paper, we propose an approach for solving the airlift planning problem faced by USTRANSCOM based on modern, large-scale optimization. Our approach relies on solving a large-scale mixed-integer programming model that disentangles the assignment decision (which aircraft will pickup and deliver which requirement) from the sequencing decision (in what order the aircraft will pickup and deliver its assigned requirements), using a combination of heuristics and column generation. Through computational experiments with both a simulated data set and a planning data set provided by USTRANSCOM, we show that our approach leads to high-quality solutions for realistic instances (e.g., 100 aircraft and 100 requirements) within operationally feasible time frames. Compared with a baseline approach that emulates current practice at USTRANSCOM, our approach leads to reductions in total delay and aircraft time of 8%-12% in simulated data instances and 16%-40% in USTRANSCOM's planning instances.

关键词： pickup and delivery with time windows mixed-integer programming column generation local search construction heuristics

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Exact and heuristic approaches for maximizing flows in UAV-enabled wireless cellular networks with multi-hop backhauls

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RAIRO-OPERATIONS RESEARCH 2024年第1期58卷 185-205页

作者： Mhiri, Mariem Msakni, Mohamed Kais Hasna, Mazen O. Khattab, Tamer Haouari, Mohamed Qatar Univ Coll Engn Dept Mech & Ind Engn Doha Qatar Norwegian Univ Sci & Technol Dept Ind Econ & Technol Management Trondheim Norway Qatar Univ Coll Engn Elect Engn Dept Doha Qatar

This paper investigates the problem of data routing in backhaul networks using Unmanned Aerial Vehicles (UAVs) to relay data from Small Cells (SCs) to the core network. The objective is to maximize the total fulfilled demand of data to be routed, while ensuring technical requirements such as hop constraints and edge capacity. The problem is formulated using a compact mixed-integer programming model, which can solve small- and medium-sized topologies. In addition, a fast constructive heuristic based on a maximal tree is developed to solve large-scale topologies, resulting in a significant reduction in CPU time. The quality of the heuristic is evaluated by using column generation for solving the linear programming relaxation of an exponential formulation. The computational study shows the effectiveness and value of the proposed compact model and constructive heuristic for various topology sizes. Furthermore, experiments demonstrate that by keeping the network setup constant and updating the demand vector only, the computational time of the compact model can be drastically reduced for all topology sizes.

关键词： Bakchaul network unmanned Aerial Vehicles (UAVs) data routing mixed-integer programming heuristic column generation

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