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Retirement optimization through aircraft transfers and employment

JOURNAL OF AIR TRANSPORT MANAGEMENT 2019年第Aug.期79卷 101680-000页

作者： Newcamp, Jeffrey Verhagen, W. J. C. Santos, Bruno F. Curran, Richard Delft Univ Technol Fac Aerosp Kluyverweg 1 NL-2629 HS Delft Netherlands

Military aircraft retirements are an afterthought for many lifecycle planners. More active management of end-of-life fleets can yield increased confidence in fleet capability and retirement timelines. This work provides fleet managers with a tool to manage remaining aircraft flight hours to yield a desired fleet retirement pattern. It solves an equivalent flight hour minimization problem using a mixed-integer linear programming model for a military aircraft fleet having a network with basing and mission type constraints. The model minimizes differences in remaining equivalent flight hours for individual aircraft in future years, thereby allowing a fleet manager to alter the timeline for retirement of individual aircraft. A relocation cost is applied to discourage excessive, costly aircraft relocations. The United States Air Force A-10 Thunderbolt II aircraft is used as a case study while disruptions such as deployments are modeled to show the methodology's robustness. This work proves that a fleet of aircraft with dissimilar utilization histories and varying amounts of remaining useful lifetime can be actively managed to change the time at which individual aircraft are ready for retirement. The benefit to fleet managers is the ability to extract additional lifetime out of their aircraft prior to retirement.

关键词： Military aircraft Aircraft retirement mixed-integer linear programming Aircraft transfers

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BUSINESS ANALYSIS OF THE DRONE'S LAST MILE DELIVERY ENVIRONMENT

BUSINESS ANALYSIS OF THE DRONE'S LAST MILE DELIVERY ENVIRONM...

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作者： Caio Ferreira da Rosa Pantarotto POLITECNICO DI TORINO

学位级别：硕士

A good transportation from the last hub to the final customer receives the name of last mile delivery. Last mile is currently the least efficient component of the delivery chain, presenting high costs besides the small distances incurred. The major challenges of last mile delivery as it is today are related to an increase of labor costs and the wastes inherent to the current model of attended home delivery. In addition to that, customer requirements are getting more rigid as they expect not only precise and costless deliveries, but also fast ones. In that scenario, drone technology emerges as a potential problem solver. The introduction of drones performing the last mile delivery can improve its efficiency by increasing the asset usage, reducing the work force demanded and performing deliveries within a short lead time, among others. However, the introduction of this technology still faces some barriers, mainly related to its legalization, public acceptance and other issues related to the technology itself, such as its range and interaction with the final customer. In addition, the introduction of this technology does not only affect some operational components of the delivery chain, but also how the business entities within this environment perform their roles and interact with each other. Because of that, a study of the concept of business model and how it can be applied to the last mile delivery context was necessary. To develop suitable business models, a defined framework was used and a general classification of the drone usage potentialities on the specific context was made. As result, four business models involving different business entities, with the common factor that they all used the drone technology to perform the last mile delivery, were developed and analyzed, presenting not only how the actors interacted between each other but also the context in which each model could be applied. The four business models discusses were (i) centralized distribution c

关键词： last mile delivery drone technology business model mixed-integer linear programming

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Long-Term Co-optimized Generation and Transmission Expansion Planning with Renewables in Complicated Environments

Long-Term Co-optimized Generation and Transmission Expansion...

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2nd IEEE Conference on Energy Internet and Energy System Integration (EI2)

作者： Li Hui Liu Siwei Wu Lei Qi Qingru Zhang Mingli Shu Jun State Grid Econ Technol Res Inst Co Ltdr Beijing Peoples R China Clarkson Univ ECE Dept Potsdam NY USA Liaoning Elect Co Ltd Econ Tech Res Inst Shenyang Liaoning Peoples R China North China Elect Power Univ EE Dept Beijing Peoples R China

ISBN: (纸本)9781538685495

This paper presents a new approach for solving the multi-year co-optimized generation and transmission expansion planning problem with renewable energy resources in geographic information systems (GIS). The proposed optimization model is to determine when (which year), where (which cell), and what (which type) generators and transmission lines will be built for minimizing the sum of investment costs, operation costs (including energy and emission costs), and load shedding costs during the planning horizon. Prevailing constraints include power balance requirements, branch limits, power limits of generators, and construction limits of cells. A two-step approach to combine Dijkstra's algorithm and mixed-integer linear programming (MILP) is introduced for solving the large-scale optimization problem. The effectiveness of the proposed approach is validated by numerical case studies on a 9-bus system.

关键词： Long-term planning co-optimized generation and transmission expansion planning renewable generation planning optimal line routing geographic information systems Dijkstra's algorithm mixed-integer linear programming

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Strategic evacuation planning with pedestrian guidance and bus routing: a mixed integer programming model and heuristic solution

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JOURNAL OF ADVANCED TRANSPORTATION 2016年第7期50卷 1314-1335页

作者： Heydar, Mojtaba Yu, Jie Liu, Yue Petering, Matthew E. H. Univ Newcastle Callaghan NSW Australia Univ Wisconsin Dept Civil & Environm Engn Milwaukee WI 53211 USA Univ Wisconsin Dept Ind & Mfg Engn Milwaukee WI 53201 USA

This paper presents a mathematical model to plan emergencies in a densely populated urban zone where a certain numbers of pedestrians depend on transit for evacuation. The proposed model features an integrated operational framework, which simultaneously guides evacuees through urban streets and crosswalks (referred to as the pedestrian network) to designated pickup points (e.g., bus stops), and routes a fleet of buses at different depots to those pick-up points and transports evacuees to their destinations or safe places. In this level, the buses are routed through the so-called vehicular network. An integrated mixed integer linear program that can effectively take into account the interactions between the aforementioned two networks is formulated to find the maximal evacuation efficiency in two networks. Because the large instances of the proposed model are mathematically difficult to solve to optimality, a two-stage heuristic is developed to solve larger instances of the model. Results from hundreds of numerical examples analysis indicate that proposed heuristic works well in providing (near) optimal or feasibly good solutions for medium-scale to large-scale instances that may arise in real transit-based evacuation situations in a much shorter amount of computational time compared with cplex (can find optimal/feasible solutions for only five instances within 3hours of running). Copyright (c) 2016 John Wiley & Sons, Ltd.

关键词： evacuation mixed-integer linear programming vehicle routing public transit system transportation

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Modeling and Solving the Deadline Satisfaction Problem in Line-of-Balance Scheduling

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JOURNAL OF MANAGEMENT IN ENGINEERING 2018年第1期34卷 1-12页

作者： Zou, Xin Zhang, Qian Zhang, Lihui North China Elect Power Univ Dept Econ Management Baoding 071003 Hebei Peoples R China North China Elect Power Univ Sch Econ & Management Beijing 102206 Peoples R China

This study investigates the deadline satisfaction problem in line-of-balance (LOB) scheduling, where each activity can be done concurrently in several units by hiring additional crews, and all employed crews are allocated to implement an activity in sequential units smoothly with no interruption. Furthermore, the project must be completed within a given deadline. In previous studies, the objective was to minimize the total number of crews under the assumption that the cost of hiring a crew is the same for all activities. In fact, this cost usually differs among activities because of the differences in type of work, crew size, and technical level of workers. This paper presents a mixed-integer linear programming model with an extended objective of minimizing the crew employment cost of all activities. The model is equipped with an exact procedure to validate the feasibility of a prespecified deadline. A highway project was used to show the application of the proposed method, and then extensive computational experiments were conducted to investigate the performance of the proposed method by comparing the obtained results with those obtained by the existing methods. The results highlight the significance of integrating the time-cost trade-off analysis, and indicate that the proposed method can find optimal solutions for large-scale projects within a reasonable amount of time.

关键词： Repetitive projects Line-of-balance Time-cost trade-off Deadline constraint mixed-integer linear programming

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Dynamic convexification within nested Benders decomposition using Lagrangian relaxation: An application to the strategic bidding problem

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2017年第2期257卷 669-686页

作者： Steeger, Gregory Rebennack, Steffen Colorado Sch Mines Div Econ & Business Golden CO 80401 USA

Many decomposition algorithms like Benders decomposition and stochastic dual dynamic programming are limited to convex optimization problems. In this paper, we utilize a dynamic convexification method that makes use of Lagrangian relaxation to overcome this limitation and enables the modeling of non convex multi-stage problems using decomposition algorithms. Though the algorithm is confined by the duality gap of the problem being studied, the computed upper bounds (for maximization problems) are at least as good as those found via a linear programming relaxation approach. We apply the method to the strategic bidding problem for a hydroelectric producer, in which we ask: What is the revenue maximizing production schedule for a single price-maker hydroelectric producer in a deregulated, bid based market? Because the price-maker's future revenue function has a sawtooth shape, we model it using mixed-integer linear programming. To remedy the non-concavity issues associated with modeling the future revenue function as a mixed-integer linear program, we model the price-maker's bidding decision utilizing both Benders decomposition and Lagrangian relaxation. We demonstrate the utility of our algorithm through an illustrative example and through three case studies in which we model electricity markets in El Salvador, Honduras, and Nicaragua. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Lagrangian relaxation mixed-integer linear programming Benders decomposition Hydroelectric scheduling Strategic bidding problem Stochastic dual dynamic programming

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Evasion-Robust Classification on Binary Domains

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ACM TRANSACTIONS ON KNOWLEDGE DISCOVERY FROM DATA 2018年第4期12卷 50-50页

作者： Li, Bo Vorobeychik, Yevgeniy Univ Calif Berkeley Berkeley CA 94720 USA Vanderbilt Univ 221 Kirkland Hall Nashville TN 37235 USA 5221 Panama Ave Richmond CA 94804 USA 401 Bowling Ave 7 Nashville TN 37212 USA

The success of classification learning has led to numerous attempts to apply it in adversarial settings such as spam and malware detection. The core challenge in this class of applications is that adversaries are not static, but make a deliberate effort to evade the classifiers. We investigate both the problem of modeling the objectives of such adversaries, as well as the algorithmic problem of accounting for rational, objective-driven adversaries. We first present a general approach based on mixed-integer linear programming (MILP) with constraint generation. This approach is the first to compute an optimal solution to adversarial loss minimization for two general classes of adversarial evasion models in the context of binary feature spaces. To further improve scalability and significantly generalize the scope of the MILP-based method, we propose a principled iterative retraining framework, which can be used with arbitrary classifiers and essentially arbitrary attack models. We show that the retraining approach, when it converges, minimizes an upper bound on adversarial loss. Extensive experiments demonstrate that the mixed-integer programming approach significantly outperforms several state-of-the-art adversarial learning alternatives. Moreover, the retraining framework performs nearly as well, but scales significantly better. Finally, we show that our approach is robust to misspecifications of the adversarial model.

关键词： Design Algorithms Performance Adversarial classification classifier evasion robust learning mixed-integer linear programming adversarial examples

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Optimal design of energy conversion units for residential buildings considering German market conditions

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ENERGY 2017年 139卷 895-915页

作者： Schuetz, Thomas Schraven, Markus Hans Remy, Sebastian Granacher, Julia Kemetmueller, Dominik Fuchs, Marcus Mueller, Dirk Rhein Westfal TH Aachen EON Energy Res Ctr Inst Energy Efficient Bldg & Indoor Climate Mathieustr 10 Aachen Germany

Many countries have passed governmental action plans to support the installation of renewable energy sources. However, most studies dealing with the optimization of building energy systems neglect a precise modeling of such subsidies, although these subsidies are specifically designed to strongly influence system setups. Therefore, this paper extends a model for the optimization of energy systems by a more accurate consideration of storage units and enhance both models by accounting for major German pieces of legislation aimed at supporting renewable energies. Additionally, we consider typical German market characteristics, in particular the availability of multiple gas and electricity tariffs. We compare our model with the original formulation regarding a pure cost minimization and a forced reduction of CO2 emissions for three new buildings located in Germany. The results imply that the considered subsidies strongly support the installation of PV modules and CHP units. Without these subsidies, batteries and solar thermal collectors become more important. Additionally, the findings illustrate that the new storage model is slightly more accurate, but only marginally affects the total annual costs and required computing times. The conducted sensitivity analysis has shown that the obtained results are relatively robust to variations in energy tariff costs and demands. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Building energy systems German regulations mixed-integer linear programming Multiple energy tariffs

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Bulk ship fleet renewal and deployment under uncertainty: A multi-stage stochastic programming approach

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2017年 97卷 69-96页

作者： Arslan, Ayse N. Papageorgiou, Dimitri J. Univ Florida Dept Ind & Syst Engn Gainesville FL 32611 USA ExxonMobil Res & Engn Co Corp Strateg Res 1545 Route 22 East Annandale NJ 08801 USA

Faced with simultaneous demand and charter cost uncertainty, an industrial shipping company must determine a suitable fleet size, mix, and deployment strategy to satisfy demand. It acquires vessels by time chartering and voyage chartering. Time chartered vessels are acquired for different durations, a decision made before stochastic parameters are known. Voyage charters are procured for a single voyage after uncertain parameters are realized. We introduce the first multi-stage stochastic programming model for the bulk ship fleet renewal problem and solve it in a rolling horizon fashion. Computational results indicate that our approach outperforms traditional methods relying on expected value forecasts. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Chartering Fleet planning Fleet renewal Maritime transportation mixed-integer linear programming Multi-stage stochastic programming

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A multi-objective model for the green capacitated location-routing problem considering environmental impact

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COMPUTERS & INDUSTRIAL ENGINEERING 2017年 110卷 114-125页

作者： Toro, Eliana M. Franco, John F. Granada Echeverri, Mauricio Guimaraes, Frederico Gadelha Univ Tecnol Pereira Fac Ingn Ind Pereira Colombia Univ Tecnol Pereira Fac Ingn Programa Ingn Elect Pereira Colombia Univ Estadual Paulista UNESP Ilha Solteira Brazil Univ Fed Minas Gerais Dept Elect Engn Belo Horizonte MG Brazil

The Capacitated Location-Routing Problem (CLRP) is a strategic-level problem involving the selection of one or many depots from a set of candidate locations and the planning of delivery routes from the selected depots to a set of customers. During the last few years, many logistics and operations research problems have been extended to include greenhouse effect issues and costs related to the environmental impact of industrial and transportation activities. In this paper a new mathematical model for the calculation of greenhouse gas emissions is developed and a new model for the CLRP considering fuel consumption minimization is proposed. This model, named Green CLRP (G-CLRP), is represented by a mixed integer linear problem, which is characterized by incorporating a set of new constraints focused on maintaining the problem connectivity requirements. The model proposed is formulated as a bi-objective problem, considering the minimization of operational costs and the minimization of environmental effects. A sensitivity analysis in instances of different sizes is done to show that the proposed objective functions are indeed conflicting goals. The proposed mathematical model is solved with the classical epsilon constraint technique. The results clearly show that the proposed model is able to generate a set of tradeoff solutions leading to interesting conclusions about the operational costs and the environmental impact. This set of solutions is useful in the decision process because several planning alternatives can be considered at strategic level. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Capacitated location-routing problem Green vehicle routing problem Green logistics mixed-integer linear programming Vehicle routing problem

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