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Smooth Flight Trajectory Planning in the Presence of No-Fly Zones and Obstacles

JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2010年第2期33卷 454-462页

作者： Mattei, Massimiliano Blasi, Luciano Univ Naples 2 Dept Aerosp & Mech Engn I-81031 Aversa Italy

This paper describes a novel procedure to generate continuously differentiable optimal flight trajectories in the presence of arbitrarily shaped no-fly zones and obstacles having a fixed position in time. The operational flight scenario is first discretized with 9 finite dimensional grid of positions-directions pairs. A weighted and oriented graph is then defined for which the nodes are the earlier mentioned grid points and for which the arcs correspond to minimum length trajectories compliant with obstacle avoidance constraints. Arcs are obtained via solving convex quadratic programming optimization problems that can also account for geometrical constraints such as trajectory curvature limitations. The problem of finding an optimal trajectory be tween two nodes of the so-called core paths graph is then solved via a minimum cost path search algorithm. In a real-time application perspective, the generation of the core paths graph is computationally cumbersome. Moreover, the aircraft position and direction rarely coincide with one of the graph nodes. However, if the graph is built offline and stored, the definition of an optimal trajectory connecting any points of the space domain requires a reduced computational effort. The particular case of piecewise polynomial trajectories minimizing a flight path's length, compliant with constraints on curvature and flight-path angles, is fully developed. Two- and three-dimensional examples are discussed to show the applicability as well as the effectiveness of the technique.

关键词： Flight Trajectory Obstacle Avoidance Quadratic programming Flight Path Angle Search Algorithm Pontryagin's Maximum Principle UAV mixed integer linear programming MATLAB Flight Altitude

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Optimization of On-site Renewable Energy Generation for Industrial Sites

Optimization of On-site Renewable Energy Generation for Indu...

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IEEE/PES Power Systems Conference and Exposition

作者： Suriya Ruangpattana Diego Klabjan Jorge Arinez Stephan Biller Department of Industrial Engineering and Management Sciences Northwestern University Manufacturing Systems Research Laboratory General Motors R&D Center

ISBN: (纸本)9781612847894

We consider the energy sourcing decision problem faced by industrial power consumers who must determine their long-term electricity procurement plan and need to evaluate various options to meet load requirements for their facilities including those which may involve on-site renewable generation. Other than sourcing from on-site renewable generation such as solar photovoltaic or wind, power can be purchased from spot markets or through a power purchase agreement, i.e. energy supply contract. We develop a mixed-integer linear model to make decisions that include investments in renewable generation, power purchases from spot markets, and amount sourced from supply contracts. Taking into account renewable energy certificates, the model's objective is to maximize revenue from trading renewable certificates minus the expected total costs of investing and operating on-site renewable generation, and purchasing from electricity markets. Real load data from manufacturing plants are used to illustrate a numerical case study for our model.

关键词： mixed integer linear programming Renewable energy Sustainability On-site generation Industrial consumers

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Transmission Switching in Expansion Planning

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IEEE TRANSACTIONS ON POWER SYSTEMS 2010年第3期25卷 1722-1733页

作者： Khodaei, Amin Shahidehpour, Mohammad Kamalinia, Saeed IIT Dept Elect & Comp Engn Chicago IL 60616 USA

Transmission switching (TS) is introduced to add flexibility to the transmission and generation capacity expansion planning problem. TS could improve the performance of the capacity expansion planning model and reduce the total planning cost. The capacity expansion planning problem is decomposed into a master problem and two subproblems. The master problem utilizes the candidate set for additional generating unit and transmission capacity investments to find the optimal plan throughout the planning horizon. The subproblems use the optimal plan, apply transmission switching to relieve any transmission flow violations, and calculate the optimal dispatch of generating units. The transmission network contingencies are also considered in the subproblems. The case studies exhibit the effectiveness of the proposed expansion planning approach.

关键词： Benders decomposition mixed integer linear programming transmission and generation capacity expansion planning transmission switching

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Oil production optimization-A piecewise linear model, solved with two decomposition strategies

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COMPUTERS & CHEMICAL ENGINEERING 2010年第11期34卷 1803-1812页

作者： Gunnerud, Vidar Foss, Bjarne NTNU Norwegian Inst Technol Dept Engn Cybernet N-7491 Trondheim Norway

This paper presents a new method for real-time optimization of process systems with a decentralized structure where the idea is to improve computational efficiency and transparency of a solution. The contribution lies in the application and assessment of the Lagrange relaxation and the Dantzig-Wolfe methods, which allows us to efficiently decompose a real-time optimization problem. Furthermore, all nonlinearities are modeled by piecewise linear models, resulting in a mixed integer linear program, with the added benefit that error bounds on the solution can be computed. The merits of the method are studied by applying it to a semi-realistic model of the Troll west oil rim, a petroleum asset with severe production optimization challenges due to rate dependent gas-coning wells. This study indicates that both the Lagrange relaxation and in particular the Dantzig-Wolfe approach offers an interesting option for complex production systems. Moreover, the method compares favorably with the non-decomposed method. (C) 2009 Elsevier Ltd. All rights reserved.

关键词： Oil production planning Piecewise linearization mixed integer linear programming Lagrangian decomposition Dantzig-Wolfe decomposition

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Topology and routing optimization for congestion minimization in optical wireless networks

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OPTICAL SWITCHING AND NETWORKING 2010年第3期7卷 95-107页

作者： Ouveysi, Iradj Shu, Feng Chen, Wei Shen, Gangxiang Zukerman, Moshe City Univ Hong Kong Dept Elect Engn Kowloon Hong Kong Peoples R China Univ Melbourne EEE Dept Melbourne Vic 3010 Australia Eindhoven Univ Technol NL-5600 MB Eindhoven Netherlands

Optical wireless networks have appealing features such as very high broadband data rates and cost effectiveness. They represent a potential alternative to the last mile (first mile) wireless access problem. However, they are also highly vulnerable to external disturbances such as adverse weather and building sway. In this paper, we develop robust and efficient methods for outdoor optical wireless networks by jointly considering topology optimization and survivability strategies. We propose linearized congestion minimization schemes with working and protection paths (LCM-WP), in which a mixed integer linear program is formulated to choose the optimal working and protection paths for every OD pair such that the network congestion is minimized. In particular, the objective is to minimize the maximum amount of traffic on the links. To solve realistically sized problems, we consider a restricted version of the LCM-WP, in which only limited sets of candidate working and protection paths are considered. A simple algorithm is developed to find candidate working and protection paths for each origin-destination (OD) pair. Implementation of our LCM-WP schemes demonstrates the efficiency of our approach in terms of the number of constraints and solution time. It also shows that our approach is applicable to realistically sized networks. (C) 2010 Elsevier B.V. All rights reserved.

关键词： Optical wireless mixed integer linear programming Topology control Routing Survivable networks

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A flexible MILP model for multiple-shift workforce planning under annualized hours

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2010年第3期200卷 860-873页

作者： Hertz, Alain Lahrichi, Nadia Widmer, Marino Ecole Polytech Dept Math & Genie Ind Montreal PQ H3C 3A7 Canada Ecole Polytech Dept Math & Genie Ind GERAD 3000 Montreal PQ H3T 2A7 Canada Univ Fribourg Dept Informat CH-1700 Fribourg Switzerland

Flexibility in workforce planning is one of the best ways to respond to fluctuations of the demand. This paper proposes a flexible mixed integer linear programming (MILP) model to solve a multiple-shift workforce planning problem under annualized working hours. The model takes into account laws and collective agreements that impose constraints on overtime and holidays. We consider possible gradual hiring of full time and partial time workers. Several objectives are pursued such as balancing the workload of the employees or minimizing the workforce size. Computational experiments on a real life problem demonstrate the effectiveness of the model. (C) 2009 Elsevier B.V. All rights reserved.

关键词： OR in manpower planning mixed integer linear programming Decision support systems

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Routing, scheduling and channel assignment in Wireless Mesh Networks: Optimization models and algorithms

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AD HOC NETWORKS 2010年第6期8卷 545-563页

作者： Capone, A. Carello, G. Filippini, I. Gualandi, S. Malucelli, F. Politecn Milan Dipartimento Elettron & Informaz I-20133 Milan Italy

Wireless Mesh Networks (WMNs) can partially replace the wired backbone of traditional wireless access networks and, similarly, they require to carefully plan radio resource assignment in order to provide the same quality guarantees to traffic flows. In this paper we study the radio resource assignment optimization problem in Wireless Mesh Networks assuming a time division multiple access (TDMA) scheme, a dynamic power control able to vary emitted power slot-by-slot, and a rate adaptation mechanism that sets transmission rates according to the signal-to-interference-and-noise ratio (SINR). The proposed optimization framework includes routing, scheduling and channel assignment. Quality requirements of traffic demands are expressed in terms of minimum bandwidth and modeled with constraints defining the number of information units (packets) that must be delivered per frame. We consider an alternative problem formulation where decision variables represent compatible sets of links active in the same slot and channel, called configurations. We propose a two phases solution approach where a set of configurations is first selected to meet traffic requirements along the best available paths, and then configurations are assigned to channels according to device characteristics and constraints. The optimization goal is to minimize the number of used slots, which is directly related to the global resource allocation efficiency. We provide a lower bound of the optimal solution solving the continuous relaxation of problem formulation. Moreover, we propose a heuristic approach to determine practical integer solutions (upper bound). Since configuration variables are exponentially many, our solution approaches are based on the column generation technique. In order to assess the effectiveness of the proposed algorithms we show the numerical results obtained on a set of realistic-size randomly generated instances. (C) 2009 Elsevier B.V. All rights reserved.

关键词： Optimization Routing Scheduling Channel assignment Radio resource assignment Power control Rate control mixed integer linear programming Column generation

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Formation Optimal Maneuvers Under Inertial Attitude Dynamics

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JOURNAL OF SPACECRAFT AND ROCKETS 2010年第2期47卷 295-307页

作者： Zanon, Darren J. Campbell, Mark E. Cornell Univ Ithaca NY 14853 USA

A technique for generating optimal maneuvers for realistic thruster placements on rotating spacecraft in formations is developed. The approach uses linear programming optimization to initialize a Hamilton-Jacobi-Bellman optimization. The linear programming solution develops a fast and accurate solution for the discretized problem;the subsequent Hamilton-Jacobi-Bellman optimization minimizes the true continuous cost (such as formation fuel use). A Schur decomposition and singular value decomposition are employed to enhance the speed and robustness of the Hamilton-Jacobi-Bellman optimization. The resultant technique scales well with the number of thruster switches and is generally applicable to spacecraft for which inertial frame dynamics are known over one or more orbits. The approach is evaluated in simulation on a two-spacecraft cooperative inspection mission. Analysis is performed on a variety of potential strategies for choosing reference centers, stabilizing relative orbits, and decreasing orbit separation distance, showing excellent performance in both solution accuracy and fuel use while reducing computation time compared with traditional approaches.

关键词： Attitude Control System linear programming Singular Value Decomposition Spacecraft Formation Perigee Satellite Formation Highly Eccentric Orbit mixed integer linear programming Thrust Vectoring Pulsed Plasma Thruster

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Trajectory Planning for Multiple Autonomous Systems Using mixed integer linear programming

Trajectory Planning for Multiple Autonomous Systems Using Mi...

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Southeastern Symposium on System Theory

作者： T.A. Ademoye A. Davari Graduate Research Assistant WVU Institute of Technology USA Department of Electrical & Computer Engineering WVU Institute of Technology USA

This paper addresses the problem of finding optimal trajectories for multiple autonomous systems. mixed integer linear programming (MILP) is described for designing time and energy- or fuel-optimal maneuvers that account for the presence of other vehicles. The paper shows how integer constraints can be added to linear programming to account for obstacle avoidance and collision avoidance among the group of autonomous systems

关键词： Trajectory mixed integer linear programming Unmanned aerial vehicles Vehicle dynamics Remotely operated vehicles Collision avoidance Equations Mobile robots Kinematics Automotive engineering

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Production scheduling of a multi-grade PET resin plant

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COMPUTERS & CHEMICAL ENGINEERING 2010年第3期34卷 387-400页

作者： Liberopoulos, George Kozanidis, George Hatzikonstantinou, Olympia Univ Thessaly Dept Mech Engn Volos 38334 Volos Greece

We present a discrete-time, mixed integer linear programming (MILP) model for the production scheduling of a continuous-process multi-grade PET resin plant. The objective is to minimize the cost associated with grade changeovers in order to avoid undesirable variations in base resin properties and process conditions that occur during such changes. The constraints of the model include requirements related to sequence-dependent changeovers, sequential processing with production and space capacity, mixed and flexible finite intermediate storage, and intermediate demand due-dates. We present a case study that illustrates the application of the model on a real problem scenario and provides insight into its behavior. The numerical experience demonstrates that the computational requirements of the model are quite reasonable for problem sizes that typically arise in practical applications. (C) 2009 Elsevier Ltd. All rights reserved.

关键词： Polymer industry PET resin Continuous multi-grade process Production scheduling mixed integer linear programming

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