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IEEE International Conference on Systems, Man and Cybernetics

作者： Froehlich, Ralf Huesig, Matthias Hamburg Univ Technol Inst Automat Hamburg Germany

ISBN: (纸本)9781424427932

This paper presents two modeling approaches for hatching and scheduling jobs on parallel non-identical machines. For scheduling of jobs the due dates as a hard restriction and machine dependent processing times are considered. Between each of the jobs a setup may be necessary or not, depending on the predecessor. The setup of the machines is done by a single worker who needs to be scheduled as well, since only he can serve one machine at a lime. The objective is to maximize the overall workload of the machines meeting the constraint of the due dates. While the first approach uses mixed integer linear programming to calculate an optimal schedule, the second one uses a simulation, based on colored Petri nets. Both methods are tested and evaluated using illustrative simulation examples.

关键词： Family Setup Times Scheduling on Parallel Non-Identical Machines mixed integer linear programming Colored Petri Nets

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Supervised learning of intra-daily recourse strategies for generation management under uncertainties

Supervised learning of intra-daily recourse strategies for g...

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Bucharest PowerTech Conference

作者： Cornelusse, Bertrand Vignal, Gerald Defourny, Boris Wehenkel, Louis Univ Liege Dept Elect Engn & Comp Sci B-4000 Liege Belgium EDF R&D OSIRIS Dept F-92141 Clamart France

ISBN: (纸本)9781424422340

The aim of this work is to design intra-daily recourse strategies which may be used by operators to decide in real-time the modifications to bring to planned generation schedules of a set of units in order to respond to deviations from the forecasted operating scenario. Our aim is to design strategies that are interpretable by human operators, that comply with real-time constraints and that cover the major disturbances that may appear during the next day. To this end we propose a new framework using supervised learning to infer such recourse strategies from simulations of the system under a sample of conditions representing possible deviations from the forecast. This framework is validated on a realistic generation system of medium size.

关键词： mixed integer linear programming generation planning uncertainty management machine learning

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Integral planning of primary-secondary distribution systems using mixed integer linear programming

Integral planning of primary-secondary distribution systems ...

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IEEE General Meeting Power& Energy Society

作者： A.J. Urdaneta P.C. Paiva H. Khodr J. Dominguez-Navarro Yustam JM Universidad Simon Bolivar Venezuela Universidad de Zaragoza Spain

Summary form only given. Important research effort has been devoted to the topic of optimal planning of distribution systems. However, in general it has been mostly referred to the design of the primary network, with very modest considerations to the effect of the secondary network in the planning and future operation of the complete grid. Relatively little attention has been paid to the optimization of the secondary grid and to its effect on the optimality of the design of the complete electrical system, although the investment and operation costs of the secondary grid represent an important portion of the total costs. Appropriate design procedures have been proposed separately for both the primary and the secondary grid, however in general both planning problems have been presented and treated as different, almost isolated problems, setting aside with this approximation some important factors that couple both problems, such as the fact that they may share the right of way, use the same poles, etc., among other factors that strongly affect the calculation of the investment costs. The main purpose of this work is the development and initial testing of a model for the optimal planning of a distribution system that includes both the primary and the secondary grids, so that a single optimization problem is stated for the design of the integral primary-secondary distribution system that overcomes these simplifications. The mathematical model incorporates the variables that define both the primary as well as the secondary planning problems and consists of a mixed integer-linear programming problem that may be solved by means of any suitable algorithm. Results are presented of the application of the proposed integral design procedure using conventional mixed integer-linear programming techniques to a real case of a residential primary-secondary distribution system consisting of 75 electrical nodes.

关键词： mixed integer linear programming Design optimization Investments Cost function System testing Mathematical model Mathematical programming

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Optimizing a multiple objective surgical case sequencing problem

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2009年第2期119卷 354-366页

作者： Cardoen, Brecht Demeulemeester, Erik Belien, Jeroen Vlerick Leuven Gent Management Sch Operat & Technol Management Ctr B-9000 Ghent Belgium Katholieke Univ Leuven Fac Business & Econ Dept Decis Sci & Informat Management B-3000 Louvain Belgium Hogesch Univ Brussel Campus Econ Hogesch Centrum Modellering & Simulatie B-1000 Brussels Belgium

This paper studies a multi-objective combinatorial optimization problem in which the sequence of patients within the operating rooms of a freestanding ambulatory surgical center has to be determined. We show that the optimization problem is NP-hard and we develop some mixed integer linear programming solution approaches, which are either exact or heuristic in nature, to facilitate the decision process of the operating room scheduler. We gathered data from the UZ Leuven Campus Gasthuisberg (Belgium) to develop a structured but artificial test set and introduced the 224 instances to evaluate and compare the computational performance of the algorithmic approaches. Since the focus of this paper is directed towards the development and the Computational testing of the solution procedures, we only briefly document on some case study results with real data. (C) 2009 Elsevier B.V. All rights reserved.

关键词： Health care Operating room scheduling mixed integer linear programming

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Exact methods for single-item capacitated lot sizing problem with alternative machines and piece-wise linear production costs

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2009年第2期119卷 367-379页

作者： Akbalik, Ayse Penz, Bernard CEA LETI D2NT CNRS LTM F-38054 Grenoble France Inst Natl Polytech Grenoble G SCOP F-38031 Grenoble 1 France

In this paper, we study a special case of the capacitated lot sizing problem (CLSP). where alternative machines are used for the production of a single-item. The production cost on each machine is assumed to be piece-wise linear with discontinuous steps (step-wise costs). The over-produced finished products can be stored in an unlimited storage space to satisfy future demand. The aim is to achieve optimal production planning without backlogging. This problem can be seen as an integration of production and transportation activities in a multi-plant supply chain structure, where finished goods are sent directly from the plants to the distribution center using capacitated vehicles. For this problem, which we show to be NP-hard, we propose an exact pseudo-polynomial dynamic programming algorithm which makes it NP-hard in the ordinary sense. We also give three mixed integer linear programming (MILP) formulations that we have found in the literature for the simplest case of the CLSP. These formulations are adapted to the multi-machine case with a step-wise cost structure, to which some valid inequalities have been added to improve their efficiency. We then compare the computational time of the dynamic program to that of one MILP which we selected among MILP formulations based on its lower computational time and its lower and upper bound quality. (C) 2008 Elsevier B.V. All rights reserved.

关键词： Single-item capacitated lot sizing problem Alternative machines Step-wise production costs Dynamic programming mixed integer linear programming

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A Proposed Decision Support System for River Water Quality Management in India

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JOURNAL OF DECISION SYSTEMS 2009年第4期18卷 411-427页

作者： Babbar, Richa Arya, D. S. Joshi, Himanshu Jaypee Univ Informat Technol PO Dumehar Bani Solan Himachal Prades India Indian Inst Technol Dept Hydrol Roorkee Uttar Pradesh India

The growing concern for river water pollution in India is witnessing several initiatives from nodal agencies in terms of water pollution control. In a similar context, a need for a supportive platform is envisaged that takes care of management perspectives, feasible for Indian conditions. In this paper the most generic DSS has been proposed that caters to the requirement of regulatory authorities. In its prototype scale of application to improving water quality, at user defined water quality criterion, the system is capable of allocating waste loads to point sources, while liberating the user from writing the input files for simulation and management models. The system is designed for PC-Windows environment with minimal system requirements in terms of models viz., QUAL2E water quality model and LINDO optimizing package, interfaced using SQL Server 2000 Data base Management System. While the most expedient approach of treatment at source towards water quality management in India was addressed by the system, the example run of the DSS indicated a need of including other management options for comprehensive quality management.

关键词： Water Use mixed integer linear programming Water Quality Criteria Decision Support System

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A robust algorithm for Volt/Var control

A robust algorithm for Volt/Var control

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IEEE PES Power Systems Conference and Exposition, PSCE

作者： Andrija T. Saric Aleksandar M. Stankovic College of Engineering Northeastern University Boston USA

This paper proposes an algorithm for Volt/VAr control, where the control variables are both discrete (tap position of on-load tap-changing, OLTC transformers, switched-on shunt capacitor banks), and continuous (reactive power of generators). The optimization criterion considered is minimization of the system real power losses, subject to nodal real and reactive power balances and nodal voltage constraints. The corresponding non-linear optimization problem is solved iteratively on two levels - the Volt sub-problem is mixed integer programming (MIP) based master problem and the Var sub-problem is the mixed integer linear programming (MILP) based problem. The MILP problem is solved by Benders decomposition (BD). The proposed optimization method is formulated for the case of the uncertain input network model parameters to assess robustness aspects. The effectiveness of the proposed robust model for Volt/Var control is verified on the test example of a reduced New England/New-York interconnection with 68 nodes/86 branches/23 OLTC transformers/16 generators/9 switchable capacitors.

关键词： Robust control Reactive power Transformers Capacitors Reactive power control Power generation Constraint optimization linear programming mixed integer linear programming Optimization methods

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A MILP-based approach to path sensitization of embedded software 09

A MILP-based approach to path sensitization of embedded soft...

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Design, Automation and Test in Europe Conference and Exhibition

作者： Jose C. Costa Jose C. Monteiro TU Lisbon IST / INESC-ID Lisboa Portugal

ISBN: (纸本)9783981080155

We propose a new methodology based on mixed integer linear programming (MILP) for determining the input values that will exercise a specified execution path in a program. In order to seamlessly handle variable values, pointers and arrays, and variable aliasing, our method uses memory addresses for data references. This implies a dynamic methodology where all decisions are taken as the program executes. During execution, we gather constraints for the MILP problem, whose solution will directly yield the input values for the desired path. We present results that demonstrate the effectiveness of this approach. This methodology was implemented into a fully functional tool that is capable of handling medium sized real programs specified in the C language. Our work is motivated by the complexity of validating embedded systems and uses a similar approach to an existing HDL functional vector generation. The joint solution of the MILP problems will provide a hardware/software co-validation tool.

关键词： Embedded software Vehicle dynamics Embedded system Hardware design languages Software tools Software testing Application software Software systems mixed integer linear programming Bridges

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Finding the most cost efficient DMU with certain and uncertain input prices

Finding the most cost efficient DMU with certain and uncerta...

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International Conference on Computers & Industrial Engineering (CIE)

作者： Mehdi Toloo Maryam Shadab Mahta Yekkalam Department of Mathematics Islamic Azad University Central Tehran Branch Tehran Iran

Cost efficiency (CE) assesses the ability to produce current output at minimal cost. There are some models which are introduced to measure cost efficiency with certain and uncertain input prices. Normally, by using data envelopment analysis (DEA) models, more than one cost efficient decision making units (DMUs) are recognized. The main contribution of this paper consists of development of a model which was proposed by Amin and Toloo (2007) to some models for finding the most cost efficient DMU in various situations of input prices. These models find the most cost efficient DMU by solving only one mixed integer linear programming (MILP) in each case.

关键词： Costs Data envelopment analysis Production Mathematics Decision making mixed integer linear programming linear programming Shape Current measurement

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Modeling and Path Planning of the City-Climber Robot Part I: Dynamic Modeling

Modeling and Path Planning of the City-Climber Robot Part I:...

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2009 IEEE International Conference on Robotics and Biomimetics(2009 IEEE 机器人与仿生技术国际会议 ROBIO 2009)

作者： Ronggang Yue Jizhong Xiao Shaoping Wang Samleo L. Joseph Electrical Engineering Department the City CollegeCity University of New York (CUNY City College)C Electrical Engineering Department the CUNY City CollegeConvent Ave & 140th StreetNY 10031USA Department of Mechanical and Electronic Engineering School of Automation Science and Electrical Engi

ISBN: (纸本)9781424447749

This is the first part of a series papers on modeling and path planning of the City-Climber robot, a novel wall-climbing robot which can climb walls, move on ceilings and transit between floor and walls. In order to provide the City-Climber with 3D path planning capability to carry out tasks such as cleaning, painting, and building inspection in 3D environments, we use mixed integer linear programming (MILP) as a tool to incorporate logical constraints such as obstacle avoidance and waypoint selection with basic dynamic constraints. In this paper, we derive the dynamic model of the City-Climber robot in different cases, I.e., on the floor, walls, and ceiling, respectively. Non-dimensional variables are introduced to simplify the models. Simulation results verified the correctness of the model since the trajectories match the expected practical motion of the robot. MILP-based 3D path planning will be presented in part 2 which account for the dynamic constraints and obstacle avoidance.

关键词： Path planning Obstacle avoidance Modeling Ceilings building inspection Robot wall ceilings Decks Collision avoidance mixed integer linear programming accuracy class CLIMBING WALL

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