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Cyclic jobshop hoist scheduling with multi-capacity reentrant tanks and time-window constraints

COMPUTERS & INDUSTRIAL ENGINEERING 2018年 120卷 382-391页

作者： Feng, Jianguang Chu, Chengbin Che, Ada Northwestern Polytech Univ Sch Management Xian 710072 Shaanxi Peoples R China Univ Paris Est ESIEE Paris 2 Blvd Blaise PascalCite Descartes BP 99 F-93162 Noisy Le Grand France Univ Paris Saciay Cent Supelec Lab Genie Ind 3 Rue Joliot Curie F-91190 Gif Sur Yvette France

This paper studies the cyclic jobshop hoist scheduling with multi-capacity reentrant tanks and time-window constraints. Parts of different types are processed in a series of tanks with bounded processing times. Multi capacity tanks are used to handle stages with long processing times. Tanks can be reentrant so that a part visits them more than once. A hoist is responsible for the transportation of parts between tanks. We consider the cyclic scheduling where multiple parts enter and leave the production line during a cycle. The difficulty to deal with the problem lies in how to effectively handle the constraints related to multi-capacity reentrant tanks and their relations with time windows. To this end, a mixed-integer linear programming model is developed by addressing the time-window constraints and tank capacity constraints in a novel way. Computational experiments are conducted to demonstrate the effectiveness of the proposed model.

关键词： Cyclic jobshop scheduling Hoist scheduling Multi-capacity reentrant tanks mixed-integer linear programming

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Scheduling and Pricing of Energy Generation and Storage in Power Systems

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IEEE TRANSACTIONS ON POWER SYSTEMS 2018年第4期33卷 4308-4322页

作者： Khatami, Roohallah Parvania, Masood Khargonekar, Pramod P. Univ Utah Dept Elect & Comp Engn Salt Lake City UT 84108 USA Univ Calif Irvine Dept Elect Engn & Comp Sci Irvine CA 92697 USA

This paper proposes a fundamental model for continuous-time scheduling and marginal pricing of energy generation and storage in day-ahead power systems operation. The paper begins with formulating the economic operation problem of power systems with generating units and energy storage (ES) devices as a continuous-time optimal control problem, where the Lagrange multiplier trajectory associated with the continuous-time power balance constraint is proven to be the marginal price of energy generation and storage. The marginal price is calculated in closed-form, which reveals that in addition to the incremental cost rates of generating units, the marginal price embeds the financial ES charging offers and discharging bids that are defined as incremental charging utility and incremental discharging cost rates. This paper shows that the adjoint function associated with the ES state equation establishes a temporal dependence between the marginal prices during the ES charge and discharge states. A function space-based method is developed to solve the proposed model, which converts the continuous-time problem into a mixed-integer linear programming problem with finite dimensional decision space. The features of the proposed scheduling and pricing models are demonstrated using numerical studies conducted on the IEEE Reliability Test System.

关键词： Continuous-time optimal control energy storage marginal price mixed-integer linear programming

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A quantitative approach for optimal alarm identification

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JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES 2018年 55卷 213-222页

作者： Venkidasalapathy, Joshiba Ariamuthu Mannan, M. Sam Kravaris, Costas Texas A&M Univ Artie McFerrin Dept Chem Engn College Stn TX 77843 USA

Alarm identification refers to selecting a set of measurements to be configured to the alarm system. Contrary to prior literature which uses qualitative cause-effect based techniques, the present work incorporates quantitative aspects such as the time taken by measurements for deviation, to make alarm identification more reliable. The present work proposes a systematic approach to alarm identification through an optimization formulation, as a mixed-integer linear programming (MILP) problem, for the time. The proposed formulation maximizes the time available for operators to respond to faults while keeping the number of alarms triggered at a minimum. Subsequently, a linear multi-objective optimization formulation reduces the number of optimal solutions taking into account additional criteria, such as order of priority of potential faults. The proposed formulation is applied to the Tennessee Eastman (TE) Challenge problem. A closed-loop simulator was used for fault propagation, to obtain quantitative information required to apply the formulation, and CPLEX solver in GAMS was used to solve this case study problem.

关键词： Alarm identification mixed-integer linear programming Process safety Alarm management Abnormal event management

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Coordination of Wind Farm and Pumped-Storage Hydro for a Self-Healing Power Grid

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IEEE TRANSACTIONS ON SUSTAINABLE ENERGY 2018年第4期9卷 1910-1920页

作者： Golshani, Amir Sun, Wei Zhou, Qun Zheng, Qipeng P. Wang, Jianhui Qiu, Feng Univ Cent Florida Dept Elect & Comp Engn Orlando FL 32186 USA Univ Cent Florida Dept Ind Engn & Management Syst Orlando FL 32186 USA Southern Methodist Univ Dept Elect Engn Dallas TX 75205 USA Argonne Natl Lab Energy Syst Div Lemont IL 60439 USA

The increasing penetration of wind energy poses great challenges to the operation of power systems in normal and emergency states. However, energy storage technologies can help accommodate wind power uncertainty and variability due to their flexible characteristics. This paper focuses on the restoration phase, and provides a novel coordination strategy of wind and pumped-storage hydro (PSH) units for a faster and reliable self-healing process. The wind-PSH assisted power system restoration is formulated as a two-stage adaptive robust optimization problem. The first-stage problem determines the start-up sequence of generators and the energization times of transmission paths;and the second-stage problem decides load pickup sequences, wind power dispatch levels, and PSH units' operating modes. The column-and-constraint generation decomposition algorithm is applied to solve the two-stage adaptive robust optimization problem, which has a mixed-integer optimization in the inner-level problem. The developed coordination strategy is tested on the modified IEEE 39-bus system. Numerical results demonstrate that the coordinated wind and PSH units can increase the total energy served, enhance wind power dispatchability, and reduce wind power curtailment.

关键词： Adaptive robust optimization column-and-constraint generation mixed-integer linear programming pumped-storage hydro self-healing wind uncertainty

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Optimizing make-to-stock policies through a robust lot-sizing model

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2018年 200卷 302-310页

作者： Agra, Agostinho Poss, Michael Santos, Micael Univ Aveiro Dept Math CIDMA P-3810193 Aveiro Portugal Univ Montpellier UMR CNRS LIRMM 5506 161 Rue Ada F-34392 Montpellier 5 France Univ Aveiro Dept Math P-3810193 Aveiro Portugal

In this paper we consider a practical lot-sizing problem faced by an industrial company. The company plans the production for a set of products following a Make-To-Order policy. When the productive capacity is not fully used, the remaining capacity is devoted to the production of those products whose orders are typically quite below the established minimum production level. For these products the company follows a Make-To-Stock (MTS) policy since part of the production is to fulfill future estimated orders. This yields a particular lot-sizing problem aiming to decide which products should be produced and the corresponding batch sizes. These lot-sizing problems typically face uncertain demands, which we address here through the lens of robust optimization. First we provide a mixed integer formulation assuming the future demands are deterministic and we tighten the model with valid inequalities. Then, in order to account for uncertainty of the demands, we propose a robust approach where demands are assumed to belong to given intervals and the number of deviations to the nominal estimated value is limited. As the number of products can be large and some instances may not be solved to optimality, we propose two heuristics. Computational tests are conducted on a set of instances generated from real data provided by our industrial partner. The heuristics proposed are fast and provide good quality solutions for the tested instances. Moreover, since they are based on the mathematical model and use simple strategies to reduce the instances size, these heuristics could be extended to solve other multi-item lot-sizing problems where demands are uncertain.

关键词： Lot-sizing Make-To-Stock Robust optimization mixed-integer linear programming

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Optimised Heat Pump Management for Increasing Photovoltaic Penetration into the Electricity Grid

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ENERGIES 2019年第8期12卷

作者： Sanchez, Cristian Bloch, Lionel Holweger, Jordan Ballif, Christophe Wyrsch, Nicolas EPFL Inst Microengn IMT Photovolta & Thin Film Elect Lab PV LAB Rue Maladiere 71b CH-2000 Neuchatel Switzerland CSEM PV Ctr Rue Jaquet Droz 1 CH-2000 Neuchatel Switzerland

Advanced control of heat pumps with thermal storage and photovoltaics has recently been promoted as a promising solution to help decarbonise the residential sector. Heat pumps and thermal storage offer a valuable flexibilisation mean to integrate stochastic renewable energy sources into the electricity grid. Heat pump energy conversion is nonlinear, leading to a challenging nonlinear optimisation problem. However, issues like global optimum uncertainty and the time-consuming methods of current nonlinear programming solvers draw researchers to linearise heat pump models that are then implemented in faster and globally convergent linear programming solvers. Nevertheless, these linearisations generate some inaccuracies, especially in the calculation of the heat pump's coefficient of performance (COP). In order to solve all of these issues, this paper presents a heuristic control algorithm (HCA) to provide a fast, accurate and near -optimal solution to the original nonlinear optimisation problem for a single-family house with a photovoltaic system, using real consumption data from a typical Swiss house. Results highlight that the HCA solves this optimisation problem up to 1000 times faster, yielding an operation that is up to 49% cheaper and self -consumption rates that are 5% greater than other nonlinear solvers. Comparing the performance of the HCA and the linear solver intlinprog, it is shown that the HCA provides more accurate heat pump control with an increase of up to 9% in system Operating Expense OPEX and a decrease of 8% in self -consumption values.

关键词： photovoltaics demand-side management air-to-water modulated heat pump thermal energy storage nonlinear programming mixed-integer linear programming heuristics optimal control problem

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A MILP methodology to optimize sizing of PV - Wind renewable energy systems

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ENERGY 2018年 165卷 385-398页

作者： Lamedica, Regina Santini, Ezio Ruvio, Alessandro Palagi, Laura Rossetta, Irene SAPIENZA Univ Rome Dept Astronaut Elect & Energy Engn Rome Italy SAPIENZA Univ Rome Dept Comp Control & Management Engn Rome Italy Rete Ferroviaria Italiana SpA Rome Italy

This paper proposes a methodology that is based on mixed-integer linear programming (MILP) to calculate the optimal sizing of a hybrid wind-photovoltaic power plant in an industrial area. The proposed methodology considers the: i) load requirements;ii) physical and geometric constraints for the renewable plants installation;iii) operating and maintenance costs of both wind and PV power plants;and the iv) electric energy absorbed by the public network. The power demand variation associated with the production cycles is considered by using a stochastic simulation tool. To consider both the load and seasonality variability, and to adapt the methodology to the actual operational use of the power plant, the optimization is performed separately for each month of the year. Then, an integrated economic analysis is discussed. The methodology is adopted to analyze an industrial plant in the Rome area used as a train depot and for maintenance purposes. The results, which combine the needs of the plant activity with the availability of renewable energy, enabled the determination of optimal solutions and the relevant savings achievable. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Industrial power plant mixed-integer linear programming Optimization Renewable energy systems

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Intruder alert! Optimization models for solving the mobile robot graph-clear problem

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CONSTRAINTS 2018年第3期23卷 335-354页

作者： Morin, Michael Castro, Margarita P. Booth, Kyle E. C. Tran, Tony T. Liu, Chang Beck, J. Christopher Univ Laval Dept Operat & Decis Support Syst Quebec City PQ Canada Univ Toronto Dept Mech & Ind Engn Toronto ON Canada

We develop optimization approaches to the graph-clear problem, a pursuit-evasion problem where mobile robots must clear a facility of intruders. The objective is to minimize the number of robots required. We contribute new formal results on progressive and contiguous assumptions and their impact on algorithm completeness. We present mixed-integer linear programming and constraint programming models, as well as new heuristic variants for the problem, comparing them to previously proposed heuristics. Our empirical work indicates that our heuristic variants improve on those from the literature, that constraint programming finds better solutions than the heuristics in run-times reasonable for the application, and that mixed-integer linear programming is superior for proving optimality. Given their performance and the appeal of the model-and-solve framework, we conclude that the proposed optimization methods are currently the most suitable for the graph-clear problem.

关键词： Pursuit-evasion Graph-clear problem Constraint programming mixed-integer linear programming Optimization Mobile robotics

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An accelerated extended cutting plane approach with piecewise linear approximations for signomial geometric programming

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JOURNAL OF GLOBAL OPTIMIZATION 2018年第3期70卷 579-599页

作者： Zhan, Yiduo Zheng, Qipeng P. Tseng, Chung-Li Pasiliao, Eduardo L. Univ Cent Florida Dept Ind Engn & Management Syst Orlando FL 32816 USA UNSW UNSW Business Sch Sydney NSW 2052 Australia Air Force Res Lab 101 West Eglin Blvd Eglin AFB FL 32542 USA

This paper presents a global optimization approach for solving signomial geometric programming (SGP) problems. We employ an accelerated extended cutting plane (ECP) approach integrated with piecewise linear (PWL) approximations to solve the global optimization of SGP problems. In this approach, we separate the feasible regions determined by the constraints into convex and nonconvex ones in the logarithmic domain. In the nonconvex feasible regions, the corresponding constraint functions are converted into mixed integer linear constraints using PWL approximations, while the other constraints with convex feasible regions are handled by the ECP method. We also use pre-processed initial cuts and batched cuts to accelerate the proposed algorithm. Numerical results show that the proposed approach can solve the global optimization of SGP problems efficiently and effectively.

关键词： Signomial geometric programming Piecewise linear approximation mixed-integer linear programming Accelerated extended cutting plane

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Scheduling pumpoff operations in onshore oilfields with electric-power constraints and variable cycle time

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COMPUTERS & OPERATIONS RESEARCH 2018年 91卷 247-257页

作者： Camponogara, Eduardo Guardini, Luiz Alberto de Assis, Leonardo Salsano Univ Fed Santa Catarina Dept Automat & Syst Engn CxP 476 BR-88040900 Florianopolis SC Brazil

An oilfield is a complex enterprise that requires hefty capital investments and substantial energy resources for its operation. In mature onshore oilfields, sucker-rod pumps are deployed to enable oil production when the reservoir pressure is low. Albeit robust, such an artificial-lifting technique relies on electric-power supply to keep the rotary machines running. Managing a limited source of electric power while, at the same time, maximizing oil production and reducing equipment wear is of paramount importance, particularly so with today's low prices for the oil barrel. To this end, this paper proposes mixed-integer linear formulations for scheduling the operations of sucker-rod pumps, which work according to a control policy that alternates between on and off pumping periods, the so called pumpoff policy. Formulations for scheduling the initial operations and reconfiguring the control policies are developed, implemented, and tested with computational experiments. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Sucker-rod pumping Scheduling Electric-power resource Onshore oilfield mixed-integer linear programming

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