The point coverage, sink location, and data routing problems are considered in an integrated way and two new mixed-integerprogramming formulations are proposed. As these models are difficult to solve, a nested soluti...
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ISBN:
(纸本)9783642121388
The point coverage, sink location, and data routing problems are considered in an integrated way and two new mixed-integerprogramming formulations are proposed. As these models are difficult to solve, a nested solution procedure is proposed. The best sensor locations are sought by tabu search in the upper level. For the fixed sensor locations, the remaining problem of determining sink locations and data routes are solved efficiently in the lower level. According to the experimental results performed on a number of test instances, the performance of the nested solution approach is quite satisfactory, and the proposed heuristic method brings considerable improvements over a two-stage solution approach.
A personalized driver assisting system that makes use of the driver's behavior model is developed. As a model of driving behavior, the Probability-weighted ARX (PrARX) model, a type of hybrid dynamical system mode...
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ISBN:
(纸本)9781424453634
A personalized driver assisting system that makes use of the driver's behavior model is developed. As a model of driving behavior, the Probability-weighted ARX (PrARX) model, a type of hybrid dynamical system models, is introduced. A PrARX model that describes the driver's vehicle-following skill on expressways is identified using a simple gradient descent algorithm from actual driving data collected on a driving simulator. The obtained PrARX model describes the driver's logical decision making as well as continuous maneuver in a uniform manner. Finally, the optimization of the braking assist is formulated as a mixed-integer linear programming (MILP) problem using the identified driver model, and computed online in the model predictive control framework.
Hybrid electric vehicles are regarded as a possible solution for the reduction of pollutant emissions and for improving the fuel economy. Besides the conventional cooling circuit for the engine, hybrid vehicles need c...
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Hybrid electric vehicles are regarded as a possible solution for the reduction of pollutant emissions and for improving the fuel economy. Besides the conventional cooling circuit for the engine, hybrid vehicles need cooling for the electrical drives and for the energy storage systems as well. The development of appropriate cooling systems has the consequence that the number of auxiliary components involved, the weight and above all the energy consumption is increased. Therefore in order to minimize the energy consumption an optimal strategy for the operation of the cooling aggregates is required. In this paper an approach for finding the optimal control strategy of the electric auxiliaries over an apriori defined driving cycle is introduced. An energy minimization problem with constraints given by the maximum allowed temperature of the components is stated. This problem is based on a nonlinear mathematical model of the cooling system. It is shown how the nonlinear continuous time model can be equivalently replaced by a suitable linear discrete time model where some of the variables are confined to take integer values. This allows us to cast the optimization problem as a mixedintegerlinear program. The proposed approach is demonstrated by an example. For this purpose a cooling system is considered where an electrically driven water pump and an electric cooling fan are involved. As a result the optimal interaction of the water pump and the fan is computed such that the energy consumption of these components is minimized subject to given temperature constraints.
Planning of distributed energy systems is a challenging task,involving a lot of technical,economic,environmental and political factors. In this study,an optimization model based decision support system and the relevan...
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ISBN:
(纸本)9781457700668
Planning of distributed energy systems is a challenging task,involving a lot of technical,economic,environmental and political factors. In this study,an optimization model based decision support system and the relevant software package have been developed to provide comprehensive analysis of economic,energetic and environmental issues within a distributed energy system framework. The optimization problem is formulated as a mixedintegerlinearprogramming (MILP) model where the objective is to minimize the overall cost of the distributed energy system including both investing and running costs. By using a user friendly interface,the system can be used without the necessary to have special expertise and knowledge on energy system planning and decision analysis. In addition,besides the distributed energy system planning,it can be also used for examining and visualizing impacts of local energy and environmental policies,regional development policies,and climate change within a local framework.
Petroleum allocation is an important link for the integration of petroleum supply chain at PETROBRAS as it is responsible for refining the strategic supply planning information to be used at the operation levels. In t...
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Petroleum allocation is an important link for the integration of petroleum supply chain at PETROBRAS as it is responsible for refining the strategic supply planning information to be used at the operation levels. In this work we describe how mathematical programming is being used to solve the petroleum allocation problem and we show the effectiveness of a local search method by optimization to solve real industrial problems. We propose a mixed-integer linear programming formulation of the problem that relies on a time/space discretization network. As the model cannot be solved for the industrial size instances of the problem, and not even a feasible solution can be found after 15 days of computation, we implement an algorithm based on a heuristic to find a feasible solution and on a local search procedure based on optimization to improve it. Using this algorithm. Solutions are found for all the case studies within 10% of optimality in less than 5 h. (C) 2009 Elsevier Ltd. All rights reserved.
Scheduling is an important aspect in the overall control of a flexible manufacturing system. The research presented focuses on production scheduling of jobs within a flexible manufacturing cell (FMC)-one type of flexi...
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Scheduling is an important aspect in the overall control of a flexible manufacturing system. The research presented focuses on production scheduling of jobs within a flexible manufacturing cell (FMC)-one type of flexible manufacturing system. Due to the complexity of the FMC scheduling problem, a 0-1 mixed-integer linear programming (MILP) model is formulated for M machines and N jobs with alternative routings. Although small instances of the problem can be solved optimally with MILP models, a two-stage Tabu Search (TS(2)) algorithm that minimises the manufacturing makespan (MS) is proposed to solve medium-to-large-scale problems more efficiently. During Stage I (construction phase), two heuristics are utilised to generate an initial feasible sequence and an initial MS solution. In Stage II (improvement phase), the acquired initial solutions from Stage I are combined with a Tabu Search meta-heuristic procedure that provides improved MS solutions. The TS(2) algorithm provides tremendous savings in computational time for medium/large-sized multi-machine FMC problems.
We present a bilevel model for transmission expansion planning within a market environment, where producers and consumers trade freely electric energy through a pool. The target of the transmission planner, modeled th...
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We present a bilevel model for transmission expansion planning within a market environment, where producers and consumers trade freely electric energy through a pool. The target of the transmission planner, modeled through the upper-level problem, is to minimize network investment cost while facilitating energy trading. This upper-level problem is constrained by a collection of lower-level market clearing problems representing pool trading, and whose individual objective functions correspond to social welfare. Using the duality theory the proposed bilevel model is recast as a mixed-integer linear programming problem, which is solvable using branch-and-cut solvers. Detailed results from an illustrative example and a case study are presented and discussed. Finally, some relevant conclusions are drawn.
This paper addresses the optimal design of the grinding section of a ceramic tile plant operating in a cyclic mode with the units (mills) following a batch sequence. The optimal design problem of this single product p...
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This paper addresses the optimal design of the grinding section of a ceramic tile plant operating in a cyclic mode with the units (mills) following a batch sequence. The optimal design problem of this single product plant is formulated with a fixed time horizon of one week, corresponding to one cycle of production, and using a discrete-time resource task network (RTN) process representation. The size of the individual units is restricted to discrete values, and the plant operates with a set of limited resources (workforce and equipment). The goal is to determine the optimal number and size of the mills to install in the grinding section, the corresponding production schedule, and shift policy. This problem involves labor/semi-labor intensive (LI/SLI) units with a depreciation cost of the same order as that of the operation cost. The optimal design of the grinding section comprises the trade-off between these two costs. The resulting optimization formulation is of the form of a mixedintegerlinearprogramming (MILP) problem, solved using a branch and bound solver (CPLEX 9.0.2). The optimal solution is analyzed for various ceramic tile productions and different shift policies.
It is widely agreed that an increased participation of the demand side in the electricity markets would produce benefits not only for the individual consumers but also for the market as a whole. This paper proposes a ...
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It is widely agreed that an increased participation of the demand side in the electricity markets would produce benefits not only for the individual consumers but also for the market as a whole. This paper proposes a method for quantifying rigorously the effect that such an increase would have on the various categories of market participants. A new centralized complex-bid market-clearing mechanism has been devised to take into consideration the load shifting behavior of consumers who do submit price-sensitive bids. The effects of the proportion of demand response on the market are illustrated using a test system with ten generating units scheduled over 24 periods.
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