A dedicated Inter Terminal Transport (ITT) system must be able to efficiently transport containers inside the port area over a separate road preventing congestion on the ports entry roads, bundling incoming and outgoi...
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ISBN:
(纸本)9781479931064
A dedicated Inter Terminal Transport (ITT) system must be able to efficiently transport containers inside the port area over a separate road preventing congestion on the ports entry roads, bundling incoming and outgoing container flows, and increasing competitiveness of the port. In this paper, a technique for decision support when designing inter terminal transport systems is proposed. In particular, a deterministic minimum cost flow model with time expanded graphs is presented. The model is able to support the design phase by quickly calculating an optimal vehicle configuration minimizing delays, saving time and money in the early phases of planning. In order to illustrate the potential of the model, it is applied for the proposed ITT system at Maasvlakte 1 and 2 areas in the Port of Rotterdam. The optimal configurations, as well as impact of various parameters, are determined.
Based on the day-ahead forecast of system load and wind power output. A joint operation of pumped storage and wind power plants model is built with the purpose of minimizing the system operation cost. In order to achi...
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ISBN:
(纸本)9781479941254
Based on the day-ahead forecast of system load and wind power output. A joint operation of pumped storage and wind power plants model is built with the purpose of minimizing the system operation cost. In order to achieve the higher system flexibility and reduce the impact of volatility of wind power, pumped-storage units are incorporated into the unit commitment (UC) problem with wind power. The UC problem of the joint operation of pumped-storage and wind power plants is formulated as the mixedinteger convex program, which is optimized by Cplex. Conducted on a ten-unit system simulation, we can get the conclusion that the joint operation of pumped-storage and wind power plants is effective to reduce the impact of volatility of wind power on the power grid operation. At the same time, economic benefit is remarkable.
Managing uncertainty has been a challenging task for market operations. This paper first reviews the current practice of managing uncertainties at MISO. A framework of using robust optimization based approach on MISO ...
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ISBN:
(纸本)9781479964154
Managing uncertainty has been a challenging task for market operations. This paper first reviews the current practice of managing uncertainties at MISO. A framework of using robust optimization based approach on MISO Look-Ahead commitment (LAC) is then introduced. The numerical results show that this type of approaches are promising and yet with challenges to overcome in order to be practical for real world application.
This paper deals with the problem of scheduling of mobile robots taking into account preemption cases in a flexible manufacturing system (FMS). In addition to capability of transporting materials between some machines...
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ISBN:
(纸本)9783319075938;9783319075921
This paper deals with the problem of scheduling of mobile robots taking into account preemption cases in a flexible manufacturing system (FMS). In addition to capability of transporting materials between some machines, mobile robots are able to perform manufacturing tasks at other machines by using their manipulation arms. These manufacturing tasks can be preempted to allow mobile robots to transport materials when needed. The performance criterion is to minimize time required to complete all tasks, i.e. makespan. A mixed-integer programming (MIP) model is formulated to find the optimal solutions for the problem. Numerical experiments are investigated to demonstrate results of the proposed approach.
The EU research project DISCUS defines a future proof end-to-end network architecture for next-generation communication networks. One central decision is at which and at how many Local Exchange (LE) locations the acti...
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ISBN:
(纸本)9781479956012
The EU research project DISCUS defines a future proof end-to-end network architecture for next-generation communication networks. One central decision is at which and at how many Local Exchange (LE) locations the active equipment has to be placed. The key drivers here are threefold: as hard constraint, technical requirements must be satisfied, while as softer constraints, reliability and cost-efficiency should be as high as possible. In this paper we present an optimization study on a set of parameters that influence the number of selected locations for active equipment. In particular we compute the number of active nodes that is actually necessary to connect all customers. Moreover, for this study we compute a realistic reference network that contains the Local Exchange (LE) locations of Italy provided by TELECOM ITALIA.
Currently, Russian power sector has switched to the market model for controlling electric power industry functioning and development. Due to a need to consider numerous specific features characteristic of the market-b...
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Currently, Russian power sector has switched to the market model for controlling electric power industry functioning and development. Due to a need to consider numerous specific features characteristic of the market-based industry, modern criteria for designing electric networks should obviously differ from the criteria of "planned economy" approach. The paper considers new method for long-term transmission expansion problem (TEP) based on solving number of optimization subproblems with a system of mathematical models. The models allow taking into account set of technical and economical factors. The proposed method is practically applied to the problem of Russian Unified National Energy Grid (UNEG) expansion.
The electric rail sector, like many sectors, is looking for means to reduce its energy consumption and energy cost. In this work we consider the scenario where the utility provider charges based on the maximum consump...
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ISBN:
(纸本)9781509001644
The electric rail sector, like many sectors, is looking for means to reduce its energy consumption and energy cost. In this work we consider the scenario where the utility provider charges based on the maximum consumption over a period. Therefore one wishes to schedule the departure of trains such that the aggregate load is balanced across time periods while satisfying timetabling and resource restrictions. We present an approach which combines the strengths of a number of research areas such as constraint programming, linear programming, mixed-integer programming, and large neighbourhood search. The empirical performance on instances from an ongoing research challenge demonstrates the approach's ability to dramatically reduce the overall energy cost. In addition, we are able to close a number of the instances for which we prove optimality.
This technical note concerns the predictive control of discrete-time linear models subject to state, input and avoidance polyhedral constraints. Owing to the presence of avoidance constraints, the optimization associa...
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This technical note concerns the predictive control of discrete-time linear models subject to state, input and avoidance polyhedral constraints. Owing to the presence of avoidance constraints, the optimization associated with the predictive control law is non-convex, even though the constraints themselves are convex. The inclusion of the avoidance constraints in the predictive control law is achieved by the use of a modified version of a mixed-integer programming approach previously derived in the literature. The proposed modification consists of adding constraints to ensure that linear segments of the system trajectories between consecutive sampling times do not cross existing obstacles. This avoids the significant extra computation that would be incurred if the sampling time was reduced to prevent these crossings. Simulation results show that the inclusion of these additional constraints successfully prevents obstacle collisions that would otherwise occur. Copyright (C) 2008 John Wiley & Sons, Ltd.
In this paper, we propose a new probabilistic model for minimizing the anticipated regret in combinatorial optimization problems with distributional uncertainty in the objective coefficients. The interval uncertainty ...
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In this paper, we propose a new probabilistic model for minimizing the anticipated regret in combinatorial optimization problems with distributional uncertainty in the objective coefficients. The interval uncertainty representation of data is supplemented with information on the marginal distributions. As a decision criterion, we minimize the worst-case conditional value at risk of regret. The proposed model includes the interval data minmax regret model as a special case. For the class of combinatorial optimization problems with a compact convex hull representation, a polynomial sized mixed-integer linear program is formulated when (a) the range and mean are known, and (b) the range, mean, and mean absolute deviation are known;and a mixed-integer second order cone program is formulated when (c) the range, mean, and standard deviation are known. For the subset selection problem of choosing K elements of maximum total weight out of a set of N elements, the probabilistic regret model is shown to be solvable in polynomial time in the instances (a) and (b) above. This extends the current known polynomial complexity result for minmax regret subset selection with range information only.
This paper describes mixedinteger nonlinear programming (MINLP) heuristics for solving dynamic scheduling problems in complex petroleum production systems with a network topology. We modify the Feasibility Pump heuri...
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This paper describes mixedinteger nonlinear programming (MINLP) heuristics for solving dynamic scheduling problems in complex petroleum production systems with a network topology. We modify the Feasibility Pump heuristic for convex MINLPs [Bonami and Gonçalves, 2010] by formulating a multiobjective problem, in which we aim at balancing the two goals of quickly obtaining a feasible solution and preserving solution quality with respect to the objective value. We further present a simple linearization-based heuristic, only aimed at quickly generating feasible solutions. The MINLP heuristics are applied to a dynamic multi-pipeline shale well and compressor scheduling problem, targeted on application in decision-support tools for improving operations in large shale-gas systems. Developing efficient and robust heuristics are important for the applicability of these tools, in the sense that low computation times are often more important than global optima. A computational study shows that the proposed objective-oriented Feasibility Pump is competitive both in terms of solution quality and computation time compared to other heuristics and the branch-and-bound method.
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