This paper presents a mixed integer linear programming formulation for load-side control of electrical energy demand. The formulation utilizes demand prediction to determine if control actions are necessary, and it sc...
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This paper presents a mixed integer linear programming formulation for load-side control of electrical energy demand. The formulation utilizes demand prediction to determine if control actions are necessary, and it schedules both shedding and restoration times based on an optimization model that minimizes the net cost of load shedding. Operational constraints are satisfied through the use of minimum/maximum uptimes/downtimes, which depend upon the current state of the system. The algorithm is evaluated using a simulation model of an underground coal mining operation where, (i) its performance is compared with a traditional static, priority-based, load-shedding schedule, and, (ii) its potential is established for producing net savings through demand control.
The trim-loss problem appears when a customer's demand is to be satisfied in a paper converting mill. A set of product paper reels need to be cut from raw-paper reels. The problem is by nature an integer problem a...
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The trim-loss problem appears when a customer's demand is to be satisfied in a paper converting mill. A set of product paper reels need to be cut from raw-paper reels. The problem is by nature an integer problem and therefore gives rise to a difficult combinatorial problem. Maybe the most difficult problem beside. the combinatorics, is the fact that the paper converting mill needs to adapt itself to both the customer specified widths and the raw paper widths that are delivered from a raw paper mill. This fact makes it difficult to avoid material losses during the process. In the present paper some key issues are considered as to the combining the paper mill and the paper converting mill. (C) 1998 published by Elsevier Science Ltd. All rights reserved.
Development of a sensitivity analysis (SA) procedure is a significant part of constructing robust solutions for a class of resource constrained planning and scheduling problems. The key uncertain parameters, the proba...
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Development of a sensitivity analysis (SA) procedure is a significant part of constructing robust solutions for a class of resource constrained planning and scheduling problems. The key uncertain parameters, the probabilities that projects will be terminated, occur in both the objective function and the left-hand side of the constraints. Estimates of the mean probability of failure for a task can be extracted from historical data;however, it is important to take into account the sensitivity of the proposed solution to variations in these estimates. Parameter studies show complex interactions between the objective function and the resource constraints. A method to study the behavior of the solution using branch and bound algorithms enhanced with logical programming is introduced. (C) 1998 Elsevier Science Ltd. All rights reserved.
Two main aspects in hardware/software co-design are hardware/software partitioning and co-synthesis. Most co-design approaches work only on one of these problems. In this paper, an approach coupling hardware/software ...
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ISBN:
(纸本)9780818683596
Two main aspects in hardware/software co-design are hardware/software partitioning and co-synthesis. Most co-design approaches work only on one of these problems. In this paper, an approach coupling hardware/software partitioning and co-synthesis is presented, working fully-automatically. The techniques have been integrated in the co-design tool COOL supporting the complete design flow from system specification to board-level implementation for multi-processor and multi-ASIC target architectures for data-flow dominated applications.
An optimization problem for designing a non-uniformly spaced, linear phase FIR filter with minimal complexity is formulated, and solved by mixed integer linear programming (MILP). Design examples illustrate that the p...
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An optimization problem for designing a non-uniformly spaced, linear phase FIR filter with minimal complexity is formulated, and solved by mixed integer linear programming (MILP). Design examples illustrate that the proposed method is useful for designing a wide range of filter types, and can outperform the subset selection-based design methods.
Several optimization models have been proposed in the literature to solve the project selection, timing and sequencing problem. Models based on dynamic programming (DP) such as embebed state DP, objective space DP, an...
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Progression schemes are commonly used by traffic engineers for the coordination of traffic signals on arterial streets. Commonly available programs use the traditional approach which consists of a uniform bandwidth de...
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Progression schemes are commonly used by traffic engineers for the coordination of traffic signals on arterial streets. Commonly available programs use the traditional approach which consists of a uniform bandwidth design for each arterial. The multi-band criterion, on the other hand, enables us to adapt the progressions to the specific characteristics of each link in the network and thus to obtain improved performance. In this paper we describe the development and application of the multi-band signal optimization scheme in multiarterial grid networks. The proposed model optimizes all the signal control variables, including phase lengths, offsets, cycle time and phase sequences and generates variable bandwidth progressions on each arterial in the network.
A workpiece scheduling problem considering imprecisions over processing and transporting times is studied in this work. These considerations result in a fuzzy linearprogramming problem. We present methodologies to so...
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A workpiece scheduling problem considering imprecisions over processing and transporting times is studied in this work. These considerations result in a fuzzy linearprogramming problem. We present methodologies to solve them, based on the fuzzy number ordering techniques. These methodologies give good information to decision makers about the domain containing the optimal solution. The proposed algorithm is applied in an example and the results are analysed.
This paper studies the problem of designing a logical topology over a wavelength-routed all-optical network (AON) physical topology, The physical topology consists of the nodes and fiber links in the network, On an AO...
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This paper studies the problem of designing a logical topology over a wavelength-routed all-optical network (AON) physical topology, The physical topology consists of the nodes and fiber links in the network, On an AON physical topology, we can set up lightpaths between pairs of nodes, where a lightpath represents a direct optical connection without any intermediate electronics, The set of lightpaths along with the nodes constitutes the logical topology, For a given network physical topology and traffic pattern (relative traffic distribution among the source-destination pairs), our objective is to design the logical topology and the routing algorithm on that topology so as to minimize the network congestion while constraining the average delay seen by a source-destination pair and the amount of processing required at the nodes (degree of the logical topology), We will see that ignoring the delay constraints can result in fairly convoluted logical topologies with very long delays, On the other hand, in all our examples, imposing it results in a minimal increase in congestion, While the number of wavelengths required to imbed the resulting logical topology on the physical all optical topology is also a constraint in general, we find that in many cases of interest this number can be quite small, We formulate the combined logical topology design and routing problem described above (ignoring the constraint on the number of available wavelengths) as a mixed integer linear programming problem which we then solve for a number of cases of a six-node network, Since this programming problem is computationally intractable for larger networks, we split it into two subproblems: logical topology design, which is computationally hard and will probably require heuristic algorithms, and routing, which can be solved by a linear program, We then compare the performance of several heuristic topology design algorithms (that do take wavelength assignment constraints into account) against
This paper presents a mixed integer linear programming (MILP) model for a new class of dynamic project selection and funding problems under risk given multiple scarce resources of different qualifications. The underly...
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This paper presents a mixed integer linear programming (MILP) model for a new class of dynamic project selection and funding problems under risk given multiple scarce resources of different qualifications. The underlying stochastic decision tree concept extends classical approaches mainly in that it adds a novel node type that allows for the continuous control of discrete branching probability distributions. The control functions are piecewise linear and are convex for the costs and concave for the benefits. The MILP-model has been embedded in a prototype Decision Support System (DSS). With respect to the proposed solution the DSS provides complete probability distributions for both costs and benefits.
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