Charitable foundations and government programmes should endeavour to allocate their limited resources to best serve their constituents. Yet, mathematical programming techniques are rarely used despite overwhelming evi...
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Charitable foundations and government programmes should endeavour to allocate their limited resources to best serve their constituents. Yet, mathematical programming techniques are rarely used despite overwhelming evidence of their superiority in selecting projects that yield higher levels of total benefits. We present a novel hybrid selection model' that combines binary linear programming and heuristic rank-based models applied to two case studies. The first case focuses on providing services to women and shows a hybrid model would have selected the top three signature' projects and maintained an above-average overall project benefit while securing a 180% improvement in the number of projects funded, a 66% improvement in the number of women served and a 132% improvement in the total benefit achieved. In the second case, we apply the hybrid approach to data from the US government's largest forest preservation programme and demonstrate that the hybrid approach could allow the programme to select up to 11 top-scoring projects while still achieving a 97% gain in the total overall benefit compared to their traditional method. These case studies show that the hybrid approach has the potential to be applied in a variety of settings and improve how foundations and programmes achieve their goals.
This paper deals with the Airline Delay Management Problem (ADMP), which can be described as the task of dealing with daily airline operational delays and deciding whether to delay subsequent flights at a hub airport ...
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This paper deals with the Airline Delay Management Problem (ADMP), which can be described as the task of dealing with daily airline operational delays and deciding whether to delay subsequent flights at a hub airport or to have them departing on time. An innovative integer linearprogramming approach is presented to the capacitated case of the ADMP and airport limitations in terms of bay availability, taxiway capacity and runway separation are incorporated to represent capacity constraints. Fuel cost, passenger compensation, and passenger inconvenience costs are included in the objective function. The decision variables include the re-timing of flight departures and arrivals, the use of the airport capacity over time and the rebooking of passengers in case of missed connections. To guarantee the linearity of the optimization model and fast computational times, a receding horizon modeling framework is adopted. The approach is applied to a case study using real operational and passenger data from an international hub and-spoke carrier. The case study shows the capability of the linear model to deal with a complete day of operations within a few minutes. The results suggest that the proposed approach can lead to cost reductions of almost 30% during recovery, when compared with the solution from the airline. In addition, a sensitivity analysis is provided to investigate the impact of not including passenger inconvenience costs and of reducing runway capacity. (C) 2017 Elsevier Ltd. All rights reserved.
This paper presents a new procedure for finding the optimal placement of the phasor measurement units (PMUs) in modern power grids to achieve full network observability under normal operating conditions, and also abno...
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This paper presents a new procedure for finding the optimal placement of the phasor measurement units (PMUs) in modern power grids to achieve full network observability under normal operating conditions, and also abnormal operating conditions such as a single line or PMU outage, while considering the availability of PMU measuring channels. The proposed modeling framework is implemented using the fuzzy binary linear programming (FBLP) technique. linear fuzzy models are proposed for the objective function and constraints alike. The proposed procedure is applied to five benchmark systems such as the IEEE 14-bus, 30-bus, 39-bus, 57-bus, and 118-bus. The numerical results demonstrate that the proposed framework is capable of finding a fine-tuned optimal solution with a simple model and acceptable solution characteristics compared with early works in the literature. Besides, four evaluation indices are introduced to assure the various criteria under study such as the observability depth, measurement redundancy, and robustness of the method under contingencies. The results show that full network observability can be met under normal conditions using 20% PMUs penetration; however, under contingencies, approximately 50% PMUs penetration is required. The novelty of the proposed procedure has proven the capability of the proposed linear fuzzy models to find better optimal number of PMUs with lower number of channels compared to other algorithms under various operating conditions. Hence, the proposed work represents a potential tool to monitor power systems, and it will help the operators in a smart grid environment.
Smart metering systems have become widespread around the world. RF mesh communication systems have contributed to the creation of smarter and more reliable power systems. This paper presents an algorithm for positioni...
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Smart metering systems have become widespread around the world. RF mesh communication systems have contributed to the creation of smarter and more reliable power systems. This paper presents an algorithm for positioning GPRS concentrators to attain delay constraints for a ZigBee-based mesh network. The proposed algorithm determines the number and placement of concentrators using integer linearprogramming and a queueing model for the given mesh network. The solutions given by the proposed algorithm are validated by verifying the communication network performance through simulations.
Ridesharing is an emerging travel mode that reduces the total amount of traffic on the road by combining people's travels together. While present ridesharing algorithms are trip-based, this paper aims to achieve s...
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ISBN:
(纸本)9781450345897
Ridesharing is an emerging travel mode that reduces the total amount of traffic on the road by combining people's travels together. While present ridesharing algorithms are trip-based, this paper aims to achieve significantly higher matching chances by a novel, activity-based algorithm. The algorithm expands the potential destination choice set by considering alternative destinations that are within given space-time budgets and would provide a similar activity function as the originals. In order to address the increased combinatorial complexity of trip chains, the paper introduces an efficient space-time filter on the foundations of time geography to search for accessible resources. Globally optimal matching is achieved by binary linear programming. The ridesharing algorithm is tested with a series of realistic scenarios of different population sizes. The encouraging results demonstrate that the matching rate by activity-based ridesharing is significantly increased from the baseline scenario of traditional trip-based ridesharing.
One of the key applications of low Power wireless sensor networks is wireless metering for smart grid. In such wireless sensor networks, nodes are often battery powered, and hence power is the main constraint for the ...
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ISBN:
(纸本)9781467380164
One of the key applications of low Power wireless sensor networks is wireless metering for smart grid. In such wireless sensor networks, nodes are often battery powered, and hence power is the main constraint for the network. To reduce the power consumption in wireless sensor network with spanning tree structure, data was aggregated from ingresses and send only one aggregated data packet to egress. In this paper we propose an energy efficient algorithm for scheduling each node's transmission in a multi-channel multi-hop wireless sensor network. We formulate the scheduling problem into binarylinear equations for the wireless sensor network with given routing topology, and solve the binarylinear equations to drive optimal scheduling solution. Simulation results show that the proposed method reduces the power consumption up to 40% compared to a non-optimal scheduling method.
Efficient resource allocation in OFDM-based optical networks is directly affected by definition and formulations of Routing and Spectrum Assignment (RSA) problem. In this paper, we propose new binarylinear Programmin...
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ISBN:
(纸本)9781509034352
Efficient resource allocation in OFDM-based optical networks is directly affected by definition and formulations of Routing and Spectrum Assignment (RSA) problem. In this paper, we propose new binary linear programming (BLP) formulations for the RSA problem that provide more efficient resource allocation in comparison with previous formulations. Unlike the conventional formulations that mainly aim at minimizing used spectrum slots, our formulations simultaneously aim at defragmentation and minimization of the assigned spectrum slots. We show contiguity constraint of the conventional formulations may incorrectly make a feasible solution unattainable. To solve this problem, we remove the contiguity constraint and embed its effect as a penalty term in the goal function. Two performance metrics for evaluating the amount of contiguity and defragmentation in a typical network are also defined. Simulation results show that the new formulations provide a considerable improvement in the performance of the RSA process in terms of the amount of contiguity and defragmentation with respect to the previous formulations.
In this paper, we consider the resource allocation problem in a Cognitive Radio (CR) downlink system employing both Orthogonal Frequency Division Multiple Access (OFDMA) and Multiple-Input Multiple-Output (MIMO) techn...
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ISBN:
(纸本)9781509028603
In this paper, we consider the resource allocation problem in a Cognitive Radio (CR) downlink system employing both Orthogonal Frequency Division Multiple Access (OFDMA) and Multiple-Input Multiple-Output (MIMO) technologies. We aim at maximizing the total cognitive system throughput subject to the interference power constraint at the Primary Receiver (PR), the total transmission power constraint at the Secondary Base Station (SBS), and the Quality of Service (QoS) requirement for each SU in terms of the data rate and Bit Error Rate (BER). This joint resource allocation problem integrates subcarrier assignment, power allocation, bit loading, and interference management, and can be formulated as a binary linear programming (BLP) framework. Although the Branch and Bound (BnB) algorithm is a general approach to obtain the optimal solution for a BLP problem, it is impractical in this joint resource allocation problem due to the high computational complexity. In order to provide a good balance between performance and computational complexity, a Novel Two-Step based (NTS) algorithm is proposed in this paper. Numerical results show that the NTS algorithm can reduce the computational complexity significantly with only marginal performance degradation.
Clock mesh is popular in high performance VLSI design because it is more robust against variations than clock tree at a cost of higher power consumption. In this paper, we propose novel techniques based on binary line...
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ISBN:
(纸本)9781424481927
Clock mesh is popular in high performance VLSI design because it is more robust against variations than clock tree at a cost of higher power consumption. In this paper, we propose novel techniques based on binary linear programming for clock mesh synthesis for the first time in the literature. The proposed approach can explore both regular and irregular mesh configurations, adapting to non-uniform load capacitance distribution. Our synthesis consists of two steps: mesh construction to minimize total capacitance and skew, and balanced sink assignment to improve slew/skew characteristics. We first show that mesh construction can be analytically formulated as binary polynomial programming (a class of nonlinear discrete optimization), then apply a compact linearization technique to transform into binary linear programming, significantly reducing computational overhead. Second, our balanced sink assignment enables a sink to tap the least loaded mesh segment (not the nearest one) with another binary linear programming which reduces both slew and skew. Experiments show that our techniques improve the worst skew and total capacitance by 14% and 15% over the state-of-the-art clock mesh algorithm [19] on ISPD09 benchmarks.
In this paper, an efficient and comprehensive formulation for the optimal placement of phasor measurement units (PMUs) is proposed to minimize the number of PMU installation subject to full network observability. More...
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In this paper, an efficient and comprehensive formulation for the optimal placement of phasor measurement units (PMUs) is proposed to minimize the number of PMU installation subject to full network observability. Moreover, the formulation is extended for assuring complete observability under single PMU loss or single line outage cases. Since the proposed optimization formulation is regarded to be a multiple-solution one, both the installation cost and measurement redundancy are employed to differentiate the solutions with the same number of PMUs to be installed. In all of the investigations, the effect of zero-injection buses in the power system is considered. The effectiveness of the proposed method is verified via some IEEE standard systems and compared with some newly reported methods. Results show that the proposed method is simple to implement and more accurate compared to other existing methods. Moreover, by considering the presented method, the minimum number of required PMUs is decreased in some cases. Copyright (c) 2014 John Wiley & Sons, Ltd.
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