This paper presents a mathematical modeling technique that allows for formulating a farmer decision problem. We use fuzzy logic and binary integer programming respectively to represent the factors and decision utiliti...
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ISBN:
(纸本)9781632667335
This paper presents a mathematical modeling technique that allows for formulating a farmer decision problem. We use fuzzy logic and binary integer programming respectively to represent the factors and decision utilities in the problem. We will briefly look at the data requirements for this model. The techniques used in determining the fuzzy rule base will be discussed. We will show the application of artificial neural networks for determining the rule base in our model. A mathematical representation of the system will be created, which can act as an approximation for any problem formulation. Finally, we will use all these techniques on a sample problem, which uses simulated data.
This paper presents a PMU (phasor measurement unit) placement algorithm that gives the optimal PMU placement location and minimum number of PMUs for any electric network while considering different approaches. Complet...
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ISBN:
(纸本)9781467373906
This paper presents a PMU (phasor measurement unit) placement algorithm that gives the optimal PMU placement location and minimum number of PMUs for any electric network while considering different approaches. Complete observability, complete observability with N-1 redundancy, different depths of unobservability, multi-stage sequential placement, real-time monitoring of critical buses are the various PMU placement approaches considered in this paper. The required input for the proposed algorithm is system information and other key aspects like locations of existing PMUs, locations unsuitable for PMU placement, and knowledge of critical buses. binary integer programming is used to find the respective PMU placement location and minimum number of PMUs. The algorithm is tested on IEEE 39-bus system, IEEE 118-bus system, and IEEE 300-bus system. The results suggest that the algorithm can be used on any power system network and the suitable PMU placement approach can be implemented for application.
Computation Offloading, sending computational tasks to more resourceful servers, is becoming a widely-used approach to save limited resources on mobile devices like battery life, storage, processor, etc. Given an appl...
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ISBN:
(纸本)9781479935130
Computation Offloading, sending computational tasks to more resourceful servers, is becoming a widely-used approach to save limited resources on mobile devices like battery life, storage, processor, etc. Given an application that is partitioned into multiple tasks, the offloading decisions can be made on each of them. However, considering the delay constraint and the extra costs on data transmission and remote computation, it is not trivial to make optimized decisions. Existing works have formulated offloading decision problems as either graph-partitioning or binary integer programming problems. The first approach can solve the problem in polynomial time but is not applicable to delay constraints. The second approach relies on an integerprogramming solver without a polynomial time guarantee. We provide an algorithm, DTP (Deterministic delay constrained Task Partitioning), to solve the offloading decision problem with delay constraints. DTP gives near-optimal solution and runs in polynomial time in the number of tasks. Going beyond prior work on linear delay constraints that apply only to serial tasks, we generalize the delay constraints to settings where the dependency between tasks can be described by a tree. Furthermore, we provide another algorithm, PTP (Probabilistic delay constrained Task Partitioning), which gives stronger QoS guarantees. Simulation results show that our algorithms are accurate and robust, and scale well with the number of tasks.
In this article, the problem of selection and configuration of visual sensors in Visual Sensor Networks (VSNs) is studied for coverage of the existing targets in the three-dimensional network area. It is assumed that ...
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ISBN:
(纸本)9781467320726
In this article, the problem of selection and configuration of visual sensors in Visual Sensor Networks (VSNs) is studied for coverage of the existing targets in the three-dimensional network area. It is assumed that visual sensors are capable of Pan-Tilt-Zoom (PTZ) ability and able to choose the covered area and desirable target through configuration of the angle of view in two horizontal and vertical dimensions and alteration of the enlargement scale, In order to solve the problem of selection and configuration, a method is presented according to binary integer programming (BIP). It ensures to find the best solution. In addition, it has less calculation complexity compared with other optimization methods. Applying the proposed solution, two problems of k-coverage and full angle coverage have been assessed using two models of point target model and circular target model. The perceived results properly confirm the efficiency of the proposed method in terms of execution speed and decreasing the computation complexity.
By controlling distribution process, a good improvement will be observed in not only net profit of related company but also customer satisfaction. Cross-docking network is considered as a useful method for achieving t...
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ISBN:
(纸本)9781612848334
By controlling distribution process, a good improvement will be observed in not only net profit of related company but also customer satisfaction. Cross-docking network is considered as a useful method for achieving to these goals. In this paper, transportation problem of cross-docking network is used in order to minimize the total cost for transferring the loads between origins and destinations. The cost of not delivering goods in due time (delay cost) is considered in this study. This assumption makes the model more realistic. Thus, decisions about dispatching directly or indirectly will be more realistic. This problem is formulated using binary integer programming and solved by simulated annealing (SA). Several numerical examples are solved, and the results show that this algorithm can find efficient solutions in comparison with exact algorithm.
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