The paper analyzes the development level of the institute of public–private partnership (PPP) in Russia’s mining complex and the partnership mechanism, within which the state, using RF Investment Fund monies, assist...
详细信息
The reliability of traffic flows is a serious challenge to cognitive radio networks due to the interruptions from primary users. A backup path scheme is proposed to protect the secondary user traffic flows against the...
详细信息
ISBN:
(纸本)9781424492688
The reliability of traffic flows is a serious challenge to cognitive radio networks due to the interruptions from primary users. A backup path scheme is proposed to protect the secondary user traffic flows against the interruptions from primary users. In such a scheme, the traffic flow can be switched to a backup path if the working path is interrupted by primary users. When primary users leave, the traffic flow will be switched back to the working path. The problem of selecting backup paths is formulated as an integer programming problem. Given a backup path, a statistical rule is proposed for switching the traffic flow to the backup path, based on the Bayesian decision framework. The switching rule is implemented on a USRP GNU Radio node based testbed, which consists of a multi-hop cognitive radio network and a primary user. The hardware experiment shows that the system cost, defined as a weighted sum of throughput loss and average packet delay, is reduced by around 50% in a typical setup, compared with the scenario of no backup paths.
We propose a novel antenna design method consisting of the gradient method and method of moment is proposed. An antenna structure is represented by the combination of small segments. By regarding the 0/1 state segment...
详细信息
ISBN:
(纸本)9783000216442
We propose a novel antenna design method consisting of the gradient method and method of moment is proposed. An antenna structure is represented by the combination of small segments. By regarding the 0/1 state segment variable as a real parameter, a matrix equation for the gradient method is derived. Fast computation causing of automatic decisions of simultaneous changing segments achieves practical design for various antennas, including large-scale antennas.
Advertising is one of the important instruments in the success and continued growth of a product. Total expenditures for advertising in the United States may run into many billions of dollars. In this paper, an effici...
详细信息
We investigate the performance of the recently proposed Unified Particle Swarm Optimization algorithm on two categories of operations research problems, namely minimax and integer programming problems. Different varia...
详细信息
ISBN:
(纸本)0780389166
We investigate the performance of the recently proposed Unified Particle Swarm Optimization algorithm on two categories of operations research problems, namely minimax and integer programming problems. Different variants of the algorithm are employed and compared with established variants of the Particle Swarm Optimization algorithm. Statistical hypothesis testing is performed to justify the significance of the results. Conclusions regarding the ability of the Unified Particle Swarm Optimization method to tackle operations research problems as well as on the performance of each variant are derived and discussed.
This paper proposes a behavioral level partitioning method for efficient behavioral synthesis from a large sequential program consisting of a set of functions. Our method optimally determines functions to be inlined i...
详细信息
ISBN:
(纸本)9781595936059
This paper proposes a behavioral level partitioning method for efficient behavioral synthesis from a large sequential program consisting of a set of functions. Our method optimally determines functions to be inlined into the main module and ones to be synthesized into sub modules in such a way that the overall datapath is minimized while the complexity of individual modules is lower than a certain level. The partitioning problem is formulated as an integer programming problem. Experimental results show the effectiveness of the proposed method.
We propose an optimization method to maximize the productivity of PCB (printed circuit board) assembly of modular mounters. The modular mounter is a series of compact SMD (surface mount device) placement modules, wher...
详细信息
ISBN:
(纸本)9781424481262
We propose an optimization method to maximize the productivity of PCB (printed circuit board) assembly of modular mounters. The modular mounter is a series of compact SMD (surface mount device) placement modules, where each module has assembly head and feeder lanes. The throughput of the mounter is maximized by balancing the assembly time of each module. We indentify the problem as an integer programming problem, and divide the problem into feeder arrangement problem and mount sequence problem by decoupling the path into forward arcs and backward arcs. The integer-programming based algorithms such as branch-and-bound algorithm and transportation algorithm are applied to solve the formulated problems. Simulation results are presented to verify the usefulness of the proposed method.
Engineer-to-order (ETO) production is a method in which products are designed and manufactured in response to customer orders. Typical products of ETO production targeted in this study are large products such as power...
详细信息
ISBN:
(纸本)9780791887882
Engineer-to-order (ETO) production is a method in which products are designed and manufactured in response to customer orders. Typical products of ETO production targeted in this study are large products such as power plants, plants, and shipbuilding. These products have long lead times and delivery times, and production plans need to be generated for a year or more in advance. This study proposes a hierarchical production planning (HPP) framework to generate long-term, medium-term, and short-term production plans using common granularity of production equipment and unit time on production planning method for ETO production of large products. A load planning required for the long-term production plan is formulated as an integer programming problem, and the load plans are generated using a mathematical programming solver and a constraint programming solver.
We develop an approach for minimizing expected unmet demand in a supply chain modelled using a Bayesian network. We allow for nodes to be upgraded, subject to a budget constraint, to reduce the probability that the no...
详细信息
We develop an approach for minimizing expected unmet demand in a supply chain modelled using a Bayesian network. We allow for nodes to be upgraded, subject to a budget constraint, to reduce the probability that the node becomes non-operational. We formulate the problem of selecting an optimal set of node upgrades as a linear binary integer program (BIP). Ours is the first formulation of expected loss minimization in Bayesian-modelled supply chains as a BIP. Unlike previous published formulations, our formulation allows for the conditional probability table of each node in the Bayesian network to be quite general, including allowing an upgraded node to have a nonzero probability of failure, and allowing multiple types of upgrades for a node. This reflects real world scenarios, including those in which node upgrades do not completely eliminate risk. We present computational results for small problems and illustrate how the solution set changes with the budget. Results for a larger food supply chain with 44 nodes and 63 arcs are also discussed. Finally, we present a preprocessing method for reducing the number of constraints needed for the BIP formulation, and evaluate the savings in run time achieved by applying our constraint reduction method.
Brain Storm Optimization (BSO) is one of the major effective swarm intelligence algorithms that simulate the human brainstorming process to find optimality for optimization problems. BSO method has successfully been a...
详细信息
Brain Storm Optimization (BSO) is one of the major effective swarm intelligence algorithms that simulate the human brainstorming process to find optimality for optimization problems. BSO method has successfully been applied to many real-world problems. This study employs BSO method, called BSO-IP, to solve the integer programming problem. Our method collects best solutions to generate new solutions that then search for optimal solutions in all areas of search *** BSO-IP method solves some benchmark integer programming problems to test its efficiency. The BSO-IP is used to simulate the 3D protein structure prediction problem, which is mathematically presented as an integer programming problem to approve the viability and helpfulness of our proposed Algorithm. The experimental results of different benchmarks protein structure show that our proposed method is superior in high performance, convergence, and stability in predicting protein structure. We examined our strategy results to be promising compared to other results.
暂无评论