Optimal sensorplacement on freeway corridor is of great interest to transportation authorities. However, current traffic sensors are easily subject to various failures. Therefore, it is necessary to incorporate senso...
详细信息
Optimal sensorplacement on freeway corridor is of great interest to transportation authorities. However, current traffic sensors are easily subject to various failures. Therefore, it is necessary to incorporate sensor failure into the optimal sensorplacement model. In this article, a two-stage stochastic model is proposed for the purpose of travel time estimation on freeway corridor. To balance the effectiveness and reliability, a stochastic conditional value at risk (CVaR) model is also proposed. Since both models are too complicated, a customized genetic algorithm is developed. Numerical experiments show that considering sensor failure makes a significant performance improvement in the sensorplacement pattern. Sensitivity analysis is also applied to investigate the impact of a number of allowable sensors and different traffic sensor failure probability.
The surveillance multi-sensorplacement is an important optimization problem that consists of positioning several sensors of different types to maximize the coverage of a determined area while minimizing the cost of t...
详细信息
The surveillance multi-sensorplacement is an important optimization problem that consists of positioning several sensors of different types to maximize the coverage of a determined area while minimizing the cost of the deployment. In this work, we tackle a modified version of the problem, consisting of spatially distributed multi-sensorplacement for indoor surveillance. Our approach is focused on security surveillance of sensible indoor spaces, such as military installations, where distinct security levels can be considered. We propose an evolutionary algorithm to solve the problem, in which a novel special encoding (integer encoding with binary conversion) and effective initialization have been defined to improve the performance and convergence of the proposed algorithm. We also consider the probability of detection for each surveillance point, which depends on the distance to the sensor at hand, to better model real-life scenarios. We have tested the proposed evolutionary approach in different instances of the problem, varying both size and difficulty and obtained excellent results regarding the cost of sensors' placement and convergence time of the algorithm.
In this paper, we are interested in the Robust sensorplacementproblem (RSPP) in municipal water networks. As the contamination source and time are rather random and almost impossible to forecast, we aim to minim...
详细信息
In this paper, we are interested in the Robust sensorplacementproblem (RSPP) in municipal water networks. As the contamination source and time are rather random and almost impossible to forecast, we aim to minimize the maximum population exposed over all contamination scenarios by placing a limited number of sensors into the network. We formulate a mixedinteger program model based on an absolute robustness criterion and design a tabu search heuristic to solve it quickly and efficiently. At last, we use a computational experiment to illustrate the effectiveness of our approach compared to the classical methods found in most of the literature.
Coverage and connectivity are two important performance metrics in wireless sensor networks. In this paper, we study the sensor placement problem to achieve both coverage and connectivity. Instead of using the simplis...
详细信息
Coverage and connectivity are two important performance metrics in wireless sensor networks. In this paper, we study the sensor placement problem to achieve both coverage and connectivity. Instead of using the simplistic disk coverage model, we use our recently proposed confident information coverage model as the sensor coverage model. The grid approach is applied to discretize the sensing field, and our objective is to place the minimum number of sensors to form a connected network and to provide confident information coverage for all of the grid points. We first formulate the sensor placement problem as a constrained optimization problem. Then, two heuristic algorithms, namely the connected cover formation (CCF) algorithm and the cover formation and relay placement with redundancy removal (CFRP-RR) algorithm, are proposed to find the approximate solutions for the sensor placement problem. The simulation results validate their effectiveness, and the CCF algorithm performs slightly better than the CFRP-RR algorithm.
The perspective relaxation (PR) is a general approach for constructing tight approximations to mixed-integer nonlinear programs (MINLP) with semicontinuous variables. The PR of a MINLP can be formulated either as a mi...
详细信息
The perspective relaxation (PR) is a general approach for constructing tight approximations to mixed-integer nonlinear programs (MINLP) with semicontinuous variables. The PR of a MINLP can be formulated either as a mixed-integer second-order cone program (MI-SOCP), provided that the original objective function is SOCP-representable, or as a semi-infinite MINLP. In this paper, we show that under some further assumptions (rather restrictive, but satisfied in several practical applications), the PR of a mixed-integer quadratic program (MIQP) can also be reformulated as a piecewise-quadratic program (QP), ultimately yielding a QP relaxation of roughly the same size of the standard continuous relaxation. Furthermore, if the original problem has some exploitable structure, then this structure is typically preserved in the reformulation, thus allowing the construction of specialized approaches for solving the PR. We report on implementing these ideas on two MIQPs with appropriate structure: a sensor placement problem and a quadratic-cost (single-commodity) network design problem.
暂无评论