A5088969714- Advanced Multi-Objective Optimization Algorithms
- Simulation Techniques and Applications
- Formal Methods in Verification
- Physical Unclonable Functions (PUFs) and Hardware Security
- Security and Verification in Computing
- Software Reliability and Analysis Research
- Software Testing and Debugging Techniques
- Water Systems and Optimization
- Advanced Malware Detection Techniques
- Gaussian Processes and Bayesian Inference
- Optimal Experimental Design Methods
- Smart Grid Energy Management
- Metaheuristic Optimization Algorithms Research
- Scheduling and Optimization Algorithms
- Advanced Bandit Algorithms Research
- Water Treatment and Disinfection
- Advanced Image and Video Retrieval Techniques
- Model Reduction and Neural Networks
- Advanced Queuing Theory Analysis
- Reservoir Engineering and Simulation Methods
- Manufacturing Process and Optimization
- Sports Analytics and Performance
- Smart Grid Security and Resilience
Arizona State University
2017-2021
Decision Systems (United States)
2019
This work is in the field of requirements driven search-based test case generation methods for Cyber-Physical Systems (CPS). The basic characteristic testing that search process guided by high level captured formal logic and, particular, Signal Temporal Logic (STL). Given a system trajectory, STL specifications can be equipped with quantitative semantics which evaluate closeness given trajectory from violating requirement. Hence, searching trajectories decreasing value respect to...
This report presents the results from 2020 friendly competition in ARCH workshop for falsification of temporal logic specifications over Cyber-Physical Systems. We briefly describe settings, which have been inherited previous year, give background on participating teams and tools discuss selected benchmarks. The benchmarks are available website1, as well competition’s gitlab repository2. In comparison to 2019, we two new with novel approaches, show a clear improvement performances some
This report presents the results from 2019 friendly competition in ARCH workshop for falsification of temporal logic specifications over Cyber-Physical Systems. We describe organization and how it differs previous years. give background on participating teams tools discuss selected benchmarks results. The are available website1, as well competition’s gitlab repository2. main outcome is a common benchmark repository, an initial base-line falsification, with multiple tools, which will...
This report presents the results from 2021 friendly competition in ARCH work- shop for falsification of temporal logic specifications over Cyber-Physical Systems. We briefly describe settings, which have been inherited previ- ous years, give background on participating teams and tools discuss selected benchmarks. Apart new requirements participants, major novelty this instalment is that falsifying inputs validated independently. During pro- cess, we uncovered several issues like...
Optimization-based falsification, or search-based testing, is a method of automatic test generation for Cyber-Physical System (CPS) safety evaluation. CPS evaluation guided by high level system requirements that are expressed in Signal Temporal Logic (STL). Trajectories from executed simulations evaluated against STL using satisfaction robustness as quantitative metric. In particular, the distance metric between simulated trajectory, associated to specific input, and known unsafe set, i.e.,...
Real-time decision making has acquired increasing interest as a means to efficiently operating complex systems. The main challenge in achieving real-time is understand how develop next generation optimization procedures that can work using: (i) real data coming from large dynamical system, (ii) simulation models available reproduce the system dynamics. While this paper focuses on different problem with respect literature RL, methods proposed be used support sequential setting well. result of...
Water Distribution Networks are a particularly critical infrastructure for the high energy costs and frequent failures. Variable Speed Pumps have been introduced to improve regulation of water pumps, key overall performance. This paper addresses problem analyzing effect VSPs on pressure distribution WDN, which is highly correlated leakages costs. Due fact that network behavior can only be simulated, we formulate as black box feasibility determination, solve with novel stochastic partitioning...
Water Distribution Networks are a particularly critical infrastructure for the high energy costs and frequent failures. Variable Speed Pumps have been introduced to improve regulation of water pumps, key overall performance. This paper addresses problem analyzing effect VSPs on pressure distribution WDN, which is highly correlated leakages costs. Due fact that network behavior can only be simulated, we formulate as black box feasibility determination, solve with novel stochastic partitioning...
Recent advances in sensing, data analytics, and manufacturing technologies (e.g., 3-D printing, soft robotics, nanotechnologies, etc.) provide the potential to produce highly customized products by allowing flexible system design, endless device configurations, unprecedented information flows. These opportunities also increase complexity of controlling such systems optimally, which typically requires fast exploration an increasingly large number alternative operation strategies. Simulation...
Analytical and simulation models are two common types of approaches used to estimate predict the performance complex production systems. Typically analytical fast run but can have reduced accuracy. On other hand achieve high accuracy, only at cost large time number replications. Traditionally, research has been focusing on development able a satisfactory trade off between accuracy computational effort. Nevertheless, such an approach implies choice single model approximate system behavior....
The field of simulation optimization has seen algorithms proposed for local optimization, drawing upon different locally convergent search methods. Similarly, there are numerous global with differing strategies to achieve convergence. In this paper, we look specifically into meta-model based that stochastically drive through an optimal sampling criteria evaluated over a constructed the predicted response considering uncertainty response. We propose Trust Region Based Optimization Adaptive...
The field of simulation optimization has seen algorithms proposed for local optimization, drawing upon different locally convergent search methods. Similarly, there are numerous global with differing strategies to achieve convergence. In this paper, we look specifically into meta-model based that stochastically drive through an optimal sampling criteria evaluated over a constructed the predicted response considering uncertainty response. We propose Trust Region Based Optimization Adaptive...
Global optimization techniques often suffer the curse of dimensionality. In an attempt to face this challenge, high dimensional search try identify and leverage upon effective, lower, dimensionality problem either in original or a transformed space. As result, algorithms for exploit projection create random embedding. Our approach avoids modeling spaces, assumption low effective We argue that effectively functions can be recursively optimized over sets complementary lower subspaces. light,...
Knowledge discovery and decision making through data-and model-driven computer simulation ensembles are increasingly critical in many application domains. However, these expensive to obtain. Consequently, given a relatively small budget, one needs identify sparse ensemble that includes the most informative simulations help effective exploration of space input parameters. In this paper, we propose complicacy-guided parameter sampling (CPSS) for knowledge with limited budgets, which relies on...
We introduce the algorithm Bayesian Optimization (BO) with Fictitious Play (BOFiP) for optimization of high dimensional black box functions. BOFiP decomposes original, dimensional, space into several sub-spaces defined by non-overlapping sets dimensions. These are randomly generated at start algorithm, and they form a partition dimensions original space. searches alternating BO, within sub-spaces, information exchange among to update sub-space function evaluation. The basic idea is...