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Showing 1 to 18 of 18 for “"chance constraints"”.
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Probabilistic motion planning and optimization incorporating chance constraints
… The risk-aware stage of p-Chekov accounts for chance constraints through state probability distribution and collision probability estimation. Based on the deterministic Chekov planner, p-Chekov incorporates a linear-quadratic Gaussian motion planning (LQG-MP) approach into robot state …
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Analytic chance constraints for the robust guidance of autonomous parafoils
… as Analytic CC-RRT, builds upon the framework of chance-constrained rapidly-exploring random trees (CC-RRT). This planner enables fast incremental trajectory construction in cluttered, non-convex environments, while using chance constraints to ensure probabilistic feasibility. The designed …
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A framework for the integration of design and operation under uncertainty using dynamic perturbation and chance constraints
Process design is a fundamental aspect of developing new processes in the chemical industry. Often, process design is performed sequentially. In the first step, the design is found by optimization under steady-state conditions and under consideration of economic criteria. In the second step, the …
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Constraint programming for optimization under uncertainty in inventory control
… between variables can be stated in the form of constraints. CP features discrete domains and global constraints. Global constraints capture interesting substructures of a problem, encapsulate dedicated inference algorithms based on feasibility and/or optimality reasoning, and provide information …
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Direct-Current Power Flow Solvers and Energy Storage Sizing
… random, the energy and power limits are posed as chance constraints. The chance constraints are enforced in a distributionally robust fashion. The proposed scheme is contrasted to a charging policy under Gaussian uncertainties and a deterministic formulation.
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Optimization Techniques for Instream Flow Allocations
… for a reservoir are defined in a set of LDR chance constraints which enforce the satisfaction, at specified reliabilities, of water use goals other than those required to meet biological IFN. Values for instream flows which are maximized are based on the median committed releases produced …
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Threat Assessment and Proactive Decision-Making for Crash Avoidance in Autonomous Vehicles
… The crash avoidance problem is formulated as a chance-constrained optimization problem to account for uncertainty in the surrounding vehicle's motion. These chance-constraints always ensure a minimum probabilistic safety of the autonomous vehicle by keeping the probability of crash below a …
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NETWORK OPTIMIZATION TO MODEL RANDOM RISK OF SUPPLY CHAIN DISRUPTIONS
… these models utilize linear integer programming, chance constraints programming, and dynamic programming in different ways, seeking to demonstrate various methods for routing supplies through a network vulnerable to random disruptions. Lastly, we analyze results to determine the suitability of …
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Dynamic execution of temporal plans with sensing actions and bounded risk
… within risk bounds (also referred to as chance constraints). By being conditional, the plan allows the autonomous agent to adapt to its environment in real-time by conditioning the choice of activity to be executed on the agent's current level of knowledge, or belief, about the true state …
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Robust sampling-based motion planning for autonomous vehicles in uncertain environments
… state and future evolution of environmental constraints. The vehicle may also face uncertainty in its own motion. To provide safe navigation under such conditions, motion planning algorithms must be able to rapidly generate smooth, certifiably robust trajectories in real-time. The primary …
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Techniques for VLSI Circuit Optimization Considering Process Variations
… as fuzzy numbers in the fuzzy formulation and as chance constraints in the stochastic formulation. Further, we have proposed a piece-wise linear formulation for the variation aware buffer insertion and driver sizing (BIDS) problem. The BIDS problem is solved at the logic level, with look-up table …
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Energy-efficient control of a smart grid with sustainable homes based on distributing risk
… control of a residential building, and 3) a chance-constrained model-predictive controller with a probabilistic guarantee of constraint satisfaction, which can control continuously operating systems such as an electrical grid and a building. We build the three algorithms upon the …
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Hybrid Multi-Objective Optimization Models for Managing Pavement Assets
… that uses the weighting sum method and chance constraints. This model can handle multiple incommensurable and conflicting objectives while considering probabilistic constraints related to the available budget over the planning horizon, but is found more suitable to problems with small …
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Machine Learning and Quantum Computing for Optimization Problems in Power Systems
While optimization problems are ubiquitous in all domains of engineering, they are of critical importance to power systems engineers. A safe and economical operation of the power systems entails solving many optimization problems such as security-constrained unit commitment, economic dispatch, …
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Frequency Stability Constrained Grid Operation with High Penetration of Renewables
… linked with PV power output is factored in using chance constraints to ensure real time delivery of its frequency regulation services. The framework’s functionality is verified in the IEEE 39 bus network with a large scale PV power plant. The results show that a small real time generation dispatch …
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Coping Uncertainty in Wireless Network Optimization
… programming, worst-case optimization, and chance-constrained programming (CCP). Among the three, CCP has some unique benefits compared to the other two approaches. Stochastic programming explicitly requires full distribution knowledge, which is usually unavailable in practice. In …
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Collaborative diagnosis of over-subscribed temporal plans
… over-subscription is resolved through suspending constraints or dropping goals. While helpful, in real-world scenarios, we often want to preserve our plan goals as much possible. As human beings, we know that slightly weakening the requirements of a travel plan, or replacing one of its …