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To deal with the increasing penetration of uncertainties caused by renewable generations and uncertain loads, this paper proposes a novel robust optimization model for the optimal power flow (OPF) problem of power systems. In the model proposed, the generation and the network topology are co-optimized, and then the proposed robust optimal power flow with transmission switching (ROPF_TS) model is converted...
A secrecy transmission method with robust power control is investigated in this paper for a downlink two-tier femtocell network, where an eavesdropper attempts to wiretap the legitimate macrocell users. Considering the imperfect channel gains, a probability constraint robust optimization problem is formulated to satisfy the quality-of-service (QoS) of users. We aim to maximize the secrecy rate with...
This paper addresses a surgeries scheduling problem with a single server in charge of key medical facility. A surgery can be processed with a precedent setup by the server on one of available operating rooms. The setup can be processed at only one surgery at any time. Thus, it is critically important to simultaneously consider the setup precedence and operating room scheduling decisions. A robust...
In this paper, the problem of fleet management in electric vehicles (EVs) sharing service under demand uncertainty is studied. To solve this problem, we propose two robust methodologies to generate robust fleets reposition plans that mitigate rental demand uncertainty and imbalances. More specifically, an adjustable robust optimization model (AROM) and joint chance constraints model (CCM) are developed...
To enable an intelligent traffic light system (ITLS) to consider the interactions between the signal controls and the traffic flow distribution resulting from the selfish-routing behaviors of travelers, a dynamic origin-destination (O-D) demand estimation model and a dynamic combined traffic assignment and signal control (CTA-SC) model are needed. However, the ITLS may collect inaccurate and incomplete...
Renewable energies are expected to be the main electricity generation source. However, the variability of renewable energy supply poses challenges to the generation expansion modelling as uncertainty of hourly generation need to be adequately taken into account. This paper analyzes the implications of different approaches to optimization under uncertainty, ranging from stochastic to robust optimization...
In this paper, we integrate two independent multiplicative uncertainties (uncertain demand and cost) and facility disruptions together, introduce budget uncertainty set to capture uncertain parameters. Based on the underlying deterministic model, we propose a two-stage robust facility location model, incorporating facility disruptions in recourse stage, which is an nonlinear problem resulted by two...
Technological advances and climate considerations drive substantial changes within the electricity sector. Yet, these changes, although their thrust might be intuitive, are subject to large uncertainties: Technologies may be available earlier or later, international/regional co-ordination may work better or worse etc. This poses significant challenges to the task of transmission planning: Therefore,...
A Linear Quadratic robust control algorithm is proposed for the system with non-stochastic uncertainties. In this paper, the uncertainties are the noises which lie in a bounded ellipsoid set. The assumption weakens the requirements of the known Gaussian distribution in the traditional Linear Quadratic Gaussian (LQG) control. Based on the linear characteristic of the system and robust optimization...
In order to explore the effect of altruistic behavior on supply chain policies and performance, based on the wholesale price contract, we establish a game model consisted of an altruistic retailer and a self-interested supplier, and obtain the robust optimal solution when the demand information is missing. We find, the improvement of the selfish supplier gains are at the expense of the altruistic...
In virtualized datacenters (vDCs), dynamic consolidation of virtual machines (VMs) is used as one of the most common techniques to achieve both energy-and resource-utilization efficiency. Live migrations of VMs are used for dynamic consolidation but due to dynamic resource demand variation of VMs may lead to frequent and non-optimal migrations. Assuming deterministic workload of the VMs may ensure...
In this paper, a modified PI-D controller with pulse width pulse frequency (PWPF) modulator with on-off thruster for a rigid satellite is tuned under uncertainties in a quasi- normalized form. A modified proportional-integral-derivative (PID) based on observer method is used as a controller. Uncertainty is considered on thruster model, thrust level, and external disturbance parameters. Thruster is...
This paper focuses on a closed-loop production planning and inventory control problem commonly encountered in the real manufacturing practice. We firstly present a deterministic model for this particular problem with several features such as remanufacturing and one-way substitution. Then we take into consideration the uncertainty of the new item demand, the remanufactured item demand and the returned...
This paper reports recent progress in modeling and simulation of a one-dimensional Micro-Mirror Array actuated by an electrostatic force. We present results obtained through numerical simulations of a single cell: the analysis and the optimization of the pull-in voltage and the analysis of the bounces of the mirror in contact with the base when it is subjected to a voltage exceeding the pull-in voltage...
We design finite antenna arrays for far-field sensing at multiple wavelengths, under two design paradigms. The first design paradigm is optimized for collection of measurements at multiple wavelengths, fusing these together for joint inference over an underlying scene. The second design paradigm is robust, in a sense that it is guaranteed to allow good inference over the scene at any one single wavelength...
With the augmented penetration of renewable energy, such as solar power and wind power, the electricity grids could be destabilizing due to the intermittent nature of renewable sources. In order to ensure power system reliability, robust optimization method is introduced to the energy schedule of micro grid system. This work presented a two-stage robust optimization method to calculate a numerical...
This paper aims at presenting the new 2-stage framework of Robust Optimization for Lean Supply Chain design under uncertainty by using the so-called Dual Lean Filter. First, we formulate one quantitative model of Fat Supply Chain in stable circumstance based on the six-performance drivers of Chopra and Meindl, (2013). Then, we propose one novel procedure called Forward Lean Filter in order to transform...
This paper presents a robust and optimal operation tracking Energy Management System (EMS) for Mobile Base Transceiver Station (BTS) Microgrid equipped with Battery, PV panels and Diesel Engine Generator (DEG) for unreliable grid. The contribution is particularly focused on minimizing the DEG fuel (with DEG ON/OFF frequency) at the time of power-grid outage (i.e. Blackout). The EMS is designed to...
In the deregulated electricity market, wind power producers (WPPs) are required to submit their generation profile in the day-ahead (DA) market. The consideration of uncertainties associated with price and wind power become crucial to facilitate decision making and risk hedging for WPPs. In this paper, a bidding strategy based on robust optimization is proposed under two trading floors, namely DA...
For a multi-objective optimization problem applied to the electric machine design, a new robust surrogate-assisted algorithm is proposed in this research. The proposed algorithm can find a robust and well-distributed Pareto front set rapidly and precisely for robust nondominated solutions by using a kriging surrogate model and an uncertainty consideration with worst case scenario. The outstanding...
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