Papers by Keyword: Robust Optimization

Abstract: We consider the problem of finding the optimal shape of a force-sensing element which is integrated into a tubular structure. The goal is to make the sensor element sensitive to specific forces and insensitive to other forces. The problem is stated as a PDE-constrained minimization program with both nonconvex objective and nonconvex constraints. The optimization problem depends on uncertain parameters, because the manufacturing process of the structures underlies uncertainty, which causes unwanted deviations in the sensory properties. In order to maintain the desired properties of the sensor element even in the presence of uncertainty, we apply a robust optimization method to solve the uncertain program.The objective and constraint functions are continuous but not differentiable with respect to the uncertain parameters, so that existing methods for robust optimization cannot be applied. Therefore, we consider the nonsmooth robust counterpart formulated in terms of the worst-case functions, and show that subgradients can be computed efficiently. We solve the problem with a BFGS--SQP method for nonsmooth problems recently proposed by Curtis, Mitchell and Overton.

Abstract: In this article, we propose a nonlinear semidefinite program (SDP) for the robust trusstopology design (TTD) problem with beam elements. Starting from the semidefinite formulation ofthe robust TTD problem we derive a stiffness matrix that can model rigid connections between beams.Since the stiffness matrix depends nonlinearly on the cross-sectional areas of the beams, this leads toa nonlinear SDP. We present numerical results using a sequential SDP approach and compare them toresults obtained via a general method for robust PDE-constrained optimization applied to the equationsof linear elasticity. Furthermore, we present two mixed integer semidefinite programs (MISDP), onefor the optimal choice of connecting elements, which is nonlinear, and one for the correspondingproblem with discrete cross-sectional areas.

Abstract: The strain energy of dam body and its sensitivity to the deformation modulus of foundation are taken as objective functions, feasibility robust constraint of stress is taken into account with the consideration of uncertainty of foundation deformation modulus, and a robust optimization model for shape design of arch dams is established based on strain energy. A formula of sensitivity of dam strain energy to deformation modulus of foundation is derived and a relevant algorithm is proposed. The optimization of a planned arch dam indicates that, the dam strain energy and its sensitivity to foundation deformation modulus of optimal design are reduced 2.29% and 15.51%, respectively, of that of initial design, and the validity of the proposed model is demonstrated.

Abstract: The paper presents an optimization by using the robust engineering approach, for the optimization of the deep drilling process by assessing the surface roughness by the R_a parameter. The trials were developed according with the Robust Engineering principles, by applying the Taguchi Method. The parameter for decision is the average profile height (Ra) of the roughness. Finally, there are presented solutions for the setting-up the deep drilling parameters levels in such a way to assure the best quality at the level of the generated surface. The method results to be reliable for being applied for achieving the optimal setup machining parameters used for the deep drilling process.

Abstract: Considering the uncertainty of waste electronic recovery quantity in consumption areas and recycling rate in dismantling centers, a robust optimization model for single-cycle waste electronic recycling network with capacity constraints is established to determine the number and location of the facilities, the flows between each facility. A numerical example is provided to demonstrate the feasibility of the model.

Abstract: In steam power system optimal problems, uncertain parameters should be considered unless the solution will be infeasible. The uncertain parameters and constraints in steam power system optimization model are analyzed. Then the related constraints with uncertain parameters which used to be expressed by joint chance constraints are approximated, and a robust optimization model of steam power system is proposed. The simulation results illustrate the validity of the model.

Abstract: Traditional supply chain theory often assumes perfect alignment between system inventory and actual inventory. However, inventory information is usually inaccurate due to many reasons in practice. We hereby describe an expended newsvendor model with inventory inaccuracy who wants to remove this negative effect by investing RFID system. By analyzing the best respond to market factors (commodity availability caused by inventory inaccuracy and tag price of RFID), we generate the optimal order quantity of newsvendor (retailer in this paper) and his minimal regret value. Unlike other paper describing uncertain parameters with probability function, we use only upper limit and lower limits to display demand. We adopt robust deviation criterion to minimize the absolute regret and treat it as the determine principle. Finally, we achieve a result that when commodity availability or tag price meets some specific conditions, investing RFID can be rather profitable.Keywords: inventory inaccuracy, robust optimization, RFID technology

Abstract: Considering the uncertainty of recovery and remanufacturing productivity rates in the reverse logistics remanufacturing process, we describe it by adopting the discrete scenarios of non-probabilistic and establish a multi-objective remanufacturing reverse logistics LRP robust model based on the NPRO.Lingo10 is used to solve the specific example, and then compared with the optimization values of objective function under the corresponding certain environment. The results verify the robustness of the model.

Abstract: Due to wind resources distribution characteristics and current situation of power grid, wind power is mainly large-scaled and centralized developed in China. In order to meet the security requirements of power system under this circumstance, a real-time security constrained dispatch method considering the impact of wind power uncertainty on N-1 line contingency safety is proposed. Key N-1 line contingency security constraints are identified by sensitivity analysis and added into dispatching model. Robust optimization approach is employed to solve this optimal problem. Simulation results of the IEEE-30 nodes power system validated the rationality and feasibility of the proposed method.

Abstract: This paper examines optimization of revenue of power plants facing stochastic demand with varied prices. A network optimization model is proposed for power plant revenue management under an uncertain environment. The network optimization has a stochastic programming formulation designed to capture the randomness of the unknown demand. A novel approach of robust optimization and PSO are applied to solve the problem on a scenario-basis. Decision-makers risk aversion is considered in the objective function. Mean absolute value is used to measure risk of deviation of revenue from its expected value.