A hybrid optimization strategy for the maintenance of the wheels of metro vehicles: Vehicle turning, wheel re-profiling, and multi-template use

2017 ◽  
Vol 232 (3) ◽  
pp. 832-841 ◽  
Author(s):  
Wei Zhu ◽  
Di Yang ◽  
Jun Huang
Keyword(s):  
Optimal Solution ◽  
Hybrid Optimization ◽  
Optimization Approach ◽  
Optimization Strategy ◽  
Wheel Wear ◽  
Rail Systems ◽  
Common Strategy ◽  
Shanghai Metro ◽  
Open Nature

The wheel–rail contact relationship has a great impact on the security and reliability of metro vehicles in service. In particular, wear modeling and maintenance optimization of the wheels play significant roles with regard to both safety and cost. However, it is difficult to provide a satisfactory model of wheel wear because of the open nature of real wheel–rail systems and the constantly varying environmental conditions in which they operate. Historically, re-profiling, which also has its limitation to some extent, was adopted as a common strategy to restore the original profiles of the worn wheels. Acknowledging that re-profiling is not the only strategy for dealing with wheel wear, the authors of this study have developed a more advanced optimization approach that includes two more strategies, namely, vehicle turning and multi-template use, to give as near an optimal solution as possible. Vehicle turning refers to the reversal of the vehicle’s orientation on the rail, whereas multi-template use refers to the situation where different re-profiling templates are used alternately. In this paper, re-profiling, vehicle turning, and multi-template use have been discussed separately. Then a hybrid optimization strategy for the maintenance of the wheels of metro vehicles has been proposed, with the aim of maximizing the wheel life while minimizing the relevant costs. An initial case study on the Shanghai Metro system shows that the proposed approach is able to provide a more reasonable solution for the optimization of the maintenance strategies.

Improved similarity measure in case-based reasoning: a case study of construction cost estimation

2019 ◽  
Vol 27 (2) ◽  
pp. 561-578 ◽  
Author(s):  
Won-Gil Hyung ◽  
Sangyong Kim ◽  
Jung-Kyu Jo
Keyword(s):  
Cost Estimation ◽  
Hybrid Approach ◽  
Optimal Solution ◽  
Case Based Reasoning ◽  
Optimization Approach ◽  
Cost Information ◽  
Planning Stage ◽  
Content Type ◽  
Case Based

Purpose Applied a hybrid approach using genetic algorithms (GAs) for a case-based retrieval process in order to increase the overall improved cost accuracy for a case-based library. The paper aims to discuss this issue. Design/methodology/approach A weight optimization approach using case-based reasoning (CBR) with proposed GAs for developing the CBR model. GAs are used to investigate optimized weight generation with an application to real project cases. Findings The proposed CBR model can reduce errors consistently, and be potentially useful in the early financial planning stage. The authors suggest the developed CBR model can provide decision-makers with accurate cost information for assessing and comparing multiple alternatives in order to obtain the optimal solution while controlling cost. Originality/value The system can operate with more accuracy or less cost, and CBR can be used to better understand the effects of factor interaction and variation during the developed system’s process.

A MultiDisciplinary Optimization Approach for Sizing Vertical Lift Aircraft

2021 ◽  
Author(s):  
Ananth Sridharan ◽  
Bharath Govindarajan
Keyword(s):  
Optimal Solution ◽  
Multidisciplinary Optimization ◽  
Shape Design ◽  
Optimization Approach ◽  
Optimization Strategy ◽  
Clock Time ◽  
Element Analysis ◽  
Analysis And Design ◽  
Design Variables ◽  
Vertical Lift

This paper presents an approach to reframe the sizing problem for vertical-lift unmanned aerial vehicles (UAVs) as an optimization problem and obtains a weight-optimal solution with up to two orders of magnitude of savings in wall clock time. Because sizing is performed with higher fidelity models and design variables from several disciplines, the Simultaneous Analysis aNd Design (SAND) approach from fixed-wing multidisciplinary optimization literature is adapted for the UAV sizing task. Governing equations and disciplinary design variables that are usually self-contained within disciplines (airframe tube sizes, trim variables, and trim equations) are migrated to the sizing optimizer and added as design variables and (in)equality constraints. For sizing consistency, the iterative weight convergence loop is replaced by a coupling variable and associated equality consistency constraint for the sizing optimizer. Cruise airspeed is also added as a design variable and driven by the sizing optimizer. The methodology is demonstrated for sizing a package delivery vehicle (a lift-augment quadrotor biplane tailsitter) with up to 39 design variables and 201 constraints. Gradient-based optimizations were initiated from different starting points; without blade shape design in sizing, all processes converged to the same minimum, indicating that the design space is convex for the chosen bounds, constraints, and objective function. Several optimization schemes were investigated by moving combinations of relevant disciplines (airframe sizing with finite element analysis, vehicle trim, and blade aerodynamic shape design) to the sizing optimizer. The biggest advantage of the SAND strategy is its scope for parallelization, and the inherent ability to drive the design away from regions where disciplinary analyses (e.g., trim) cannot find a solution, obviating the need for ad hoc penalty functions. Even in serial mode, the SAND optimization strategy yields results in the shortest wall clock time compared to all other approaches.

scholarly journals Hybrid optimization design approach of asymmetric base-isolation coupling system for twin buildings

2021 ◽  
pp. 146134842199296
Author(s):  
Wonsuk Park ◽  
Seung-Yong Ok
Keyword(s):  
Vibration Control ◽  
Optimization Design ◽  
Base Isolation ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Hybrid Optimization ◽  
Optimization Approach ◽  
Efficient Design ◽  
Coupling System ◽  
Twin Buildings

This study proposes a new configuration of asymmetric base-isolation coupling system for the vibration control of twin buildings, and also presents an efficient design method of using a hybrid optimization technique integrated with preference-based dimensionality reduction technique. The purpose of the proposed optimization approach is to guarantee the compromise optimal solution of well-balancing the mutually conflicting design objectives. In order to demonstrate the proposed approach, the adjacent 20-story twin buildings subjected to earthquake excitations were adopted as target buildings and it was verified through numerical examples that the proposed optimization technique can successfully find the optimal solution to achieve various design objectives in a balanced manner. The seismic performance was also compared with the existing different-story connection system with uniform distribution of dampers. The comparative results of the seismic performances between two systems clearly demonstrate that the proposed system can achieve great performance improvement over the existing system while maintaining balanced design preferences. Thus, it can be concluded that the proposed system can be a very effective system for the vibration control problem of the twin buildings.

scholarly journals Integrated Urban Energy Planning: A Case-Study Using Optimization

2021 ◽  
Author(s):  
Jingbo Guo ◽  
Côme Bissuel ◽  
Francois Courtot
Keyword(s):  
Energy Demand ◽  
High Efficiency ◽  
Optimal Solution ◽  
Energy Planning ◽  
Optimization Approach ◽  
Energy Prices ◽  
Renewable Energy Resources ◽  
Planning Optimization ◽  
Urban Energy

This article describes an integrated energy planning optimization case-study. Starting from an integrated urban energy planning practice based on the urban planning information, an optimization approach is implemented to support decisions on suitable energy structures. Based on a use-case, energy demand, renewable energy resources, energy policy and energy prices are analyzed and set as inputs of the optimization. The results are energy structures minimizing the cost for two separated zones. Meanwhile, under different scenarios, in terms of renewable ratio targets and thermal storage, comparison is made for illustrating economy differences. The optimization mentioned in the article is modelled as a Mixed-Integer Linear Programming problem, which can search the optimal solution with high efficiency among the possible system designs.

scholarly journals A Dynamic Optimization Strategy for the Operation of Large Scale Seawater Reverses Osmosis System

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Aipeng Jiang ◽  
Jian Wang ◽  
Wen Cheng ◽  
Changxin Xing ◽  
Shu Jiangzhou
Keyword(s):  
Finite Element ◽  
Dynamic Model ◽  
Large Scale ◽  
Optimal Solution ◽  
Differential Algebraic Equations ◽  
Optimal Operation ◽  
Algebraic Equations ◽  
Optimization Strategy ◽  
Storage Tanks

In this work, an efficient strategy was proposed for efficient solution of the dynamic model of SWRO system. Since the dynamic model is formulated by a set of differential-algebraic equations, simultaneous strategies based on collocations on finite element were used to transform the DAOP into large scale nonlinear programming problem named Opt2. Then, simulation of RO process and storage tanks was carried element by element and step by step with fixed control variables. All the obtained values of these variables then were used as the initial value for the optimal solution of SWRO system. Finally, in order to accelerate the computing efficiency and at the same time to keep enough accuracy for the solution of Opt2, a simple but efficient finite element refinement rule was used to reduce the scale of Opt2. The proposed strategy was applied to a large scale SWRO system with 8 RO plants and 4 storage tanks as case study. Computing result shows that the proposed strategy is quite effective for optimal operation of the large scale SWRO system; the optimal problem can be successfully solved within decades of iterations and several minutes when load and other operating parameters fluctuate.

Hybrid Simulation-Based Optimization for Production Planning of a Dedicated Remanufacturing System

2021 ◽  
Vol 12 (3) ◽  
pp. 53-79
Author(s):  
Navee Chiadamrong ◽  
Chayanan Tangchaisuk
Keyword(s):  
Hybrid Simulation ◽  
Hybrid Optimization ◽  
Optimization Approach ◽  
Swarm Optimization ◽  
Multiple Products ◽  
Decision Variables ◽  
Simulation Based ◽  
Simulation Based Optimization ◽  
Two Hybrid

This paper presents a comparative simulation study of a dedicated remanufacturing system. The production line of a dedicated remanufacturing system producing multiple products under uncertain environment is improved through the simulation-based optimization approach. Appropriate inventory capacity of buffers, a proper switching rule, and a suitable run size of each product should be optimally set to yield the highest system's profit. Then, hybrid simulation-based optimization algorithms with two hybrid optimization forms using a Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) as complementary to each other in relation to their standard algorithms are proposed and compared. A case study is used to demonstrate and compare the performances among the algorithms to show the advantages of the proposed algorithms. This approach can assist in decision making for the planning and management of dedicated remanufacturing systems that are required to operate with various decision variables under uncertainties.

scholarly journals Stochastic Models for Optimizing Availability, Cost and Sustainability of Data Center Power Architectures through Genetic Algorithm

2019 ◽  
Vol 26 (2) ◽  
pp. 27-44
Author(s):  
Márcio Sergio Soares Austregésilo ◽  
Gustavo Callou
Keyword(s):  
Genetic Algorithm ◽  
Case Studies ◽  
Data Center ◽  
Electric Energy ◽  
Optimal Solution ◽  
Stochastic Petri Nets ◽  
Optimization Approach ◽  
Optimization Strategy ◽  
Electric Energy Consumption ◽  
Typical Data

In recent years, the growth of information technology has required higher reliability, accessibility, collaboration, availability, and a reduction of costs on data centers due to factors such as social network, cloud computing, and e-commerce. These systems require redundant mechanisms on the data center infrastrucutre to achieve high availability, which may increase the electric energy consumption, impacting in both the sustainability and cost. This work proposes a multi-objective optimization approach, based on Genetic Algorithms, to optimize cost, sustainability and availability of data center power infrastructures. The main goal is to maximize availability and minimize cost and exergy consumed (adopted to estimate the environmental impacts). In order to compute such metrics, this work adopts the energy flow model (EFM), reliability block diagrams (RBD) and stochastic petri nets (SPN). Two case studies are conducted to show the applicability of the proposed strategy: (i) takes into account 5 typical data center architectures that were optimized to conduct the validation process of the proposed strategy; (ii) uses the optimization strategy in two architectures classified by ANSI / TIA-942 (TIER I and II). In both case studies, significant improvements were achieved in the results, which were very close to the optimum one that was obtained by a brute force algorithm that analyzes all the possibilities and returns the optimal solution. It is worth mentioning that the time used to obtain the results using the genetic algorithm approach was significantly lower (6,763,260 times), in comparison with the strategy which combines all the possible combinations to obtain the optimal result.

scholarly journals Hybrid Trajectory Optimization Method and Tracking Guidance for Variable-Sweep Missiles

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Zhifang Wei ◽  
Yang Cheng ◽  
Xiangxiang Guo ◽  
Senlin Liu
Keyword(s):  
Trajectory Optimization ◽  
Pseudospectral Method ◽  
Linear Quadratic Regulator ◽  
Attack Angle ◽  
Hybrid Optimization ◽  
Optimization Approach ◽  
Optimization Strategy ◽  
Linear Quadratic ◽  
Sweep Angle ◽  
The Impact

In this paper, an offline hybrid trajectory optimization approach is proposed for variable-sweep missiles to explore the superiority in the diving phase. Aiming at the maximal terminal velocity with the impact angle constraint, the trajectory optimization model is formulated under multiple constraints, and the aerodynamic analysis in different sweep angles is discussed. Unlike only the attack angle used for the optimization process traditionally, the two-variable optimization scheme on both the attack angle and sweep angle is investigated for variable-sweep missiles. Then, the trajectory optimization problem is transformed into the nonlinear programming problem via a hybrid optimization strategy combining the Gauss pseudospectral method and direct shooting method to obtain the high precision and fast convergence solution. Finally, to verify the feasibility of the optimal trajectory under uncertainties, the tracking guidance law is designed on basis of the gain scheduled linear quadratic regulator control. Numerical simulation results reveal not only of the proposed hybrid optimization strategy but also of the superiority of variable-sweep missiles compared with traditional missiles.

Hybrid optimization strategy beyond local optima in aerospace panel designs

AIAA Journal ◽  
1999 ◽  
Vol 37 ◽  
pp. 588-593
Author(s):  
K. L. Chan ◽  
David Kennedy ◽  
Fred W. Williams
Keyword(s):  
Hybrid Optimization ◽  
Optimization Strategy ◽  
Local Optima
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