Strategy research of used cars in online sequential auction based on fuzzy theory

2020 ◽  
pp. 1-11
Author(s):  
Zhou Ke ◽  
Ma Gang ◽  
Wang Yafei ◽  
Zheng Junjun ◽  
Wang Shilei ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Theory ◽  
Optimal Strategies ◽  
Online Auction ◽  
Fuzzy Simulation ◽  
Strategy Research ◽  
Sequential Auction ◽  
Optimal Function ◽  
Used Cars ◽  
Mean Variance

With the development of “Internet+”, online auction platforms of used cars have emerged a lot. As a typical representative of the continuous purchase environment, online sequential auction of used cars faces many uncertainties, including uncertain revenue and risk. To describe them, adopting fuzzy theory to create mean-variance model to estimate the revenue and risk is showed in this paper. Moreover, three types of sellers, aggressive, conservative and rational sellers are analyzed respectively, and strategy models are built, where the multi-criteria optimal function for the latter one is adapted Cobb-Douglas production function. Then, a genetic algorithm based on fuzzy simulation is proposed through integrating the fuzzy simulation and 0-1 genetic algorithm, which can solve the models validly. Lastly, the practical example from Guazi website shows the optimal strategies derived by models can meet sellers’ demands, especially goals of both higher revenue and lower risk for rational sellers, which proves practicability of the model and validity of algorithm.

scholarly journals Cable Tension Adjustment Based upon Fuzzy Theory and Genetic Algorithm.

2000 ◽  
pp. 143-151
Author(s):  
Masakatsu KANEYOSHI ◽  
Hitoshi FURUTA ◽  
Hiroshi TANAKA
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Theory ◽  
Cable Tension

Transformer Fault Diagnosis Based on Improved Quantum Genetic Algorithm and BP Network

2010 ◽  
Vol 29-32 ◽  
pp. 1543-1549 ◽  
Author(s):  
Jie Wei ◽  
Hong Yu ◽  
Jin Li
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Fault Diagnosis ◽  
Bp Neural Network ◽  
Fuzzy Theory ◽  
Back Propagation ◽  
Gas Analysis ◽  
Bp Network ◽  
Quantum Genetic Algorithm ◽  
Transformer Fault

Three-ratio of the IEC is a convenient and effective approach for transformer fault diagnosis in the dissolved gas analysis (DGA). Fuzzy theory is used to preprocess the three-ratio for its boundary that is too absolute. As the same time, an improved quantum genetic algorithm IQGA (QGASAC) is used to optimize the weight and threshold of the back propagation (BP). The local and global searching ability of the QGASAC approach is utilized to find the BP optimization solution. It can overcome the slower convergence velocity and hardly getting the optimization of the BP neural network. So, aiming at the shortcoming of BP neural network and three-ratio, blurring the boundary of the gas ratio and the QGASAC algorithm is introduced to optimize the BP network. Then the QGASAC-IECBP method is proposed in this paper. Experimental results indicate that the proposed algorithm in this paper that both convergence velocity and veracity are all improved to some extent. And in this paper, the proposed algorithm is robust and practical.

scholarly journals A Bank Credit Model with Capital-Constrained Newsvendor Under Two Ordering Opportunities

2016 ◽  
Vol 4 (5) ◽  
pp. 408-418 ◽  
Author(s):  
Deli Zhao ◽  
Baofeng Zhang ◽  
Zongshui Wang
Keyword(s):  
Interest Rate ◽  
Capital Market ◽  
Optimal Strategies ◽  
Mathematic Model ◽  
Bank Credit ◽  
Order Quantity ◽  
Financing System ◽  
Primary Order ◽  
Mean Variance ◽  
Variance Criterion

AbstractThis paper proposes a financing system consisting of a bank under Mean-Variance criterion and a capital-constrained retailer, where the bank offers an unlimited credit to the retailer. The demand is assumed to be stochastic. The newsvendor is allowed to make an emergency order with a minimum reorder quantity threshold (RQT). It shows that under RQT, the newsvendor has different reorder strategies. The optimal primary order quantity and interest rate are derived, sequentially. Extension under perfectly competitive capital market is given. The mathematic model reveals that RQT and reorder price have significant effect on the optimal strategies.

scholarly journals High-frequency trading with fractional Brownian motion

2020 ◽  
Author(s):  
Paolo Guasoni ◽  
Yuliya Mishura ◽  
Miklós Rásonyi
Keyword(s):  
Brownian Motion ◽  
Fractional Brownian Motion ◽  
High Frequency ◽  
Asset Price ◽  
Optimal Strategies ◽  
Trading Costs ◽  
Frequency Limit ◽  
Dynamic Optimisation ◽  
High Frequency Limit ◽  
Mean Variance

Abstract In the high-frequency limit, conditionally expected increments of fractional Brownian motion converge to a white noise, shedding their dependence on the path history and the forecasting horizon and making dynamic optimisation problems tractable. We find an explicit formula for locally mean–variance optimal strategies and their performance for an asset price that follows fractional Brownian motion. Without trading costs, risk-adjusted profits are linear in the trading horizon and rise asymmetrically as the Hurst exponent departs from Brownian motion, remaining finite as the exponent reaches zero while diverging as it approaches one. Trading costs penalise numerous portfolio updates from short-lived signals, leading to a finite trading frequency, which can be chosen so that the effect of trading costs is arbitrarily small, depending on the required speed of convergence to the high-frequency limit.

Evolution of Hunter–Gatherer Strategies with a Genetically Inspired Algorithm

1998 ◽  
Vol 09 (04) ◽  
pp. 547-554 ◽  
Author(s):  
Pat Sutton ◽  
A. Georgallas ◽  
D. L. Hunter ◽  
N. Jan ◽  
R. J. Nash ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Optimal Strategy ◽  
Point Mutations ◽  
Optimal Strategies ◽  
Resource Exploitation

We address the following: Are there several optimal strategies for a hunter-gatherer society in a given environment, in which the society has an evolving level of technology and/or skills? We use the Genetic Algorithm, with point mutations, to facilitate the search for these strategies. We find that, in a generous environment, several optimal strategies are possible; there is no unique optimal strategy. We are now in a position, with the Genetic Algorithm, to assess different approaches to resource exploitation and the role of contingency.

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