Search | Engineering

Subscribe Submit

Home Journals Focus Achievement Fronts About Us 中文版

Resource Type

Journal Article 3

Year

2022 2

2017 1

Keywords

contract design 1

energy storage right 1

governance 1

improved ant colony algorithm 1

inequity aversion 1

loss aversion 1

node price fluctuation 1

portfolio 1

public project 1

reverse auction 1

risk aversion 1

risk sharing 1

transmission right 1

winner determination 1

open ︾

Search scope:

排序： Display mode:

Optimal risk allocation in alliance infrastructure projects: A social preference perspective

Xiang DING, Qian LI

Frontiers of Engineering Management 2022, Volume 9, Issue 2, Pages 326-336 doi: 10.1007/s42524-020-0145-x

Abstract: This study presents a quantitative approach based on modeling alliance member (AM)’s inequity aversionFehr and Schmidt’s inequity-aversion model is integrated into modeling partner’s utility.

Keywords： public project contract design risk sharing inequity aversion governance

HTML PDF Collect

Optimal portfolio design of energy storage devices with financial and physical right market

Frontiers in Energy 2022, Volume 16, Issue 1, Pages 95-104 doi: 10.1007/s11708-021-0788-2

Abstract: Pennsylvania-New Jersey-Maryland (PJM) electric power spot market, and the comparison between the risk aversion

Keywords： portfolio node price fluctuation transmission right energy storage right risk aversion

HTML PDF Collect

Winner determination problem with loss-averse buyers in reverse auctions

Xiaohu QIAN, Min HUANG, Yangyang YU, Xingwei WANG

Frontiers of Engineering Management 2017, Volume 4, Issue 2, Pages 212-220 doi: 10.15302/J-FEM-2017019

Abstract: Reverse auctions have been widely adopted for purchasing goods and services. This paper considers a novel winner determination problem in a multiple-object reverse auction in which the buyer involves loss-averse behavior due to uncertain attributes. A corresponding winner determination model based on cumulative prospect theory is proposed. Due to the NP-hard characteristic, a loaded route strategy is proposed to ensure the feasibility of the model. Then, an improved ant colony algorithm that consists of a dynamic transition strategy and a Max-Min pheromone strategy is designed. Numerical experiments are conducted to illustrate the effectiveness of the proposed model and algorithm. We find that under the loaded route strategy, the improved ant colony algorithm performs better than the basic ant colony algorithm. In addition, the proposed model can effectively characterize the buyer’s loss-averse behavior.

Keywords： reverse auction loss aversion winner determination improved ant colony algorithm