检索结果-内蒙古大学图书馆

A novel multi-objective bi-level programming problem under intuitionistic fuzzy environment and its application in production planning problem

引用

COMPLEX & INTELLIGENT SYSTEMS 2022年第4期8卷 3263-3278页

作者： Singh, V. P. Sharma, Kirti Chakraborty, Debjani Ebrahimnejad, Ali Visvesvaraya Natl Inst Technol Nagpur Dept Math Nagpur 440010 Maharashtra India Indian Inst Technol Kharagpur Dept Math Kharagpur 721302 W Bengal India Islamic Azad Univ Dept Math Qaemshahr Branch Qaemshahr Iran

This paper presents an optimization method to solve a multi-objective model of a bi-level linear programming problem with intuitionistic fuzzy coefficients. The idea is based on TOPSIS (technique for order preference by similarity to ideal solution) method. TOPSIS method is a multiple criteria method that identifies a satisfactory solution from a given set of alternatives based on the minimization of distance from an ideal point and maximization of distance from the nadir point simultaneously. A new model of multi-objective bi-level programming problem in an intuitionistic fuzzy environment has been considered. The problem is first reduced to a conventional multi-objective bi-level linear programming problem using accuracy function. Then the modified TOPSIS method is proposed to solve the problem at both the leader and the follower level where various linear/non-linear membership functions are used to represent the flexibility in the approach of decision-makers (DMs). The problem is solved hierarchically, i.e., first the problem at the leader level is solved and then the feasible region is extended by relaxing the decision variables controlled by the leader. The feasible region is extended to obtain a satisfactory solution for the DMs at both levels. Finally, the application of the proposed approach in the production planning of a company has been presented. An illustrative numerical example is also given to explain the methodology defined in this paper.

关键词： Multi-objective optimization problem bi-level programming problem TOPSIS method Intuitionistic fuzzy number Fuzzy optimization

来源：评论

学校读者我要写书评

暂无评论

Charging/Discharging strategy for electric vehicles based on bi-level programming problem: San Francisco case study 14

Charging/Discharging strategy for electric vehicles based on...

引用

14th IEEE International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG)

作者： Tookanlou, M. Bagheri Marzband, M. Kyyra, J. Al Sumaiti, A. Al Hosani, K. Northumbria Univ Dep Math Phys & Elect Engn Newcastle Upon Tyne Tyne & Wear England Aalto Univ Dept Elect Engn & Automat Helsinki Finland Khalifa Univ Dept Elect Engn & Comp Sci Adv Power & Energy Ctr Dhabi U Arab Emirates

ISBN: (数字)9781728142180

ISBN: (纸本)9781728142180

The increasing market share of electric vehicles (EVs) leads to determine a proper strategy for charging/discharging EV batteries such that rewards of all agents including EV charging stations (EVCSs) and EV owners (EVOs) that participate in charging/discharging EV batteries are guaranteed. In this study, an economical and technical strategy is developed. It focuses on finding proper EVCSs by EVOs and determining optimal day-ahead electricity prices traded between all agents such that the rewards of EVCSs and EVOs are met simultaneously. This optimal charging/discharging decision making and optimal day-ahead electricity prices are determined by bi-level programming problem (BLPP). The outer level corresponds to the optimization problem of EVCSs and the inner level belongs to EVOs. Salp swarm optimization (SSO) algorithm is utilized to solve BLPP. Based on determination of minimum distance travelled by EVOs and optimal day-ahead electricity prices offered by EVCSs, the rewards of EVCSs and EVOs are analysed during charging/discharging period. For simulation purposes, a case study based on San Francisco in US is presented to visualize and validate the modelling results. Six EVCSs are installed in San Francisco for charging/discharging 247 EVs during 24 hours of a typical day. Simulation results show that under implementing the proposed charging/discharging strategy, the total cost of EVOs decreases by 17.8% and total revenue of EVCSs increases 18.2%, in comparison with not considering the proposed strategy.

关键词： bi-level programming problem charging/discharging decision electric vehicles electricity pricing

来源：评论

学校读者我要写书评

暂无评论

A Double Layer Neural Network Based on Artificial Bee Colony Algorithm for Solving Quadratic bi-level programming problem 8th

A Double Layer Neural Network Based on Artificial Bee Colony...

引用

8th KES International Conference on Intelligent Decision Technologies (KES-IDT)

作者： Watada, Junzo Ding, Haochen Waseda Univ Grad Sch Informat Prod & Syst Wakamatsu Ku 2-7 Hibikino Kitakyushu Fukuoka 8080135 Japan

ISBN: (纸本)9783319396309;9783319396293

In this study, we formulate a double layer neural network based hybrid method to solve the quadratic bi-level programming problem. Our proposed algorithm comprises an improved artificial bee colony algorithm, a Hopfield network, and a Boltzmann machine in order to effectively and efficiently solve such problems. The improved artificial bee colony algorithm is developed for dealing with the upper level problem. The experiment results indicate that compared with other methods, the proposed double layer neural network based hybrid method is capable of achieving better optimal solutions for the quadratic bi-level programming problem.

关键词： bi-level programming problem Double layer neural networks Artificial bee colony algorithm

来源：评论

学校读者我要写书评

暂无评论

A Hierarchical Wind Driven Optimization Method for Solving the bi-level programming problem

A Hierarchical Wind Driven Optimization Method for Solving t...

引用

International Conference on Logistics, Informatics and Service Sciences (LISS)

作者： Xu, Lan Teng, Wei Jiangsu Univ Sci & Technol Sch Econ & Management Zhenjiang Jiangsu Peoples R China

ISBN: (纸本)9781509011025

A hierarchical wind driven optimization (WDO) method is proposed to solve the bi-level programming problem. Firstly, the WDO method is used to optimize the lower level programming problem after the upper level variables are initialized, and the positions and velocities of air parcels in the lower level are updated. Then the solutions of the upper level are optimized by the WDO method with the constrained conditions. Finally, the solutions with the minimum sum of sequences of the two-level results are selected as the final solution from the solution set. The experimental results of the proposed algorithm show the effectiveness of the proposed hierarchical wind driven optimization for solving the bi-level programming problems.

关键词： Wind driven optimization bi-level programming problem Constrained optimization

来源：评论

学校读者我要写书评

暂无评论

Hybrid particle swarm optimization and differential evolution algorithm for bi-level programming problem and its application to pricing and lot-sizing decisions

引用

JOURNAL OF INTELLIGENT MANUFACTURING 2015年第3期26卷 471-483页

作者： Ma, Weimin Wang, Miaomiao Zhu, Xiaoxi Tongji Univ Sch Econ & Management Shanghai 200092 Peoples R China

This paper proposes a hierarchical hybrid particle swarm optimization (PSO) and differential evolution (DE) based algorithm (HHPSODE) to deal with bi-level programming problem (BLPP). To overcome the shortcomings of basic PSO and basic DE, this paper improves PSO and DE, respectively by using a velocity and position modulation method in PSO and a modified mutation strategy in DE. HHPSODE employs the modified PSO as a main program and the modified DE as a subprogram. According to the interactive iterations of modified PSO and DE, HHPSODE is independent of some restrictive conditions of BLPP. The results based on eight typical bi-level problems demonstrate that the proposed algorithm HHPSODE exhibits a better performance than other algorithms. HHPSODE is then adopted to solve a bi-level pricing and lot-sizing model proposed in this paper, and the data is used to analyze the features of the proposed bi-level model. Further tests based on the proposed bi-level model also exhibit good performance of HHPSODE in dealing with BLPP.

关键词： bi-level programming problem Hierarchical Particle swarm optimization Differential evolution Pricing and lot-sizing

来源：评论

学校读者我要写书评

暂无评论

Flexibility resource planning of a power system considering a flexible supply-demand ratio

引用

FRONTIERS IN ENERGY RESEARCH 2023年 11卷

作者： Zhang, Xiaotian Lu, Mingxuan Li, Hua Gao, Fengxi Zhong, Chongfei Qian, Xiaoyi State Grid Liaoning Econ Res Inst Shenyang Peoples R China Shenyang Inst Engn Shenyang Peoples R China

Aiming at the problems of insufficient power system regulation capacity and lack of flexible resources caused by source-load uncertainty, the flexible resource planning of power systems is studied with the goal of improving flexibility. Uncertainty and flexibility are combined in this article, and a probability index of an insufficiently flexible supply-demand ratio is proposed based on the probability characteristics of flexibility. A bi-level programming model of power system flexibility resources considering the probability of an insufficiently flexible supply demand ratio is constructed. Optimal economics is used as the objective function of the planning layer, and the proposed minimum probability index of the flexible supply-demand ratio is used as the objective function of the operations layer. Economics and flexibility are studied, taking the power system in a certain area in Northeast China as the research object. A flexible resource planning scheme that meets different flexibility expectations is obtained, and the scheme is discussed in detail from the aspects of system flexibility, economic cost, and new energy consumption capacity. The effectiveness of quantitative indicators and planning methods are verified.

关键词： power system uncertainty flexibility bi-level programming problem supply-demand ratio

来源：评论

学校读者我要写书评

暂无评论

Coordination of wind power producers with an energy storage system for the optimal participation in wholesale electricity markets

引用

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2022年 136卷 107672-107672页

作者： Dadashi, Mojtaba Zare, Kazem Seyedi, Heresh Shafie-khah, Miadreza Univ Tabriz Fac Elect & Comp Engn Tabriz Iran Univ Vaasa Sch Technol & Innovat Vaasa Finland

The optimal participation of wind-based power resources within electricity markets confronts serious challenges due to the inherent uncertainty of wind speed. Accordingly, these units are forced to make take-or-pay contracts that are typically lower than market-clearing prices. Hence, wind power plants are not able to obtain the maximum possible amount of profit. One of the most promising solutions to deal with this matter is the coordination of wind-based units with flexible resources like energy storage systems. Therefore, this study presents a novel offering strategy of multiple Wind Producers (WPs) coordinated with a Battery Energy Storage System (BESS) in the form of a strategic Virtual Power Plant (VPP). To this end, a bi-level programming framework is proposed in which the VPP's expected profit is maximized at the upper-level (UL) through solving a two-stage stochastic problem. At the first stage, the VPP's optimal offers to the day-ahead (DA) market are determined before the realization of stochastic variables. At the second stage, this participant's real-time (RT) imbalance cost is optimized after determining the true value of uncertain parameters. On the contrary, at the lower-level (LL), the DA market-cleaning process is performed in the presence of conventional power producers. Moreover, this article aims to calculate the amount of net power trading of the VPP's components with the market and with one another. Ultimately, to assess the effectiveness of the provided framework, a sensitivity analysis is conducted by investigating the effect of the BESS presence on the wind-based VPP's optimal operation and expected benefit.

关键词： Wind producer Battery energy storage system Strategic virtual power plant Market-clearing process bi-level programming problem

来源：评论

学校读者我要写书评

暂无评论

Tri-level transmission expansion planning under intentional attacks: virtual attacker approach - part I: formulation

引用

IET GENERATION TRANSMISSION & DISTRIBUTION 2019年第3期13卷 390-398页

作者： Nemati, Hadi Latify, Mohammad Amin Yousefi, Gholam Reza Isfahan Univ Technol Dept Elect & Comp Engn Esfahan *** Iran

The first part of this two-part paper proposes tri-level transmission expansion planning (TTEP) under physical intentional attacks. In the first level, the network planner looks for an optimal transmission expansion plan to fortify the power network. In the second level, the attacker tries to maximise damages to the network. In the third level, the adverse effects of the attacks on the network operation are minimised by the network operator. Since the third level problem is a linear programming (LP) problem, the second and third levels are converted into a single-level model by using primal-dual transformation, and consequently, TTEP is converted into a bi-level programming problem. To achieve a single-level model, instead of assuming a unique attacker, a cooperative game of multiple virtual attackers (VAs) of which every VA is to maximise the damage by attacking one transmission line is introduced and modelled. The conditions that enforce Nash and Pareto equilibria of this game are derived as linear constraints which are lower level equivalent. By using this equivalence, the aforementioned bi-level TTEP model is converted into a single-level model that can be recast as a mixed integer LP problem. The numerical results are provided in the second part.

关键词： integer programming linear programming power transmission planning game theory physical attacks network operator network operation linear programming problem single-level model bi-level programming problem multiple virtual attackers virtual attacker approach tri-level transmission expansion planning model physical intentional attacks network planner problem optimal transmission expansion plan power network bi-level TTEP model Pareto equilibrium Nash equilibrium linear constraints

来源：评论

学校读者我要写书评

暂无评论

Analysis of adding-runs strategy for peak-hour regular bus services

引用

TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2020年 143卷 102100-102100页

作者： An, Qinhe Fu, Xiao Huang, Di Cheng, Qixiu Liu, Zhiyuan Southeast Univ Sch Transportat Jiangsu Prov Collaborat Innovat Ctr Modern Urban Jiangsu Key Lab Urban ITS Nanjing Peoples R China

This paper proposes an adding-runs strategy to alleviate in-vehicle crowding for peak-hour bus services. Passengers' departure time choices under user equilibrium and system optimum conditions are investigated with and without adding-runs strategy. A bi-level programming model is developed to determine the optimal adding-runs strategy. An artificial bee colony algorithm is adopted to solve the proposed bi-level problem. Numerical examples show that the adding-runs strategy is effective in alleviating crowding effects and reducing schedule delay in peak-hour bus services. The total system cost can be reduced by more than 8% with the optimal adding-runs strategy.

关键词： Peak-hour crowding Adding bus runs User equilibrium System optimum bi-level programming problem

来源：评论

学校读者我要写书评

暂无评论

A multi-product green supply chain under government supervision with price and demand uncertainty

引用

Journal of Industrial Engineering International 2019年第1期15卷 193-206页

作者： Hafezalkotob, Ashkan Zamani, Soma Department of Industrial Engineering Industrial Engineering College Islamic Azad University South Tehran Branch Entezari Alley Oskoui Alley Choobi Bridge Tehran *** Iran

In this paper, a bi-level game-theoretic model is proposed to investigate the effects of governmental financial intervention on green supply chain. This problem is formulated as a bi-level program for a green supply chain that produces various products with different environmental pollution levels. The problem is also regard uncertainties in market demand and sale price of raw materials and products. The model is further transformed into a single-level nonlinear programming problem by replacing the lower-level optimization problem with its Karush–Kuhn–Tucker optimality conditions. Genetic algorithm is applied as a solution methodology to solve nonlinear programming model. Finally, to investigate the validity of the proposed method, the computational results obtained through genetic algorithm are compared with global optimal solution attained by enumerative method. Analytical results indicate that the proposed GA offers better solutions in large size problems. Also, we conclude that financial intervention by government consists of green taxation and subsidization is an effective method to stabilize green supply chain members’ performance. © 2018, The Author(s).

关键词： bi-level programming problem Game theory Genetic algorithm Green supply chain Uncertainty

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：