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Research on the combinatorial optimization of EBs departure interval and vehicle configuration based on uncertain bi-level programming

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TRANSPORTATION LETTERS-THE INTERNATIONAL JOURNAL OF TRANSPORTATION RESEARCH 2023年第7期15卷 623-633页

作者： Guo, Jun Xue, Yunqiang Guan, HongZhi Beijing Univ Technol Fac Urban Construct Beijing 100124 Hebei Peoples R China East China Jiaotong Univ Sch Transportat & Logist Nanchang Jiangxi Peoples R China

Based on uncertainty theory, this paper proposed a vehicle scheduling method considering the dynamic departure interval and vehicle configuration of electric buses (EBs). An uncertain bi-level programming model (UBPM) is established, which takes the total cost of passenger travel (CP) as the upper and total cost of EBs (CB) as the lower. A chance constrained programming model (CCPM) based on the randomness of passenger waiting time and the uncertainty of interstation running time is proposed as the upper model. With a certain confidence level of service level as constraints, the goal is to minimize the total cost of passenger travel. Then, an expected value model (EVM) based on the fluctuation of energy consumption is proposed as the lower model. Taking the number of EBs as the constraint condition, the goal was to minimize the energy consumption of EBs. Finally, a practical bus route is taken as an example to verify the effectiveness of the proposed method. The results demonstrated that the optimal scheduling plan considering the uncertain variables can reduce the passenger travel cost. Collaborative optimization of EBs vehicle configuration can reduce energy consumption, delay, and the number of EBs.

关键词： Electric buses uncertainty theory bi-level programming timetable optimization vehicle configuration

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Solving bi-level programming problem with fuzzy random variable coefficients

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2017年第1期32卷 521-528页

作者： Singh, Vishnu Pratap Chakraborty, Debjani Indian Inst Technol Kharagpur Dept Math Kharagpur 721302 W Bengal India

This paper represents the bi-level linear programming problem in an imprecise and uncertain mixed environment. The aim of this paper is to introduce coefficients of leader and the follower's objective function and the constraints as the fuzzy random variable. To determine the optimal value of the leader and follower's objectives a new methodology is developed for bi-level linear programming model in the presence of fuzzy random variable. A numerical example is solved to demonstrate the methodology.

关键词： bi-level programming fuzzy random variable two stage stochastic programming fuzzy goal programming

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A bi-level programming framework for identifying optimal parameters in portfolio selection

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INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 2022年第1期29卷 87-112页

作者： Jing, Kui Xu, Fengmin Li, Xuepeng Xi An Jiao Tong Univ Sch Econ & Finance Xian 710061 Peoples R China

This paper addresses the problem of identifying optimal portfolio parameters in nonsparse and sparse models. Generally, using the sample estimates to construct a mean-variance portfolio often leads to undesirable portfolio performance. We propose a novel bi-level programming framework to identify the optimal values of expected return and cardinality, which can be estimated separately or simultaneously. In the general formulation of our approach, outer-level is designed to maximize the utility of the portfolio, which is measured by Sharpe ratio, while the inner-level is to minimize the risk of a portfolio under a given expected return. Considering the nonconvex and nonsmooth characteristics of the outer-level, we develop a hybrid derivative-free optimization algorithm embedded with alternating direction method of multipliers to solve the problem. Numerical experiments are carried out based on both simulated and real-life data. During the process, we give a prior range of cardinality using the data-driven method to promote the efficiency. Estimating the parameters by our approach achieves better performance both in the stock and fund-of-funds markets. Moreover, we also demonstrate that our results are robust when the risk is measured by conditional value-at-risk.

关键词： bi-level programming parameter estimation cardinality portfolio selection derivative-free optimization

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Type-2 fuzzy mixed-integer bi-level programming approach for multi-source multi-user water allocation under future climate change

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JOURNAL OF HYDROLOGY 2020年 591卷 125332-125332页

作者： Yue, Qiong Wang, Youzhi Liu, Liu Niu, Jun Guo, Ping Li, Peng China Agr Univ Ctr Agr Water Res China Beijing 100083 Peoples R China Hubei Zhanghe Project Adm Bur Jingmen 448156 Peoples R China

Global climate change and increasing pressure of water shortage reinforce the necessity of optimal water management. In this study, a type-2 fuzzy mixed-integer bi-level programming (T2FMBP) approach is developed for the identification of reasonable water allocation policies by incorporating type-2 fuzzy sets, mixed-integer linear programming, bi-level programming and Stewart model into a general optimization framework. The T2FMBP model improves upon conventional bi-level programming for handling tradeoffs between two-level decision makers considering multiple water allocation processes. It is capable of addressing parameter uncertainties caused by natural conditions and human activities, and supporting in-depth analysis of water allocation schemes associated with future climate change. In this study, group opinion aggregation method for fuzzy number construction, critical value method for type-2 fuzzy number defuzzification, and fuzzy coordination method for solving bi-level programming are adopted. Then, the model was demonstrated for a real-world case study in the Zhanghe Irrigation District for multi-source multi-user water resources planning. The results show that the proposed model can tackle tradeoffs among hierarchical decision makers' conflicting concerns under uncertainties characterized as type-2 fuzzy numbers. Besides, the results can help generate water allocation schemes among different water sectors as well as different crop growth stages effectively under three hydrological years (wet year, normal year, and dry year) and three representative concentration pathway (RCP) scenarios (RCP 2.6, RCP 4.5, and RCP 8.5). Furthermore, comparison was made between T2FMBP model and four single-level models with same constraints. The comparison reveals that T2FMNP model considers all the targets and makes excellent balance between two-level decision makers. A comparison between current situation and RCP scenarios will help make policies for foresight. The formulate

关键词： Type-2 fuzzy sets bi-level programming Future climate change Uncertainty Water allocation

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A bi-level programming approach for improving relief logistics operations: A real case in Kermanshah earthquake

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COMPUTERS & INDUSTRIAL ENGINEERING 2020年 145卷 106532-106532页

作者： Haeri, Abdorrrahman Hosseini-Motlagh, Seyyed-Mahdi Samani, Mohammad Reza Ghatreh Rezaei, Marziehsadat Iran Univ Sci & Technol Sch Ind Engn Univ Ave Tehran 16846 Iran

Due to its location on the world dry belt, Iran is known as a disaster-prone country. Regarding such a problem, planning for relief operations in disaster situations seems significant and undeniable. The literature on disaster management has mostly defined their problems in a single-level framework, ignoring the bi-level aspect of such problems in both preparedness and response phases. However, in the context of disaster in the real world, there is normally more than one decision-maker that each of them may have their own objective. In this study, a bilevel multi-objective programming approach is extended to design a pre-positioning and distribution network under disastrous conditions considering both preparedness and response phases. The extended framework takes into account simultaneous planning for the distribution of drug, blood and relief items among disaster victims, and transferring the injured to hospital in order to diminish the adverse effects of potential disasters in the response phase. Additionally, to determine suitable candidate places for locating relief centers in the preparedness phase, a modified version of data envelopment analysis model is utilized, something that is not frequently done for facility location planning in the disaster management field. On the other hand, to solve the bilevel multi-objective programming problem with decision-makers at the upper level (the affected country) and the lower level (the international organization), a fuzzy goal programming algorithm is proposed. Furthermore, a consolidated method with respect to a novel fuzzy measure is developed to keep the considered network safe against the inherent uncertainty. Finally, the extended framework is utilized to solve a case study in Kermanshah, the province of Iran.

关键词： Disaster relief Data envelopment analysis bi-level programming Uncertainty Fuzzy goal programming

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Optimization of Train Working Plan based on Multiobjective bi-level programming Model

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JOURNAL OF INFORMATION PROCESSING SYSTEMS 2018年第2期14卷 487-498页

作者： Hai, Xiaowei Zhao, Chanchan Inner Mongolia Univ Technol Sch Econ & Management Hohhot Peoples R China Inner Mongolia Univ Technol Coll Informat Engn Hohhot Peoples R China

The purpose of the high-speed railway construction is to better satisfy passenger travel demands. Accordingly, the design of the train working plan must also take a full account of the interests of passengers. Aiming at problems, such as the complex transport organization and different speed trains coexisting, combined with the existing research on the train working plan optimization model, the multiobjective bi-level programming model of the high-speed railway passenger train working plan was established. This model considers the interests of passengers as the center and also takes into account the interests of railway transport enterprises. Specifically, passenger travel cost and travel time minimizations are both considered as the objectives of upper-level programming, whereas railway enterprise profit maximization is regarded as the objective of the lower-level programming. The model solution algorithm based on genetic algorithm was proposed. Through an example analysis, the feasibility and rationality of the model and algorithm were proved.

关键词： bi-level programming Genetic Algorithm Multiobjective Train Working Plan

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A bi-level programming approach for production-distribution supply chain problem

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COMPUTERS & INDUSTRIAL ENGINEERING 2017年 110卷 527-537页

作者： Amirtaheri, Omid. Zandieh, Mostafa Dorri, Behrouz Motameni, A. R. Shahid Beheshti Univ GC Management & Accounting Fac Dept Ind Management Tehran Iran

This paper investigates a decentralized production-distribution supply chain consisting of one manufacturer and one distributor where the demand is jointly influenced by pricing and advertising policies. The control of decision variables is partitioned amongst the members. The manufacturer decides about wholesale price, production interval, expenditure of global advertising, and participation rate in the distributor's local advertising expenditure while the decisions on selling price, local advertising expenditure, and allocation of demands to depots are made by the distributor. We propose a Stackelberg game framework and develop two nonlinear bi-level programming models by switching the leader and follower roles between the manufacturer and the distributor. Four hierarchical solution algorithms are proposed by combining genetic algorithm and particle swarm optimization to tackle the bi-level programming models. Finally, computational experiments are carried out to analyze and compare the efficiency and effectiveness of the proposed solution procedures. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： bi-level programming Supply chain coordination Production-distribution supply chain Stackelberg game Genetic algorithms Particle swarm optimization

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A bi-level programming model for protection of hierarchical facilities under imminent attacks

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COMPUTERS & OPERATIONS RESEARCH 2015年 64卷 210-224页

作者： Aliakbarian, Nasrin Dehghanian, Farzad Salari, Majid Ferdowsi Univ Mashhad Fac Engn Dept Ind Engn Mashhad Iran

Disorders caused by deliberate sabotage and terrorist attacks have always been considered as a major threat by the governments. Hence, identifying and planning for strengthening of critical facilities have become a priority for more security and safety. This paper presents a bi-level formulation of the r-interdiction median problem with fortification for critical hierarchical facilities. In the developed bi-level formulation, the defender, as the leader, decides to protect a certain number of facilities in each level of the hierarchical system in order to minimize the impact of the most disruptive attacks to unprotected facilities. On the other hand the attacker, as the follower, with full information about protected facilities, makes his interdiction plan to maximize the total post-attack cost incurred to the defender. We develop three metaheuristic algorithms and an exhaustive enumeration method to solve the introduced problem. Extensive computational tests on a set of randomly generated instances demonstrate the effectiveness of the developed algorithms. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Hierarchical facility location Protection planning Interdiction bi-level programming Variable depth neighborhood search Simulated annealing

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LINEAR bi-level programming-PROBLEMS - A REVIEW

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JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 1991年第2期42卷 125-133页

作者： WEN, UP HSU, ST NATL TSING HUA UNIV DEPT IND ENGNKUANG FU RDHSINCHU 300TAIWAN

Multi-level programming is characterized as mathematical programming to solve decentralized planning problems. The decision variables are partitioned among ordered levels. A decision-maker at one level of the hierarchy may have his own objective function and decision space, but may be influenced by other levels. During the last 10 years, a special case of the multi-level programming problem, the linear bi-level programming (BLP) problem, has been studied with increasing interest in the area of mathematical programming problems. This paper attempts to review the literature on the linear BLP problems. It presents the basic models and the characterizations of the problem, the areas for application, the existing solution approaches, and the related models and areas for further research.

关键词： bi-level programming DECENTRALIZED PLANNING DECISION-MAKING

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Multistage transmission network expansion planning in competitive electricity market based on bi-level programming method

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EUROPEAN TRANSACTIONS ON ELECTRICAL POWER 2011年第5期21卷 1719-1730页

作者： Fan, Hong Cheng, Hao-zhong Shanghai Univ Elect Power Dept Elect Power & Automat Engn Shanghai 200090 Peoples R China Shanghai Jiao Tong Univ Dept Elect Engn Shanghai 200240 Peoples R China

A new bi-level programming model for market-based transmission network expansion planning is presented in the paper. Open access transmission brings new challenges to transmission network expansion planning. From the transmission corporation's view, the goal of optimal transmission network expansion planning scheme should not only bring the optimal transmission profit in the market, but also ensure high operation security and reliability, meanwhile social welfare is necessary to be accounted for. In this paper, the upper level programming considers transmission profit maximization in long-term planning, the lower level programming considers the social welfare maximization in short-term operation. Furthermore, N-1 security constraints are also considered in the model. A hybrid algorithm integrated with niche genetic algorithm (GA) and primal-dual interior method is adopted to solve the proposed bi-level programming model of the transmission network expansion planning. The planning methodology has been demonstrated on the 18-bus system to show the feasibility and validity, moreover, comparison has been made between traditional transmission expansion plan and proposed market-based transmission expansion plan;it was also applied to the real life system 77-bus system transmission grid. Copyright (C) 2010 John Wiley & Sons, Ltd.

关键词： electricity market transmission network expansion planning bi-level programming hybrid algorithm

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