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作者： NATTANA TANGSANGOB THAMMASAT UNIVERSITY

学位级别：硕士

Optimizing promotion price is a complicated issue facing by retailer in every competitive market. This research empirically analyzes the retailer's optimal decision on price and period. A mathematical programming model which is based on an integration of retailer's pricing decision and customer's response is proposed. The objective of this research is to utilize the model to understand how optimal promotion decision should be made to maximize retailer's profit while facing strategic customers who make a purchasing decision to minimize their purchasing and holding costs. To accomplish this study, we formulate a nonlinear bi-level programming model with discrete and continuous variables to influence the customers' purchasing decision in such a way that retailer plan. Then transform into an equivalent single model by applying Duality Theory and linearize the model which can be solve by IBM ILOG CPLEX. Further, we investigate four key parameters: (1) Competitor price; (2) Wholesale price; (3) Holding cost of customer; and (4) Demand which affect the optimal promotion price and period. The main contribution of this research is we prove that optimal solution for solving the customer model by linear programming model and integer programming model is equal. Further, the model can provide the retailer's optimal promotion discount strategy and inventory policy that is applicable for managers in industry and researchers in academic area.

关键词： promotion period retail price optimization bi-level linear programming

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Multicriteria Decision Analysis Coupled with Type-2 Fuzzy bi-level programming for Water Resource Optimization: A Case Study of the Jiulong River Basin, China

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JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT 2025年第2期151卷

作者： Zhang, Xi Jin, Lei Fu, Haiyan Fan, Yurui Yin, Ruoyu Wang, Li Xiamen Univ Technol Coll Environm Sci & Engn Xiamen 361024 Fujian Peoples R China Brunel Univ London Dept Civil & Environm Engn Uxbridge UB8 3PH Middx England Xiamen Univ Technol Coll Math & Stat Xiamen 361024 Fujian Peoples R China

The uneven spatial distribution and irrational allocation of water resources pose significant challenges to economic development and ecological environment in Jiulong River Basin, Fujian, China. In this study, a Type-2 fuzzy bi-level programming (T2FBL) method was developed to optimize the water resource system in the Jiulong River Basin. Future data for the water resources system were predicted using the back-propagation neural network method. The results were analyzed and evaluated using a new multicriteria decision analysis (MCDA) approach. Additionally, the entropy weight and technique for order of preference by similarity to ideal solution (TOPSIS) methods were combined with MCDA to develop the entropy weight TOPSIS method. With the goal of optimizing the water allocation structure in different regions to alleviate water supply pressure, the proposed model uses an improved fuzzy sorting algorithm to address uncertain parameters in the water resources system and considers the conflicting intersections of decision makers at two levels in a bi-level programming model. The results revealed the following: (1) priority was given to adjusting the water distribution structure in Zhangzhou and Longyan in China while developing secondary industries to promote regional economic development;(2) analysis and evaluation of the results of water allocation using the novel MCDA methodology indicated that the optimal scenario resulted in 51.4% increase in tertiary output;and (3) the calculation results of the T2FBL model were analyzed to establish the relationship between water resource allocation, and economic and environmental benefits, essentially serving as a reference for water resource planning. Moreover, this model reduced wastewater discharge by up to approximately 8.2% compared with the fuzzy single-level programming and bi-level programming models.

关键词： Type-2 fuzzy bi-level linear programming Multicriteria decision analysis (MCDA) Water resources

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An improved fuzzy sorting algorithm coupling bi-level programming for synergetic optimization of agricultural water resources: A case study of Fujian Province, China

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JOURNAL OF ENVIRONMENTAL MANAGEMENT 2022年 312卷 114946页

作者： Cheng, Yang Jin, Lei Pan, Yalei Bai, Ruolin Wei, Yi Huang, Guohe Xiamen Univ Technol Coll Environm Sci & Engn Xiamen 361024 Fujian Peoples R China Univ Regina Inst Energy Environm & Sustainable Communities Regina SK S4S 0A2 Canada

The uneven allocation of water resources and the shortage of regional water resources pose great challenges to the economic development and regional development balance of the Fujian province. Optimizing the water allocation structure in different regions can effectively alleviate water pressure. In this study, a type-2 fuzzy bi-level programming (T2FBL) method is proposed to plan the agricultural water resource system in the Fujian province. This method uses an improved fuzzy sorting algorithm to deal with uncertain parameters in the system and combines the bi-level programming method to balance the trade-off between two levels of decision-makers, the uncertain information contained in the secondary membership function omitted in the interval type-2 fuzzy theory is considered in the new ranking algorithm. Multiple scenarios related to different food security needs and different risk indices are examined. The major findings are as follows: (i) With an average tolerance of 75%, the average gross agricultural output value under various scenarios increased (0.4% similar to 7%) (average 3.89%) after optimization. (ii) The regional water allocation scheme under different food demands and different water availability scenarios is calculated, and the results show that prioritizing adjustments to the industrial water distribution structure of Fuzhou and Zhangzhou will greatly relieve the water pressure in the Fujian province. (iii) The relationship between the availability of system water resources and economic benefits is given through the calculation results of the T2FBL model. These findings can provide an in-depth understanding of the interaction between agricultural, industrial and tertiary industry water allocation and provide technical support for agricultural water resource planning issues.

关键词： Type-2 fuzzy number bi-level linear programming Fuzzy sorting method Agricultural water resources

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bi-level programming problem in the supply chain and its solution algorithm

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SOFT COMPUTING 2020年第4期24卷 2703-2714页

作者： Luo, Haiyan Liu, Linzhong Yang, Xun Lanzhou Jiaotong Univ Sch Traff & Transportat Lanzhou 730070 Peoples R China Lanzhou Jiaotong Univ Sch Econ & Management Lanzhou 730070 Peoples R China

Enterprise-wide supply chain planning problems naturally exhibit a multi-level decision network structure, where the upper level of a hierarchy may have his objective function and decision space partly determined by other levels. In addition, each planner's control instruments may allow him to influence the policies at other levels and thereby to improve his own objective function. As a tool, bi-level programming is applied for modeling decentralized decisions in which two decision makers make decisions successively. In this paper, we specifically address bi-level decision-making problems with budget constraint as an attractive feature in the context of enterprise-wide supply chain. We first describe the typical bi-level linear programming problem (BLLPP) and its optimal solution to the penalty function problem, and then, a cooperative decision-making problem in supply chain is modeled as BLLPP. A particle swarm optimization-based computational algorithm is designed to solve the problem, and the numerical example is presented to illustrate the proposed framework.

关键词： Decentralized supply chain bi-level linear programming Budget constraint Particle swarm optimization algorithm

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A hybrid of genetic algorithm and particle swarm optimization for solving bi-level linear programming problem - A case study on supply chain model

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APPLIED MATHEMATICAL MODELLING 2011年第8期35卷 3905-3917页

作者： Kuo, R. J. Han, Y. S. Natl Taiwan Univ Sci & Technol Dept Ind Management Taipei Taiwan Taiwan Semicond Mfg Co Dept Mfg Hsinchu Taiwan

The main goal of supply chain management is to coordinate and collaborate the supply chain partners seamlessly. On the other hand, bi-level linear programming is a technique for modeling decentralized decision. It consists of the upper level and lower level objectives. Thus, this paper intends to apply bi-level linear programming to supply chain distribution problem and develop an efficient method based on hybrid of genetic algorithm (GA) and particle swarm optimization (PSO). The performance of the proposed method is ascertained by comparing the results with GA and PSO using four problems in the literature and a supply chain distribution model. (C) 2011 Elsevier Inc. All rights reserved.

关键词： bi-level linear programming Supply chain management Genetic algorithm Particle swarm optimization

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Congestion management with demand response considering uncertainties of distributed generation outputs and market prices

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Journal of Modern Power Systems and Clean Energy 2017年第1期5卷 66-78页

作者： Linna NI Fushuan WEN Weijia LIU Jinling MENG Guoying LIN Sanlei DANG School of Electrical Engineering Zhejiang UniversityHangzhou 310027ZhejiangChina Department of Electrical and Electronic Engineering Universiti Teknologi BruneiBandar Seri Begawan BE1410Brunei Electric Power Research Institute of Guangdong Power Grid Co.Ltd. Guangzhou 510600GuangdongChina

In recent years,much attention has been devoted to the development and applications of smart grid technologies,with special emphasis on flexible resources such as distributed generations(DGs),energy storages,active loads,and electric vehicles(EVs).Demand response(DR) is expected to be an effective means for accommodating the integration of renewable energy generations and mitigating their power output *** their potential contributions to power system secure and economic operation,uncoordinated operations of these flexible resources may result in unexpected congestions in the distribution system *** addition,the behaviors and impacts of flexible resources are normally highly uncertain and complex in deregulated electricity market *** this context,this paper aims to propose a DR based congestion management strategy for smart distribution *** general framework and procedures for distribution congestion management is first presented.A bi-level optimization model for the day-ahead congestion management based on the proposed framework is ***,the robust optimization approach is introduced to alleviate negative impacts introduced by the uncertainties of DG power outputs and market *** economic efficiency and robustness of the proposed congestion management strategy is demonstrated by an actual 0.4 kV distribution system in Denmark.

关键词： Distribution system Congestion management Demand response Load aggregators Uncertainty Robust optimization bi-level linear programming

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Transmission network expansion planning with security constraints based on bi-level linear programming

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EUROPEAN TRANSACTIONS ON ELECTRICAL POWER 2009年第3期19卷 388-399页

作者： Fan, Hong Cheng, Haozhong Shanghai Jiao Tong Univ Dept Elect Engn Shanghai 200240 Peoples R China

In deregulated power market, multiple conflicting objectives with many constraints should be balanced in transmission planning. The primary objective is to ensure the reliable supply to the demand as economically as possible. In this paper, a new bi-level linear programming model for transmission network expansion planning (TNEP) with security constraints has been proposed. The modeling improves traditional building style by adding reliability planning into economy planning as constraints, letting optimal planning strategy be more economic and highly reliable. A hybrid algorithm which integrates improved niching genetic algorithm and prime-dual interior point method is newly proposed to solve the TNEP based on bi-level programming. The advantages of the new methodology include (1) the highest reliability planning scheme can be acquired a economically as possible;(2) new model avoids the contradictions of conflicting objectives in TNFP, and explores new ideas for TNEP modeling (3) the proposed hybrid algorithm is able to solve bi-level programming and fully manifests the merits of two algorithms as well. Simulation result obtained from two well-known systems and comparison analysis reveal that the proposed methodology is valid. Copyright (C) 2008 John Wiley & Sons, Ltd.

关键词： electric power system transmission network expansion planning bi-level linear programming improved niching genetic algorithms prime-dual interior point method

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