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Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/Journal of Wuhan University of Technology (Transportation Science and Engineering) 2007年第1期31卷 1-4页

作者： Zhang, Xiaopan Qi, Huan Yuan, Xiaohui Institute of System Engineering Huazhong University of Science and Technology Wuhan 430074 China School of Hydropower and Information Engineering Huazhong University of Science and Technology Wuhan 430074 China

It's very necessary to make cooperative scheduling for the total five locks in the Three Gorges Dam and the Gezhouba Dam for all ships that want to pass the two dams so as to navigate smoothly and efficiently. The cooperative scheduling, named navigation co-scheduling, is a complicated combinational optimization problem. A kind of open queuing network with two stations and five servers is used to describe the co-scheduling system and a mixed-integer nonlinear programming (MINLP) model on discrete time domain is designed to represent the optimization. Based on the MINLP model a simulated annealing algorithm with heuristic move strategy is proposed to obtain the near solution. Feasibility and effectiveness are shown by the experiment results under the real navigation data.

关键词： multi-objective programming Navigation co-scheduling Queuing network Simulated annealing Three Gorges Project

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Protection system planning in distribution networks with microgrids using a bi-level multi-objective and multi-criteria optimization technique

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ELECTRIC POWER SYSTEMS RESEARCH 2024年 228卷

作者： Reiz, Cleberton Leite, Jonatas B. Gouveia, Clara S. Javadi, Mohammad Sadegh Sao Paulo State Univ UNESP Dept Elect Engn Ilha Solteira SP Brazil Inst Syst & Comp Engn Technol & Sci INESC TEC Porto Portugal Sao Paulo State Univ UNESP BR-15385000 Ilha Solteira SP Brazil

Microgrids are able to improve several features of power systems, such as energy efficiencies, operating costs and environmental impacts. Nevertheless, microgrids' protection must work congruently with power distribution protection to safely take all advantages. This research contributes to enable their protection by proposing a bilevel method to simultaneously solve the allocation and coordination problems, where the proposed scheme also includes local protections of distributed energy resources. The uncertainties associated with generation and loads are categorized by the k-means method, as well. The non-dominated sorting genetic algorithm II is employed in the upper-level task to solve the protection and control devices allocation problem with two opposing objectives. In the lower-level task, a genetic algorithm ensures their coordination. Protection devices include reclosers and fuses from the network, and directional relays for the point of common coupling of microgrids, while control devices consist of remote-controlled switches. In contrast to related works, local devices installed at the point of coupling of distributed generation units are considered as well, such as voltage-restrained overcurrent relays and frequency relays. The optimal solution for the decision-maker is achieved by utilizing the compromise programming technique. Results show the importance of solving the allocation and coordination problems simultaneously, achieving up to $25,000 cost savings compared to cases that solve these problems separately. The integrated strategy allows the network operator to select the optimum solution for the protective system and avoid corrective actions afterward. The results also show the viability of the islanding operation depending on the decision maker's criteria.

关键词： Power distribution planning Microgrids Reliability Power system protection multi-objective programming Bi-level optimization

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Research on hybrid feature selection method of power transformer based on fuzzy information entropy

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ADVANCED ENGINEERING INFORMATICS 2021年 50卷

作者： Yu, Song Tan, Weimin Zhang, Chengming Fang, Yun Tang, Chao Hu, Dong Southwest Univ Coll Engn & Technol Chongqing 400715 Peoples R China Southwest Univ Int R&D Ctr New Technol Smart Grid & Equipment Chongqing 400715 Peoples R China

The data of dissolved gas in oil analysis (DGA) is uncertain affected by the influence of transformer capacity and fault location, which makes transformer fault diagnosis model based on DGA has low accuracy. Therefore, we propose a hybrid feature selection method based on fuzzy information entropy, whereby optimizing the reasonable DGA feature parameter according to the feature information between the parameter and fault type, to reduce the influence of DGA data uncertainty on the fault diagnosis accuracy. Firstly, the characteristic relevance and redundancy functions are constructed based on fuzzy information entropy theory. Secondly, these functions are taken as the optimization objectives of binary-chaotic multi-objective particle swarm optimization algorithm (B-CMOPSO), to search for the feature subsets in the feature space composed of 46 DGA feature parameters. Then, the optimal feature subset is selected based on the simulation accuracy of ELM, SVM, Adaboost.M1 and BPNN on the feature subsets. Finally, 30 simulation experiments are carried out to compare with several multiobjective optimization algorithms, common Filter methods and common DGA feature combinations, and the rationality of the proposed method is verified by the t-test method. The results show that the 4 classifiers accuracy means is maximatily improved by 18.95%, 20.77%, 19.85% and 21.27% respectively compared with common DGA feature combinations, indicating that the optimal feature subset preserves more feature information and can effectively reduce the influence of DGA data uncertainty on diagnostic accuracy.

关键词： Power transformer DGA Feature selection multi-objective programming Fuzzy information entropy

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A multi-objective Stochastic Model for a Green Supply Chain planning

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IFAC Proceedings Volumes 2012年第6期45卷 514-521页

作者： S.M.J. MIRZAPOUR AL-E-HASHEM Z. SAZVAR A. BABOLI Y. REKIK EMLYON Business School 23 avenue Guy de Collongue 69134 Ecully Lyon France Université de Lyon INSA-Lyon DISP Laboratory F-69621 France (Tel.: +***

In this study we develop a stochastic multi-objective stochastic programming approach to deal with a supply chain planning under uncertainty. Supply chain cost parameters such as transportation cost, inventory holding cost, shortage cost, production cost in addition to some respects as employment, dismissal, workers productivity and training are all considered. Due to the important role of the lead time especially in supplying, the lead time between suppliers and factories and between factories and customer zones is assumed to be a function of transportation mode. Cost parameters and demand fluctuations are subject to uncertainty. To develop the model, two additional objective functions are added to the classical aggregate production planning. Therefore, the proposed multi-objective model includes the minimization of the expected total cost of supply chain, the minimization of the variability of the total cost of supply chain and the minimization of the expected value of the greenhouse gas emission level. Then, the proposed model is solved applying compromise programming method. Finally, a numerical example is solved to describe the proposed model.

关键词： Aggregate production planning multi-objective programming stochastic optimization Green supply chain compromise programming.

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A Method for the Solution of Educational Investment

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Journal of Applied Mathematics and Physics 2016年第6期4卷 1131-1142页

作者： Jun’e Liu Le Yu Xiaolin Liu The School of Information Beijing Wuzi University Beijing China Graduate Department Beijing Wuzi University Beijing China

In order to improve the performance of higher education in the United States, the Goodgrant Foundation intends to donate a total of $100,000,000 (US 100 million) to an appropriate group of schools per year, for five years, starting in July 2016. For this, our team puts forward upon an optimal investment strategy, which includes the schools to invest, the investment amount of each school, and the return due to investment, to solve this problem. Our main idea is as follows. First of all, we choose suitable investment school universities in the United States. Secondly, we use Analytic Hierarchy Process to get the rate of return on investment and venture capital. Thirdly, we establish a venture capital return model. Finally, solving the mathematical model ensures the investment amount of each school and the return due to investment. To implement this strategy, first of all, we obtain the candidate school based on students score card. Then, according to the factor analysis, we analyze the factors which mainly affect the choice of school. Secondly, we employ Analytic Hierarchy Process to get the rate of return on investment and capital risk. In the end, we establish a risk return model to get investment amount for each school, amount of risk and return. In order to ensure the minimum risk and the maximum return, we set up a multi objective programming model and solve it by using the constraint method. We get the result that includes the maximum net profit of the investment and risk loss rate. According to statistical analysis, we can get the overall return of net income within five years. Finally, we choose 320 candidate schools and get the investment amount of each school according to the principle of as many schools as possible. We have proved that the foundation will receive a return of more than 295.363 million in the next 5 years. After-verification, our strategy can be directly applied to the investment field and get good results.

关键词： AHP multi-objective programming Risk Investment Return

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A fuzzy bicriteria approach for journal deselection in a hospital library

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LIBRARY COLLECTIONS ACQUISITIONS & TECHNICAL SERVICES 2007年第3-4期31卷 138-160页

作者： Lopez-Avello, Maria Luisa Rodriguez-Uria, Maria Vickoria Perez-Gladish, Blanca Bilbao-Terol, Amelia Arenas-Parra, Mar Dept Econ Cuantitat Oviedo 33006 Spain Univ Oviedo Oviedo Spain

Collection management is an important duty of librarians. In the last years journal prices have increased and library decision-makers have been forced to consider cancelling some journal subscriptions as budgets have not increased always by the same ratio. This fact has made it essential to supply reliable and efficient measures about the importance of different journals for in-house users in order to help the decision-makers to cancel subscriptions. Many journal-use studies can be found in the literature providing methods for making these kinds of decisions, but usually they consider only one single and precise decision criterion. Nevertheless, it is common knowledge that any real decision usually considers more than one criterion, and so the problem of choosing a set of journals to cancel is compounded by the existence of conflicting criteria, such as the cost of the journal and demand for the journal. As predicting possible number of users of a certain journal is a complex task, the expert's judgments could be vital elements. Fuzzy Set theory could be a useful tool in dealing with these kinds of real decisions based on the expert's knowledge and characterized by some level of subjectivity, in which the decision-maker has imprecise and/or vague data and/or incomplete information. In this paper a fuzzy bicriteria optimisation method is proposed to determine the optimal shape of the printed journal collection in a medical library in a Spanish public hospital. We jointly consider two criteria: maximising a usage function and also an opportunity coefficient of purchase function, both defined for each printed journal. Budget constraints and minimum availability constraints are taken into account. The proposed model is flexible, incorporates expert knowledge and can be easily extended to other hospital libraries. (c) 2008 Elsevier Inc. All rights reserved.

关键词： multi-objective programming fuzzy sets decision-making journal deselection weighting method

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Dynamic pricing model for new/used products in the processing of closed-loop supply chain operation

Dynamic pricing model for new/used products in the processin...

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22nd Chinese Control and Decision Conference

作者： Xu, Jiawang Zhu, Yunlong Jiang, Bo Shenyang Aeronaut Engn Inst Sch Econ & Management Shenyang 110004 Peoples R China Chinese Acad Sci Shenyang Inst Automat Shenyang 110016 Peoples R China

ISBN: (纸本)9781424451821

From the view of operation researches, the operation problem for a class of closed-loop supply chain system with one manufacturer and one supplier is considered. Demands of ultimate products and collecting quantity of used products are described by using prices and reference prices, a non-linear dynamic pricing model for new/used products in the processing of this system operation is established. The model is constructed as a dynamic programming problem and satisfying several conflict objectives, such as the operating coordination of system, making the maximum profit of all participants as much as possible. The model's validity to dynamic pricing for closed-loop supply chain system is verified by a numerical example. The results of the numerical example shows that, in the long run, through the regulations of price itself and price reference effect, the price of ultimate product and the collecting price of used product fix to a certain value without reference to the initial price of ultimate product and the collecting price of used product.

关键词： Operation researches Closed-loop supply chain Pricing policy multi-objective programming

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Some Improvements on Model Free Controller

Some Improvements on Model Free Controller

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7th World Congress on Intelligent Control and Automation

作者： Li, Junling Zhang, Shugong Jilin Univ Inst Math Changchun 130012 Peoples R China Jilin Univ Key Lab Symbol Comp & Knowledge Engn Minist Educ Changchun 130012 Peoples R China

ISBN: (纸本)9781424421138

Firstly we make a brief introduction of the algorithm and astringency of existing model free controller and then in this paper propose two methods to improve the existing controller. On the one hand, a model free controller with dead zone is presented in order to avoid frequent movement of control action and eliminate the vibration of the system in some conditions. On the other hand, the problem of model free controller with constraints is considered. This problem is reduced to a multi-objective programming (MOP) and a multilevel ordering method is used to accomplish the programming with respect to the sense of the control problem. The effectiveness of the improved controllers is verified via two numerical examples.

关键词： model free control constraint multi-objective programming multilevel ordering method

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A two-stage layout method for functional areas in logistics park

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ADVANCES IN MECHANICAL ENGINEERING 2019年第3期11卷

作者： Luo, Qingyu Zhu, Jiaxiang Jia, Hongfei Xu, Yingjun Jilin Univ Coll Transportat Changchun 130022 Jilin Peoples R China

The layout of functional areas has a great impact on the implementing of a logistics park. Existing layout models with multiple planning objectives and influencing factors are too complex to be solved. This article puts forward a two-stage layout method for functional areas in logistics parks combining a layer-by-layer analysis process and a multi-objective programming model. Base on the rational setting of functional areas, the optimization of operational processes and the quantification of the interrelations between functional areas, some green logistic goals are achieved in two stages. In the first stage, the method aims at maximizing the comprehensive relationship among functional areas and obtaining the layout structure by the layer-by-layer analysis process. In the second stage, a multi-objective planning model is established to get the location and shape of each functional area, with the goals of minimizing the material handling costs and maximizing the spatial utilization rate. A genetic algorithm is designed to solve the model. Finally, an example is put forward to verify the feasibility of the two-stage layout method, and the comparison with the previous general model is presented. This article provides a new method for the layout planning of function areas in green logistics parks.

关键词： Layout design structural analysis multi-objective programming genetic algorithm green logistics

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multi-objective optimization for perishable product dispatch in a FEFO system for a food bank single warehouse

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OPERATIONS RESEARCH PERSPECTIVES 2024年 12卷

作者： Suarez, Carlos Anibal Guano, Walter A. Perez, Cinthia C. Roa-Lopez, Heydi ESPOL Escuela Super Politecn Litoral Fac Nat Sci & Math Campus Gustavo GalindoKm 30-5 Via Perimetral Guayaquil 090902 Ecuador ESPOL Escuela Super Politecn Litoral Fac Mech Engn & Prod Sci Campus Gustavo GalindoKm 30-5 Via Perimetral Guayaquil 090902 Ecuador ESPOL Escuela Super Politecn Litoral Pacific Int Ctr Disaster Risk Reduct Campus Gustavo GalindoKm 30-5 Via Perimetral Guayaquil 090902 Ecuador

One of the main challenges of food bank warehouses in developing countries is to determine how to allocate perishable products to beneficiary agencies with different expiry dates while ensuring food safety, meeting nutritional requirements, and minimizing the shortage. The contribution of this research is to introduce a new multi-objective, multi-product, and multi-period perishable food allocation problem based on a single warehouse management system for a First Expired-First Out (FEFO) policy. Moreover, it incorporates the temporal aspect, guaranteeing the dispatch of only those perishable products that meet the prescribed minimum quality standards. A weighted sum approach converts the multi-objective problem of minimizing a vector of objective functions into a scalar problem by constructing a weighted sum of all the objectives. The problem can then be solved using a standard constrained optimization procedure. The proposed mixed integer linear model is solved by using the CPLEX solver. The solution obtained from the multi-objective problem allows us to identify days and products experiencing shortages. In such cases, when there is insufficient available inventory, the total quantity of product to be dispatched is redistributed among beneficiaries according to a pre-established prioritization. These redistributions are formulated as integer programming problems using a score-based criterion and solved by an exact method based on dynamic programming. Computational results demonstrate the applicability of the novel model for perishable items to a real-world study case.

关键词： Linear optimization multi-objective programming Perishable products FEFO Dynamic programming

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