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Multi-objective optimisation and decision-making of space station logistics strategies

INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 2016年第13期47卷 3132-3148页

作者： Zhu, Yue-he Luo, Ya-zhong Natl Univ Def Technol Coll Aerosp Sci & Engn Changsha Hunan Peoples R China

Space station logistics strategy optimisation is a complex engineering problem with multiple objectives. Finding a decision-maker-preferred compromise solution becomes more significant when solving such a problem. However, the designer-preferred solution is not easy to determine using the traditional method. Thus, a hybrid approach that combines the multi-objective evolutionary algorithm, physical programming, and differential evolution (DE) algorithm is proposed to deal with the optimisation and decision-making of space station logistics strategies. A multi-objective evolutionary algorithm is used to acquire a Pareto frontier and help determine the range parameters of the physical programming. Physical programming is employed to convert the four-objective problem into a single-objective problem, and a DE algorithm is applied to solve the resulting physical programming-based optimisation problem. Five kinds of objective preference are simulated and compared. The simulation results indicate that the proposed approach can produce good compromise solutions corresponding to different decision-makers' preferences.

关键词： Space station logistics multi-objective evolutionary algorithm physical programming differential evolution algorithm decision-making preference

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An integrated approach to solve a robust forward/reverse supply chain for short lifetime products

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COMPUTERS & INDUSTRIAL ENGINEERING 2016年 97卷 222-239页

作者： Mirmajlesi, Seyed Reza Shafaei, Rasoul KN Toosi Univ Technol Dept Ind Engn Tehran Iran

Supply chain management plays a key role in optimizing manufacturing costs in competitive markets. In this paper, a multi period, multi product, multi echelon and capacitated supply chain problem for short lifetime products was solved using both exact method and metaheuristic algorithms. The considered echelons in a forward/reverse supply chain network design include suppliers, hybrid production-inspection centers, hybrid warehouse-collection centers, retailers, disposal centers and recovery centers. To tackle both strategic and tactical nature of the problem and due to its complexity, the location problem is first solved using an exact method in which strategic decisions are made aiming to minimize the location costs. Then the allocation problem is solved using both exact and metaheuristic algorithms, namely Tabu Search and differential evolution, in which based on the results obtained from the location problem, the profit is maximized and tactical decisions are made. A cyclic feedback procedure is proposed in between the location and allocation models to obtain the best solution. The allocation model is linearized using a new method and to handle the uncertainty, a robust mixed integer programming model is developed which can retain the linearity of the model. The computational results confirm the effectiveness of the exact method for the location problem while testifies the proposed algorithms can obtain effective solutions compared with that of the exact solutions for the allocation problem in both deterministic and uncertain environment. In addition, the results show that in terms of preciseness and convergence, the proposed differential evolution algorithm outperforms the other algorithm. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Supply chain management Robust optimization Short lifetime products differential evolution algorithm Tabu Search algorithm

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Research on Formation Method of Multi-robot

Research on Formation Method of Multi-robot

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2017 2nd International Conference on Mechatronics and Information Technology(ICMIT 2017)

作者： Qinzhao Wang Jinyong Cheng Xiaolong Li Jin Pei Junxiao Bao Department of Control Engineering Armored Force Engineering College 1st Brigade Fourth Military Medical University

Aiming at the formation problem of multi-robot formation, a phased multi-robot formation strategy is proposed. The formation strategy takes full account of the robot's pose information and formation cost constraints, and decomposes the formation problem into two stages: the formation point distribution and the motion control. An improved discrete differential evolution algorithm is used to allocate the appropriate formation point for the robot. The motion controller is constructed using the consistency theory and the potential field idea, so that the robot at any initial position can move to the formation point without safety. Simulation results show that the formation strategy can form an effective formation, reduce the resource consumption of the robot during the formation process and improve the formation efficiency.

关键词： multi-robot formation differential evolution algorithm artificial potential field

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Improved differential evolution algorithm for resource-constrained project scheduling problem

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Journal of Systems Engineering and Electronics 2010年第5期21卷 798-805页

作者： Lianghong Wu Yaonan Wang Shaowu Zhou College of Information and Electrical Engineering Hunan University of Science and Technology Xiangtan 411201 E R. China College of Electrical and Information Engineering Hunan University Changsha 410082 R R. China

An improved differential evolution（IDE）algorithm that adopts a novel mutation strategy to speed up the convergence rate is introduced to solve the resource-constrained project scheduling problem（RCPSP）with the objective of minimizing project duration Activities priorities for scheduling are represented by individual vectors and a senal scheme is utilized to transform the individual-represented priorities to a feasible schedule according to the precedence and resource constraints so as to be *** investigate the performance of the IDE-based approach for the RCPSP,it is compared against the meta-heuristic methods of hybrid genetic algorithm（HGA）,particle swarm optimization（PSO） and several well selected *** results show that the proposed scheduling method is better than general heuristic rules and is able to obtain the same optimal result as the HGA and PSO approaches but more efficient than the two algorithms.

关键词： differential evolution algorithm project soheduling resource constraint priority-based scheduling.

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Option pricing for stochastic volatility model with infinite activity Levy jumps

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PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 2016年 455卷 1-10页

作者： Gong, Xiaoli Zhuang, Xintian Northeastern Univ Sch Business Adm Shenyang 110169 Peoples R China

The purpose of this paper is to apply the stochastic volatility model driven by infinite activity Levy processes to option pricing which displays infinite activity jumps behaviors and time varying volatility that is consistent with the phenomenon observed in underlying asset dynamics. We specially pay attention to three typical Levy processes that replace the compound Poisson jumps in Bates model, aiming to capture the leptokurtic feature in asset returns and volatility clustering effect in returns variance. By utilizing the analytical characteristic function and fast Fourier transform technique, the closed form formula of option pricing can be derived. The intelligent global optimization search algorithm called differential evolution is introduced into the above highly dimensional models for parameters calibration so as to improve the calibration quality of fitted option models. Finally, we perform empirical researches using both time series data and options data on financial markets to illustrate the effectiveness and superiority of the proposed method. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Stochastic volatility Infinite activity Levy process differential evolution algorithm Option pricing

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Multi-objective Hybrid DE algorithm for Solving VRPTW

Multi-objective Hybrid DE Algorithm for Solving VRPTW

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2017 International Conference on Mathematics, Modelling and Simulation Technologies and Applications（MMSTA 2017)

作者： Xiao-yu SONG Kai-wen ZHENG Yan WU Control Engineering Faculty Shenyang Jianzhu University

For the characteristics of the Vehicle Routing Problem with Time Windows(VRPTW)..a multi-objective hybrid differential evolution algorithm for VRPTW is ***,through a linearly varying parameter controls the probability of choice of DE/rand/1 mutation strategy and DE/best/1 mutation ***,a crossover operation based on merge sort is ***,selection operations employ Pareto-dominated concepts and ring rules to rank individuals and output non-dominated *** experimental results compared with single strategy DE algorithm and ABC algorithms show that the proposed algorithm is effective in solving the VRPTW.

关键词： Vehicle routing problem with time windows Strategy hybrid algorithm Merge sort nondominated set differential evolution algorithm

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Modeling of Plate Heat Exchanger Based on Kernel Partial Least Squares

Modeling of Plate Heat Exchanger Based on Kernel Partial Lea...

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第28届中国过程控制会议（CPCC 2017）暨纪念中国过程控制会议30周年

作者： Yuming Guo Fuli Wang Mingxing Jia Dapeng Niu College of Information Science & Engineering Northeastern University State Key Laboratory of Synthetical Automation for Process Industries(Northeastern University)

A model of plate heat exchanger(PHE) for predicting the outlet temperature of cooling water is developed in this *** model combines the mechanistic model with a compensating model in parallel way to reduce the errors caused by assumptions and unknown *** mechanistic model is established based on the thermal balance equation and the thermal transfer equation,furthermore,the parameters in the mechanistic model is identified by forming an optimization problem which is solved by the differential evolution(DE) *** compensating model is a data-driven model consisting of Kernel Partial Least Squares(KPLS) algorithm,which can compensate the deviation of outputs of mechanistic model from the real *** simulation results show that the proposed model demonstrate better performance compared with the pure mechanistic model,which lays an important foundation for energy-saving optimization of PHE.

关键词： Plate heat exchanger Model compensating Outlet temperature of cooling water differential evolution algorithm Kernel Partial Least Squares algorithm

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Cooperative Control of Wind and Hydro Power based on differential evolutionary algorithm

Cooperative Control of Wind and Hydro Power based on Differe...

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2017 International Electrical and Energy Conference (CIEEC 2017)

作者： Xincheng JIN Xiuyuan YANG Fang ZHANG Beijing Information Science & Technology University

With the increasing proportion of wind power,intermittent and catastrophe are becoming increasingly *** order to overcome these problems,consider using hydropower to make up for lack of wind power,wind and water has a strong complementary in season,and the hydro power is highly *** controlling the turbine's output to compensate for the lack of wind power output,the total output of wind power and hydropower is as planning to the *** paper uses the differential evolution algorithm to control the hydro turbine PID controller to control the output power,so as to make up for the wind power *** simulation results show that the differential evolution algorithm control is faster,robust than conventional PID control scheme,it can make the hydro generator stable compensating the wind power fluctuations,cut peak load fill valley load,as far as possible to meet the grid requirements,reduce the grid instability factors,is conducive to long-term *** validity of the method is verified.

关键词： Wind power Hydropower Wind and Hydropower Coordinating Operation differential evolution algorithm

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Multi-period cardinality constrained portfolio selection models with interval coefficients

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ANNALS OF OPERATIONS RESEARCH 2016年第2期244卷 545-569页

作者： Liu, Yong-Jun Zhang, Wei-Guo Wang, Jun-Bo South China Univ Technol Sch Business Adm Guangzhou 510641 Guangdong Peoples R China City Univ Hong Kong Dept Econ & Finance 88 Tat Chee Ave Kowloon Hong Kong Peoples R China

In this paper, we discuss a multi-period portfolio selection problem in emerging markets. To provide investors with more choices, we propose four multi-period cardinality constrained portfolio selection models with interval coefficients in both objective functions and constraints. The proposed models can be equivalently represented as the parameter programming problems with interval coefficients in constraints. We utilize the definition of the possibility degree for interval inequality to handle the interval inequality constraints in the proposed models and express investors' different risk attitudes. Then, the proposed models are transformed into deterministic models. After that, we design a new dynamic differential evolution algorithm with self-adapting control parameter to solve the transformed deterministic models. Finally, we provide a numerical example to illustrate the applications of the proposed models and demonstrate the effectiveness of the designed algorithm.

关键词： Multi-period portfolio Interval coefficient Order relation Possibility degree differential evolution algorithm

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Self-Adaptive differential evolution algorithm for Economic Dispatch with Transmission Losses Consideration

Self-Adaptive Differential Evolution Algorithm for Economic ...

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IEEE Region 10 Conference on TENCON 2010

作者： Sum-Im, Thanathip Srinakharinwirot Univ Fac Engn Dept Elect Engn Nakhon Nayok Thailand

ISBN: (纸本)9781424468904

In this paper, a self-adaptive differential evolution algorithm (SaDEA) is proposed for solving conventional economic dispatch (ED) problem with transmission losses consideration. The purpose of ED problem is to minimize the total fuel cost of thermal power plants associated with the technical operation and economical constraints. The software development has been performed within the mathematical programming environment of MATLAB in this work. The efficiency of the proposed methodology is initially demonstrated via the analysis of IEEE 30-bus test case. A detailed comparative study among Lambda iteration, conventional genetic algorithm (CGA), tabu search/simulated annealing (TS/SA), ant colony search algorithm (ACSA) and the proposed method is presented. From the experimental results, the proposed method has achieved solutions with good accuracy, stable convergence characteristics, simple implementation and satisfactory computational time.

关键词： component differential evolution algorithm Economic Dispatch Power System Optimization Artificial Intelligence

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