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multi-object optimization of flexible flow shop scheduling with batch process - Consideration total electricity consumption and material wastage

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JOURNAL OF CLEANER PRODUCTION 2018年 183卷 925-939页

作者： Zeng, Zhiqiang Hong, Mengna Man, Yi Li, Jigeng Zhang, Yanzhong Liu, Huanbin South China Univ Technol State Key Lab Pulp & Paper Engn Guangzhou 510640 Guangdong Peoples R China

Electricity consumption and material wastage of manufacturing industries have directly or indirectly influenced the environment. Many manufacturing enterprises are committed to improving energy and material efficiencies. To achieve this goal, one of the high-efficiency ways is to optimize the scheduling. In this study, a multi-object optimization model is constructed for a particular kind of batch processing scheduling problem existed in flexible flow shops, where the objects include makespan, electricity consumption and material wastage. First, the models for electricity consumption and material wastage are built, based on which a mathematic model for scheduling problem is built afterwards. Finally, a hybrid non-dominated sorting genetic algorithm II (NSGA-II) method is employed to solve the multi object optimization scheduling model. A case study based on a real-world paper mill industry is presented to demonstrate the effectiveness of the method and its application in practice. Moreover, a real life scheduling problem is investigated, and the result shows that the proposed method is more efficient than manual scheduling in energy and material saving. In fact, many tissue paper mills or other manufacturing industries schedule by manual labor in China, indicating that the proposed method has a significant potential in improving energy and material efficiencies in the studied flexible flow shop, and in energy and material saving in similar industries. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： multi-object optimization Flexible flow shop scheduling Electricity consumption Material wastage

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multi-object optimization design for differential and grading toothed roll crusher using a genetic algorithm

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Journal of China University of Mining and Technology 2008年第2期18卷 316-320页

作者： ZHAO La-la WANG Zhong-bin ZANG Feng School of Mechanical and Electrical Engineering China University of Mining and Technology Xuzhou Jiangsu 221008 China

Our differential and grading toothed roll crusher blends the advantages of a toothed roll crusher and a jaw crusher and possesses characteristics of great crushing,high breaking efficiency,multi-sieving and has,for the moment,made up for the short- comings of the toothed roll *** moving jaw of the crusher is a crank-rocker *** optimizing the dynamic per- formance and improving the cracking capability of the crusher,a mathematical model was established to optimize the transmission angleγand to minimize the travel characteristic value m of the moving *** algorithm is used to optimize the crusher crank-rocker mechanism for multi-object design and an optimum result is *** to the implementation,it is shown that the performance of the crusher and the cracking capability of the moving jaw have been improved.

关键词： differential and grading toothed roll crusher crank-rocker mechanism genetic algorithm multi-object optimization

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Reactive power dispatch of DFIGs in wind farm based on multi-object optimization

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INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS 2020年第3期30卷 1-16页

作者： Li, Shenghu Zhang, Yifan Yu, Xinyu Zhang, Nan Hefei Univ Technol Sch Elect Engn & Automat Hefei 230009 Anhui Peoples R China

The reactive power (var) dispatch is realized at the system and station levels. Var dispatch to the doubly fed induction generators (DFIGs) in the wind farm is seldom studied due to the difficulty of the number and modeling accuracy of the DFIGs and dependency of the var setting on its available reactive power capability (RPC). This paper proposes an optimization model to decide the incremental var output of the DFIGs in the wind farm. The object is to minimize the increments of active power loss in the wind farm and the deviation of the stator voltage of the DFIGs. Considering the voltage fluctuation at the PCC, the distribution coefficient of the var increment is defined for the DFIGs. The nonlinear constraints are expressed by the first + second-order sensitivities of the active power loss of the wind farm and the stator voltages of the DFIGs to the var output of the DFIGs. The nondominated sorting genetic algorithm II (NSGA-II) is applied to obtain the Pareto front, with the evaluation indicators of the var margin defined to decide the incremental var output of the DFIGs. The numerical results validate the feasibility of the proposed algorithm. The reactive power demand to the wind farm is distributed among the DFIGs satisfying the objects and the constraints with desirable accuracy and calculation efficiency.

关键词： doubly fed induction generator (DFIG) multi-object optimization reactive power dispatch sensitivity wind farm

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New hybrid NSGA-III&SPEA/R to multi-object optimization in a half-car dynamic model

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING 2020年第6期234卷 1660-1671页

作者： Dao, Dinh-Nam Guo, Li-Xin Northeastern Univ Sch Mech Engn & Automat Shenyang 110819 Peoples R China Le Quy Don Tech Univ Control Technol Coll Hanoi Vietnam

In this article, we conducted a new hybrid method between Non-dominated Sorting Genetic Algorithm II (NSGA-III) and SPEA/R (HNSGA-III&SPEA/R). This method is implemented to find the optimal values of the powertrain mount system stiffness parameters. This is the task of finding multi-objective optimization involving six simultaneous optimization goals: mean square acceleration and mean square displacement of the powertrain mount system. A hybrid HNSGA-III&SPEA/R has proposed with the integration of Strength Pareto evolutionary algorithm-based reference direction for multi-objective (SPEA/R) and Many-objective optimization genetic algorithm (NSGA-III). Several benchmark functions are tested, and results reveal that the HNSGA-III&SPEA/R is more efficient than the typical SPEA/R and NSGA-III. Powertrain mount system stiffness parameters optimization with HNSGA-III&SPEA/R is simulated. It proved the potential of the HNSGA-III&SPEA/R for powertrain mount system stiffness parameter optimization problem.

关键词： NSGA-III algorithm SPEA R algorithm optimal solution powertrain mount system stiffness multi-object optimization engine mount

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Research on a combined device SMES-SFCL based on multi-object optimization

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IEEE TRANSACTIONS ON APPLIED SUPERCONDUCTIVITY 2005年第2期15卷 2019-2022页

作者： Zhu, GP Wang, ZJ Zhang, GQ Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China Acad China Inst Elect Engn Beijing 10084 Peoples R China

A multi-function superconducting equipment SMES-SFCL is proposed in this paper. It mainly consists of diodes, power condition system, control circuit and a superconducting coil. Its circuit topology is also presented in the paper. Proved by previous simulation and experiment, the combined device can work as SMES or SFCL separately and effectively. Further research on the performance of the device when it fulfills the two functions simultaneously is proposed in this paper. Control strategy based on multi-object optimization is adopted, which is proved to be applicable by simulation by MATLAB. At the end of the paper, the authors give some suggestion on the device structure and control strategy.

关键词： multi-object optimization SFCL SMES

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Electric power network planning based on multi-object optimization model 5

Electric power network planning based on multi-object optimi...

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5th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT)

作者： Ye, Linhao South China Univ Technol Inst Elect Power Guangzhou Guangdong Peoples R China Guangdong Power Grid Foshan Power Supply Bur Planning & Dev Dept Foshan Guangdong Peoples R China

ISBN: (纸本)9781467371063

Aiming at solving network planning problems brought by multi-stage and multi-objection, in this paper, a multi-objective optimization method of network planning is proposed. Considering taking economy and reliability into account, with the objective function of the minimum cost of investment, the minimum annual operating costs of the system and the minimum lack of electricity costs, a general optimized model of multi-objective electric power network planning is presented. The hierarchical optimization model and hybrid genetic-simulated annealing algorithm is used to solve the problems emerging in the process of multi-objective planning. Case proves the effectiveness and scientifically of the proposed method and algorithm.

关键词： electric power network planning multi-object optimization hybrid genetic-simulated annealing algorithm hierarchical optimization model

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multi-factor and multi-object optimization for Foundation Brake Device in Railway Freight Car 16

Multi-factor and Multi-object Optimization for Foundation Br...

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16th International Conference on Ubiquitous Robots (UR)

作者： Li, Zhaoxiang Xu, Chao Zhu, Jianning Lu, Bihong Dalian Jiaotong Univ Dalian 116028 Peoples R China

ISBN: (纸本)9781728132327

It is one of the important measures for improving the operational performance of the basic brake device to ensure the safety of railway freight cars. The operational performance of basic brake device includes braking performance and mitigation performance, which are affected by multi-factor such as lever size, sleeve clearance, installation angle and so on. Therefore, a multi-factor and multi-object optimization method that based on iSIGHT and multi-body dynamics simulation is proposed. The object of optimization is to minimize the transverse displacement of the brake beam and the mitigation force, and maximize the transmission efficiency. Firstly, identify the key factors such as the thickness of fixed lever, the width of back groove of middle tie rod, and the inner diameter of bushing 3 and bushing 4 by the main effect value of orthogonal test. Then, the Latin hypercube sampling points are applied for numerical simulation to establish the response surface model. The optimal solution set is obtained by NSGA-II multi-objectives genetic algorithm cyclic approximation optimization. The optimization scheme is selected by the target importance and the distribution probability of the optimal solution set. Finally, the optimization model is validated in RecurDyn. The optimized scheme achievement shows that the transverse displacement of the brake beam is reduced by 31%, the maximum reduction in mitigation power is 36% and the transmission efficiency is increased by 2%.

关键词： multi-object optimization Foundation Brake Device Response Surface Model multi-body Dynamics

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Dynamic Analysis and multi-object optimization of the Forced Torsional Vibration for Vehicular multi-stage Planetary Gears

Dynamic Analysis and Multi-object Optimization of the Forced...

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International Conference on Power Transmission

作者： Liu Hui Cai Zhong-chang Xiang Chang-le Wang Ming-zheng Beijing Inst Technol Sch Mech & Vehicle State Key Lab Vehicular Transmiss Beijing 100081 Peoples R China

ISBN: (纸本)9783037852330

On the basis of lumped parameter model and the Lagrange method, the model of powertrain was built. Resonance vibration response and non-resonance vibration response were calculated respectively in time domain and frequency domain, characteristics of forced torsional vibration in steady state were concluded. Comparability and difference of response of parts in different stage were explained. multi-object optimization was applied to reduce vibration.

关键词： multi-stage planetary gears forced torsional vibration multi-object optimization

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Determining Thresholds in Three-Way Decisions: A multi-object optimization View 1

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International Joint Conference on Rough Sets (IJCRS)

作者： Zhang, Yuanjian Miao, Duoqian Xu, Jianfeng Zhang, Zhifei Tongji Univ Dept Comp Sci & Technol Shanghai 201804 Peoples R China Tongji Univ Key Lab Embedded Syst & Serv Comp Minist Educ Shanghai 201804 Peoples R China Tongji Univ Big Data & Network Secur Res Ctr Shanghai 200092 Peoples R China

ISBN: (数字)9783319608402

ISBN: (纸本)9783319608402;9783319608396

Determination of thresholds is recognized as a fundamental problem in decision-theoretic rough sets. Traditionally, thresholds are determined by observing Bayesian decision theory. Although the semantic seems to be enriched as compared to probabilistic rough sets, the functionality of risk is not comprehensively explored. In allusion to this situation, we develop a multi-object optimization view based model on determining thresholds. By generalizing the expected loss function to target function, this model claims that thresholds in three-way are radically constructed by pair-wise region-based target functions. By transferring the principle of pair-wise region-based target functions on multi-quantitative scenario, we present a finer-grained formulation for thresholds solving. Furthermore, we investigate the multi-layer of presented model. Finally, the optimistic and pessimistic multi-quantitative decision-theoretic rough set is defined to illustrate the value of presented model.

关键词： Three-way decisions Decision-theoretic rough sets multi-object optimization multi-quantitative

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Research on a combined device SMES-SFCL based on multi-object optimization

Research on a combined device SMES-SFCL based on multi-objec...

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2004 Applied Superconductivity Conference

作者： Zhu, GP Wang, ZJ Zhang, GQ Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China Acad China Inst Elect Engn Beijing 10084 Peoples R China

关键词： multi-object optimization SFCL SMES

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