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Prediction Model-based Multi-objective Optimization for Mix-ratio Design of Recycled Aggregate Concrete
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作者 CHEN Tao WU Di YAO Xiaojun 《Journal of Wuhan University of Technology(Materials Science)》 SCIE EI CAS CSCD 2024年第6期1507-1517,共11页
The prediction model for mechanical properties of RAC was established through the Bayesian optimization-based Gaussian process regression(BO-GPR)method,where the input variables in BO-GPR model depend on the mix ratio... The prediction model for mechanical properties of RAC was established through the Bayesian optimization-based Gaussian process regression(BO-GPR)method,where the input variables in BO-GPR model depend on the mix ratio of concrete.Then the compressive strength prediction model,the material cost,and environmental factors were simultaneously considered as objectives,while a multi-objective gray wolf optimization algorithm was developed for finding the optimal mix ratio.A total of 730 RAC datasets were used for training and testing the predication model,while the optimal design method for mix ratio was verified through RAC experiments.The experimental results show that the predicted,testing,and expected compressive strengths are nearly consistent,illustrating the effectiveness of the proposed method. 展开更多
关键词 recycled coarse aggregate mix ratio multi-objective optimization prediction model compressive strength
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A modified back analysis method for deep excavation with multi-objective optimization procedure
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作者 Chenyang Zhao Le Chen +2 位作者 Pengpeng Ni Wenjun Xia Bin Wang 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2024年第4期1373-1387,共15页
Real-time prediction of excavation-induced displacement of retaining pile during the deep excavation process is crucial for construction safety.This paper proposes a modified back analysis method with multi-objective ... Real-time prediction of excavation-induced displacement of retaining pile during the deep excavation process is crucial for construction safety.This paper proposes a modified back analysis method with multi-objective optimization procedure,which enables a real-time prediction of horizontal displacement of retaining pile during construction.As opposed to the traditional stage-by-stage back analysis,time series monitoring data till the current excavation stage are utilized to form a multi-objective function.Then,the multi-objective particle swarm optimization (MOPSO) algorithm is applied for parameter identification.The optimized model parameters are immediately adopted to predict the excavation-induced pile deformation in the continuous construction stages.To achieve efficient parameter optimization and real-time prediction of system behavior,the back propagation neural network (BPNN) is established to substitute the finite element model,which is further implemented together with MOPSO for automatic operation.The proposed approach is applied in the Taihu tunnel excavation project,where the effectiveness of the method is demonstrated via the comparisons with the site monitoring data.The method is reliable with a prediction accuracy of more than 90%.Moreover,different optimization algorithms,including non-dominated sorting genetic algorithm (NSGA-II),Pareto Envelope-based Selection Algorithm II (PESA-II) and MOPSO,are compared,and their influences on the prediction accuracy at different excavation stages are studied.The results show that MOPSO has the best performance for high dimensional optimization task. 展开更多
关键词 multi-objective optimization Back analysis Surrogate model multi-objective particle swarm optimization(MOPSO) Deep excavation
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Multi-Objective Optimization of Aluminum Alloy Electric Bus Frame Connectors for Enhanced Durability
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作者 Wenjun Zhou Mingzhi Yang +3 位作者 Qian Peng Yong Peng Kui Wang Qiang Xiao 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第7期735-755,共21页
The widespread adoption of aluminumalloy electric buses,known for their energy efficiency and eco-friendliness,faces a challenge due to the aluminum frame’s susceptibility to deformation compared to steel.This issue ... The widespread adoption of aluminumalloy electric buses,known for their energy efficiency and eco-friendliness,faces a challenge due to the aluminum frame’s susceptibility to deformation compared to steel.This issue is further exacerbated by the stringent requirements imposed by the flammability and explosiveness of batteries,necessitating robust frame protection.Our study aims to optimize the connectors of aluminum alloy bus frames,emphasizing durability,energy efficiency,and safety.This research delves into Multi-Objective Coordinated Optimization(MCO)techniques for lightweight design in aluminum alloy bus body connectors.Our goal is to enhance lightweighting,reinforce energy absorption,and improve deformation resistance in connector components.Three typical aluminum alloy connectors were selected and a design optimization platform was built for their MCO using a variety of software and methods.Firstly,through three-point bending experiments and finite element analysis on three types of connector components,we identified optimized design parameters based on deformation patterns.Then,employing Optimal Latin hypercube design(OLHD),parametric modeling,and neural network approximation,we developed high-precision approximate models for the design parameters of each connector component,targeting energy absorption,mass,and logarithmic strain.Lastly,utilizing the Archive-based Micro Genetic Algorithm(AMGA),Multi-Objective Particle Swarm Optimization(MOPSO),and Non-dominated SortingGenetic Algorithm(NSGA2),we explored optimized design solutions for these joint components.Subsequently,we simulated joint assembly buckling during bus rollover crash scenarios to verify and analyze the optimized solutions in three-point bending simulations.Each joint component showcased a remarkable 30%–40%mass reduction while boosting energy absorption.Our design optimization method exhibits high efficiency and costeffectiveness.Leveraging contemporary automation technology,the design optimization platform developed in this study is poised to facilitate intelligent optimization of lightweight metal components in future applications. 展开更多
关键词 Aluminum connectors three-point bending simulation parametric design model multi-objective collaborative optimization
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Review of multi-objective optimization in long-term energy system models
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作者 Wenxin Chen Hongtao Ren Wenji Zhou 《Global Energy Interconnection》 EI CSCD 2023年第5期645-660,共16页
Modeling and optimizing long-term energy systems can provide solutions to various energy and environmental policies involving public-interest issues.The conventional optimization of long-term energy system models focu... Modeling and optimizing long-term energy systems can provide solutions to various energy and environmental policies involving public-interest issues.The conventional optimization of long-term energy system models focuses on a single economic goal.However,the increasingly complex demands of energy systems necessitate the comprehensive consideration of multiple dimensional objectives,such as environmental,social,and energy security.Therefore,a multi-objective optimization of long-term energy system models has been developed.Herein,studies pertaining to the multi-objective optimization of long-term energy system models are summarized;the optimization objectives of long-term energy system models are classified into economic,environmental,social,and energy security aspects;and the multi-objective optimization methods are classified and explained based on the preferential expression of decision makers.Finally,the key development direction of the multi-objective optimization of energy system models is discussed. 展开更多
关键词 Long-term energy system models multi-objective optimization Energy security
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Research Progress of Aerodynamic Multi-Objective Optimization on High-Speed Train Nose Shape 被引量:1
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作者 Zhiyuan Dai Tian Li +1 位作者 Weihua Zhang Jiye Zhang 《Computer Modeling in Engineering & Sciences》 SCIE EI 2023年第11期1461-1489,共29页
The aerodynamic optimization design of high-speed trains(HSTs)is crucial for energy conservation,environmental preservation,operational safety,and speeding up.This study aims to review the current state and progress o... The aerodynamic optimization design of high-speed trains(HSTs)is crucial for energy conservation,environmental preservation,operational safety,and speeding up.This study aims to review the current state and progress of the aerodynamic multi-objective optimization of HSTs.First,the study explores the impact of train nose shape parameters on aerodynamic performance.The parameterization methods involved in the aerodynamic multiobjective optimization ofHSTs are summarized and classified as shape-based and disturbance-based parameterizationmethods.Meanwhile,the advantages and limitations of each parameterizationmethod,aswell as the applicable scope,are briefly discussed.In addition,the NSGA-II algorithm,particle swarm optimization algorithm,standard genetic algorithm,and other commonly used multi-objective optimization algorithms and the improvements in the field of aerodynamic optimization for HSTs are summarized.Second,this study investigates the aerodynamic multi-objective optimization technology for HSTs using the surrogate model,focusing on the Kriging surrogate models,neural network,and support vector regression.Moreover,the construction methods of surrogate models are summarized,and the influence of different sample infill criteria on the efficiency ofmulti-objective optimization is analyzed.Meanwhile,advanced aerodynamic optimization methods in the field of aircraft have been briefly introduced to guide research on the aerodynamic optimization of HSTs.Finally,based on the summary of the research progress of the aerodynamicmulti-objective optimization ofHSTs,future research directions are proposed,such as intelligent recognition technology of characteristic parameters,collaborative optimization of multiple operating environments,and sample infill criterion of the surrogate model. 展开更多
关键词 High-speed train multi-objective optimization PARAMETERIZATION optimization algorithm surrogate model sample infill criterion
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Principal-subordinate hierarchical multi-objective programming model of initial water rights allocation 被引量:5
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作者 Dan WU Feng-ping WU Yan-ping CHEN 《Water Science and Engineering》 EI CAS 2009年第2期105-116,共12页
The principal-subordinate hierarchical multi-objective programming model of initial water rights allocation was developed based on the principle of coordinated and sustainable development of different regions and wate... The principal-subordinate hierarchical multi-objective programming model of initial water rights allocation was developed based on the principle of coordinated and sustainable development of different regions and water sectors within a basin. With the precondition of strictly controlling maximum emissions rights, initial water rights were allocated between the first and the second levels of the hierarchy in order to promote fair and coordinated development across different regions of the basin and coordinated and efficient water use across different water sectors, realize the maximum comprehensive benefits to the basin, promote the unity of quantity and quality of initial water rights allocation, and eliminate water conflict across different regions and water sectors. According to interactive decision-making theory, a principal-subordinate hierarchical interactive iterative algorithm based on the satisfaction degree was developed and used to solve the initial water rights allocation model. A case study verified the validity of the model. 展开更多
关键词 initial water rights allocation principal-subordinate hierarchy multi-objective programming model satisfaction degree
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Multi-objective Optimization Design of Wing Structure with the Model Management Framework 被引量:3
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作者 安伟刚 李为吉 苟仲秋 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2006年第1期31-35,共5页
Evolutionary algorithm is time-consuming because of the large number of evolutions and much times of finite element analysis, when it is used to optimize the wing structure of a certain high altitude long endurance un... Evolutionary algorithm is time-consuming because of the large number of evolutions and much times of finite element analysis, when it is used to optimize the wing structure of a certain high altitude long endurance unmanned aviation vehicle(UAV). In order to improve efficiency it is proposed to construct a model management framework to perform the multi-objective optimization design of wing structure. The sufficient accurate approximation models of objective and constraint functions in the wing structure optimization model are built when using the model management framework, therefore in the evolutionary algorithm a number of finite element analyses can he avoided and the satisfactory multi-objective optimization results of the wing structure of the high altitude long endurance UAV are obtained. 展开更多
关键词 wing structure UAV multi-objective opti-mization model management framework SM- MOPSO
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A vague-set-based fuzzy multi-objective decision making model for bidding purchase 被引量:4
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作者 WANG Zhou-jing QIAN Edward Y. 《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》 SCIE EI CAS CSCD 2007年第4期644-650,共7页
A vague-set-based fuzzy multi-objective decision making model is developed for evaluating bidding plans in a bid- ding purchase process. A group of decision-makers (DMs) first independently assess bidding plans accord... A vague-set-based fuzzy multi-objective decision making model is developed for evaluating bidding plans in a bid- ding purchase process. A group of decision-makers (DMs) first independently assess bidding plans according to their experience and preferences, and these assessments may be expressed as linguistic terms, which are then converted to fuzzy numbers. The resulting decision matrices are then transformed to objective membership grade matrices. The lower bound of satisfaction and upper bound of dissatisfaction are used to determine each bidding plan’s supporting, opposing, and neutral objective sets, which together determine the vague value of a bidding plan. Finally, a score function is employed to rank all bidding plans. A new score function based on vague sets is introduced in the model and a novel method is presented for calculating the lower bound of sat- isfaction and upper bound of dissatisfaction. In a vague-set-based fuzzy multi-objective decision making model, different valua- tions for upper and lower bounds of satisfaction usually lead to distinct ranking results. Therefore, it is crucial to effectively contain DMs’ arbitrariness and subjectivity when these values are determined. 展开更多
关键词 Fuzzy multi-objective decision making model Vague set Score function Lower bound of satisfaction Upper bound of dissatisfaction
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The Information Modeling and Intelligent Optimization Method for Logistics Vehicle Routing and Scheduling with Multi-objective and Multi-constraint 被引量:2
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作者 李蓓智 周亚勤 +1 位作者 兰世海 杨建国 《Journal of Donghua University(English Edition)》 EI CAS 2007年第4期455-459,466,共6页
The vehicle routing and scheduling (VRS) problem with multi-objective and multi-constraint is analyzed, considering the complexity of the modern logistics in city economy and daily life based on the system engineering... The vehicle routing and scheduling (VRS) problem with multi-objective and multi-constraint is analyzed, considering the complexity of the modern logistics in city economy and daily life based on the system engineering. The objective and constraint includes loading, the dispatch and arrival time, transportation conditions,total cost,etc. An information model and a mathematical model are built,and a method based on knowledge and biologic immunity is put forward for optimizing and evaluating the programs dimensions in vehicle routing and scheduling with multi-objective and multi-constraints. The proposed model and method are illustrated in a case study concerning a transport network, and the result shows that more optimization solutions can be easily obtained and the method is efficient and feasible. Comparing with the standard GA and the standard GA without time constraint,the computational time of the algorithm is less in this paper. And the probability of gaining optimal solution is bigger and the result is better under the condition of multi-constraint. 展开更多
关键词 modern logistics vehicle scheduling routing optimization multi-objective multi-constraint biologic immunity information modeling
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Optimization of the Hydrological Model Using Multi-objective Particle Swarm Optimization Algorithm 被引量:2
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作者 黄晓敏 雷晓辉 +1 位作者 王宇晖 朱连勇 《Journal of Donghua University(English Edition)》 EI CAS 2011年第5期519-522,共4页
An application of multi-objective particle swarm optimization (MOPSO) algorithm for optimization of the hydrological model (HYMOD) is presented in this paper. MOPSO algorithm is used to find non-dominated solution... An application of multi-objective particle swarm optimization (MOPSO) algorithm for optimization of the hydrological model (HYMOD) is presented in this paper. MOPSO algorithm is used to find non-dominated solutions with two objectives: high flow Nash-Sutcliffe efficiency and low flow Nash- Sutcliffe efficiency. The two sets' coverage rate and Pareto front spacing metric are two criterions to analyze the performance of the algorithms. MOPSO algorithm surpasses multi-objective shuffled complex evolution metcopolis (MOSCEM_UA) algorithr~, in terms of the two sets' coverage rate. But when we come to Pareto front spacing rate, the non-dominated solutions of MOSCEM_ UA algorithm are better-distributed than that of MOPSO algorithm when the iteration is set to 40 000. In addition, there are obvious conflicts between the two objectives. But a compromise solution can be acquired by adopting the MOPSO algorithm. 展开更多
关键词 multi-objective particle swarm optimization (MOPSO) hydrological model (HYMOD) multi-objective optimization
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A New Definition and Calculation Model for Evolutionary Multi-Objective Optimization 被引量:1
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作者 Zhou Ai-min, Kang Li-shan, Chen Yu-ping, Huang Yu-zhenState Key Laboratory of Software Engineering, Wuhan University, Wuhan 430072, Hubei, China 《Wuhan University Journal of Natural Sciences》 CAS 2003年第S1期189-194,共6页
We present a new definition (Evolving Solutions) for Multi-objective Optimization Problem (MOP) to answer the basic question (what's multi-objective optimal solution?) and advance an asynchronous evolutionary mode... We present a new definition (Evolving Solutions) for Multi-objective Optimization Problem (MOP) to answer the basic question (what's multi-objective optimal solution?) and advance an asynchronous evolutionary model (MINT Model) to solve MOPs. The new theory is based on our understanding of the natural evolution and the analysis of the difference between natural evolution and MOP, thus it is not only different from the Converting Optimization but also different from Pareto Optimization. Some tests prove that our new theory may conquer disadvantages of the upper two methods to some extent. 展开更多
关键词 evolving equilibrium evolving solutions MINT model multi-objective optimization
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Multi-objective nonlinear model predictive control through switching cost functions and its applications to chemical processes 被引量:1
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作者 何德峰 余世明 俞立 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2015年第10期1662-1669,共8页
This paper proposes a switching multi-objective model predictive control(MOMPC) algorithm for constrained nonlinear continuous-time process systems.Different cost functions to be minimized in MPC are switched to satis... This paper proposes a switching multi-objective model predictive control(MOMPC) algorithm for constrained nonlinear continuous-time process systems.Different cost functions to be minimized in MPC are switched to satisfy different performance criteria imposed at different sampling times.In order to ensure recursive feasibility of the switching MOMPC and stability of the resulted closed-loop system,the dual-mode control method is used to design the switching MOMPC controller.In this method,a local control law with some free-parameters is constructed using the control Lyapunov function technique to enlarge the terminal state set of MOMPC.The correction term is computed if the states are out of the terminal set and the free-parameters of the local control law are computed if the states are in the terminal set.The recursive feasibility of the MOMPC and stability of the resulted closed-loop system are established in the presence of constraints and arbitrary switches between cost functions.Finally,implementation of the switching MOMPC controller is demonstrated with a chemical process example for the continuous stirred tank reactor. 展开更多
关键词 Nonlinear system model predictive control multi-objective control Switched control Continuous stirred tank reactor
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Multi-objective planning model for simultaneous reconfiguration of power distribution network and allocation of renewable energy resources and capacitors with considering uncertainties 被引量:9
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作者 Sajad Najafi Ravadanegh Mohammad Reza Jannati Oskuee Masoumeh Karimi 《Journal of Central South University》 SCIE EI CAS CSCD 2017年第8期1837-1849,共13页
This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously a... This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously and to improve power system's accountability and system performance parameters. Due to finding solution which is closer to realistic characteristics, load forecasting, market price errors and the uncertainties related to the variable output power of wind based DG units are put in consideration. This work employs NSGA-II accompanied by the fuzzy set theory to solve the aforementioned multi-objective problem. The proposed scheme finally leads to a solution with a minimum voltage deviation, a maximum voltage stability, lower amount of pollutant and lower cost. The cost includes the installation costs of new equipment, reconfiguration costs, power loss cost, reliability cost, cost of energy purchased from power market, upgrade costs of lines and operation and maintenance costs of DGs. Therefore, the proposed methodology improves power quality, reliability and security in lower costs besides its preserve, with the operational indices of power distribution networks in acceptable level. To validate the proposed methodology's usefulness, it was applied on the IEEE 33-bus distribution system then the outcomes were compared with initial configuration. 展开更多
关键词 optimal reconfiguration renewable energy resources sitting and sizing capacitor allocation electric distribution system uncertainty modeling scenario based-stochastic programming multi-objective genetic algorithm
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Multi-objective linear fractional inventory model with possibility and necessity constraints under generalised intuitionistic fuzzy set environment 被引量:1
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作者 Totan Garai Harish Garg 《CAAI Transactions on Intelligence Technology》 2019年第3期175-181,共7页
This study presented a multi-objective linear fractional inventory (LFI) problem with generalised intuitionistic fuzzy numbers. In modelling, the authors have assumed the ambiances where generalised trapezoidal intuit... This study presented a multi-objective linear fractional inventory (LFI) problem with generalised intuitionistic fuzzy numbers. In modelling, the authors have assumed the ambiances where generalised trapezoidal intuitionistic fuzzy numbers (GTIFNs) used to handle the uncertain information in the data. Then, the given multi-objective generalised intuitionistic fuzzy LFI model was transformed into its equivalent deterministic linear fractional programming problem by employing the possibility and necessity measures. Finally, the applicability of the model is demonstrated with a numerical example and the sensitivity analysis under several parameters is investigated to explore the study. 展开更多
关键词 multi-objective linear fractional INVENTORY model POSSIBILITY and NECESSITY CONSTRAINTS generalised intuitionistic fuzzy set ENVIRONMENT
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Improved Genetic Optimization Algorithm with Subdomain Model for Multi-objective Optimal Design of SPMSM 被引量:8
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作者 Jian Gao Litao Dai Wenjuan Zhang 《CES Transactions on Electrical Machines and Systems》 2018年第1期160-165,共6页
For an optimal design of a surface-mounted permanent magnet synchronous motor(SPMSM),many objective functions should be considered.The classical optimization methods,which have been habitually designed based on magnet... For an optimal design of a surface-mounted permanent magnet synchronous motor(SPMSM),many objective functions should be considered.The classical optimization methods,which have been habitually designed based on magnetic circuit law or finite element analysis(FEA),have inaccuracy or calculation time problems when solving the multi-objective problems.To address these problems,the multi-independent-population genetic algorithm(MGA)combined with subdomain(SD)model are proposed to improve the performance of SPMSM such as magnetic field distribution,cost and efficiency.In order to analyze the flux density harmonics accurately,the accurate SD model is first established.Then,the MGA with time-saving SD model are employed to search for solutions which belong to the Pareto optimal set.Finally,for the purpose of validation,the electromagnetic performance of the new design motor are investigated by FEA,comparing with the initial design and conventional GA optimal design to demonstrate the advantage of MGA optimization method. 展开更多
关键词 Improved Genetic Algorithm reduction of flux density spatial distortion sub-domain model multi-objective optimal design
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In silico optimization of actuation performance in dielectric elastomercomposites via integrated finite element modeling and deep learning
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作者 Jiaxuan Ma Sheng Sun 《Theoretical & Applied Mechanics Letters》 CAS CSCD 2024年第1期48-56,共9页
Dielectric elastomers(DEs)require balanced electric actuation performance and mechanical integrity under applied voltages.Incorporating high dielectric particles as fillers provides extensive design space to optimize ... Dielectric elastomers(DEs)require balanced electric actuation performance and mechanical integrity under applied voltages.Incorporating high dielectric particles as fillers provides extensive design space to optimize concentration,morphology,and distribution for improved actuation performance and material modulus.This study presents an integrated framework combining finite element modeling(FEM)and deep learning to optimize the microstructure of DE composites.FEM first calculates actuation performance and the effective modulus across varied filler combinations,with these data used to train a convolutional neural network(CNN).Integrating the CNN into a multi-objective genetic algorithm generates designs with enhanced actuation performance and material modulus compared to the conventional optimization approach based on FEM approach within the same time.This framework harnesses artificial intelligence to navigate vast design possibilities,enabling optimized microstructures for high-performance DE composites. 展开更多
关键词 Dielectric elastomer composites multi-objective optimization Finite element modeling Convolutional neural network
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Selecting China's strategic petroleum reserve sites by multi-objective programming model
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作者 Hui Li Ren-Jin Sun +3 位作者 Kang-Yin Dong Xiu-Cheng Dong Zhong-Bin Zhou Xia Leng 《Petroleum Science》 SCIE CAS CSCD 2017年第3期622-635,共14页
An important decision for policy makers is selecting strategic petroleum reserve sites. However, policy makers may not choose the most suitable and efficient locations for strategic petroleum reserve(SPR) due to the... An important decision for policy makers is selecting strategic petroleum reserve sites. However, policy makers may not choose the most suitable and efficient locations for strategic petroleum reserve(SPR) due to the complexity in the choice of sites. This paper proposes a multi-objective programming model to determine the optimal locations for China's SPR storage sites. This model considers not only the minimum response time but also the minimum transportation cost based on a series of reasonable assumptions and constraint conditions. The factors influencing SPR sites are identified to determine potential demand points and candidate storage sites. Estimation and suggestions are made for the selection of China's future SPR storage sites based on the results of this model. When the number of petroleum storage sites is less than or equals 25 and the maximum capacity of storage sites is restricted to 10 million tonnes, the model's result best fit for the current layout scheme selected thirteen storage sites in four scenarios. Considering the current status of SPR in China,Tianjin, Qingdao, Dalian, Daqing and Zhanjiang, Chengdu,Xi'an, and Yueyang are suggested to be the candidate locations for the third phase of the construction plan. The locations of petroleum storage sites suggested in this work could be used as a reference for decision makers. 展开更多
关键词 Strategic petroleum reserve Storage siteselection multi-objective modeling China
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Multi-Objective Mathematical Model for the Optimal Time to Harvest Sugarcane
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作者 Surattana Sungnul Wisanlaya Pornprakun +1 位作者 Santipong Prasattong Chanasak Baitiang 《Applied Mathematics》 2017年第3期329-343,共15页
In this paper, the sugarcane and sugar industry in Thailand is studied. The government determines the sugarcane prices which is based on the two main factors: 1) weight and 2) commercial cane sugar (standard value equ... In this paper, the sugarcane and sugar industry in Thailand is studied. The government determines the sugarcane prices which is based on the two main factors: 1) weight and 2) commercial cane sugar (standard value equal 10 C.C.S.). Usually, the C.C.S. will increase with time and the weight will decrease. The main purpose of this research is to find the optimal harvest time to maximize revenue and minimize gathering cost. The mathematical model is first formulated under the regulations of the Office of the Cane and Sugar Board (OCSB). The -constraints method is then applied to solve the multi-objective mathematical model. The optimal harvest times in the four regions of Thailand (Northern, Central, Eastern, North-Eastern) for crop years 2012/ 13, 2013/14 and 2014/15 are obtained for comparison. 展开更多
关键词 multi-objective MATHEMATICAL model SUGARCANE ε -Constraint Method
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Multi-objective model of fast-solidification sludge
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作者 周健 刘杰 +2 位作者 李晓品 张永胜 刘轶 《Journal of Central South University》 SCIE EI CAS 2012年第5期1383-1387,共5页
Many sludge curing technologies often have problems like long curing time,high cost,and low efficiency in the condition of low temperature,The compressive strength,moisture content and temperature are defined as the c... Many sludge curing technologies often have problems like long curing time,high cost,and low efficiency in the condition of low temperature,The compressive strength,moisture content and temperature are defined as the constraint conditions,and solidified cost,pH,COD,NH4+-N concentration are defined as the objective functions.The response surface analysis is used to obtain a variety of response expressions of factors,and the multi-objective optimization model of fast-solidification sludge is established.Then,the curing agent formulas are optimized.After three-day conserving,the curing sludge could meet the landfill conditions. 展开更多
关键词 solidified sludge multi-objective model sewage sludge response surface methodology
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Multi-objectives and Simulation Models for Develop Production Line in Automobiles Manufacturing System
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作者 Razman Bin Tahar Ali A. J Adham 《Chinese Business Review》 2011年第7期553-558,共6页
Automotive manufacturing is complex and includes the coordination of design in the manufacturing system. The manufacturing approaches over the past few years, disassembly have been a key issue, and it seems that simul... Automotive manufacturing is complex and includes the coordination of design in the manufacturing system. The manufacturing approaches over the past few years, disassembly have been a key issue, and it seems that simulation models are usually tailored to address a narrow set of industrial issues. This paper describes the development of the production line in the automobile manufacturing system through design, operation, and maintenance, based on multi-objectives of Algorithm and Simulation Model called MOA-SM. The both models are being developed at three different levels: the production line in the body and assembly shop, supply chain, and the production plan. The optimization tries to involve more objectives to solve the issues in manufacturing system. A solution that may optimize one performance measure may deteriorate since other performance solutions are difficult. The resulting algorithms are comparable to the simulation and multi-object in terms of success rate, assembly times, peak forces, moments, and have assembly times superior to those of a benchmark blind search algorithm. 展开更多
关键词 assembly line automotive manufacturing supply chain simulation model multi-objective production line
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