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Simulation and evaluation of tomato growth by AquaCrop model under different agricultural waste materials

International Journal of Agricultural and Biological Engineering 2024年第5期17卷 112-119页

作者： Changquan Zhou Wenju Zhao Haolin Li Feng Ma Keqian Wu College of Energy and Power Engineering Lanzhou University of TechnologyLanzhou 730050China Key Laboratory of Smart Agriculture Irrigation Equipment Ministry of Agriculture and Rural AffairsLanzhou 730050China College of Civil Engineering Lanzhou University of Information Science and TechnologyLanzhou 730300China College of Environmental Science and Energy Engineering Beijing University of TechnologyBeijing 100124China College of Water Resources and Civil Engineering China Agricultural UniversityBeijing 100083China

This study aimed to enhance the utilization of agricultural waste and identify the most suitable agricultural waste materials for tomato cultivation. It utilized a locally modified substrate labeled as CK, along with five different groups of agricultural waste materials, designated as T1 (organic fertilizer: loessial soil: straw in a ratio of 4:5:1), T2 (organic fertilizer: loessial soil: straw: grains in a ratio of 3:5:1:1), T3 (organic fertilizer: loessial soil: straw: grains in a ratio of 2:5:1:2), T4 (organic fertilizer:loessial soil:straw:grains in a ratio of 1:5:1:3), and T5 ( loessial soil:straw:grains in a ratio of 5:1:4), the AquaCrop model was employed to validate soil water content and tomato growth and yield under these treatments. Furthermore, a multi-objective genetic algorithm was employed to determine the optimal agricultural waste materials that would ensure maximum tomato yield, water use efficiency (WUE), partial factor productivity of fertilizer (PFP) and sugar-acid ratio. The results indicated that the AquaCrop model reasonably simulated volumetric soil water content, tomato canopy cover, and biomass, with root mean square error (RMSE) ranges of 20.0-69.4 mm, 15.2%-25.1%, and 1.093-3.469 t/hm2, respectively. The CK group exhibited an R-squared (R2) value of 0.63 for volumetric soil water contents, while the ratio scenarios showed R2 values exceeding 0.80. The multi-objective genetic optimization algorithm identified T5 as the optimal ratio scenario, resulting in maximum tomato yield, WUE, PFP, and quality. This study offers a theoretical foundation for the efficient utilization of agricultural wastes and the production of high-quality fruits and vegetables.

关键词： agricultural waste materials AquaCrop model nsga-ii algorithm tomato quality

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Multi-Objective Complete Fuzzy Clustering Approach

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INTELLIGENT AUTOMATION AND SOFT COMPUTING 2017年第2期23卷 285-294页

作者： Shahsamandi, Parastou E. Sadi-nezhad, Soheil Saghaei, Abbas Islamic Azad Univ Sci & Res Branch Dept Ind Engn Tehran Iran Univ Waterloo Dept Stat & Actuarial Sci Toronto ON Canada

The process of data clustering has mainly focused on optimizing a single objective function, and thus, some information is not used for clustering. Therefore, the aim of this study is to propose a multi-objective complete fuzzy clustering model (MoCFC) that simultaneously optimizes data compactness, separation, and connectedness. The model employs two optimization algorithms;AUGMECON and nsga-ii. Using some fuzzy datasets, the results show that AUGMECON has lower convergence and coverage than nsga-ii, but a higher success index. Moreover, in terms of various cluster validity indices, AUGMECON achieves better performance. However, nsga-ii is the better choice if execution time is critical.

关键词： Fuzzy clustering Multi-objective optimization nsga-ii algorithm epsilon-constraint method Fuzzy data Cluster connectedness Cluster compactness Cluster separation

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Capacity and Volume Balance of Buffering Converters for the Marine Pulsed Power System

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2023年第1期70卷 322-333页

作者： Sun, Lei Huang, Wentao Li, Ran Gao, Fei Tai, Nengling Yu, Moduo Shanghai Jiao Tong Univ Key Lab Power Transmiss & Convers Control Minist Educ Shanghai 200240 Peoples R China

In marine integrated power systems (IPS), dc/dc converters have been widely used to buffer the power of pulsed loads. However, limited by ship space and safety, its buffering capacity and volume are conflicting and need to be balanced. Existing methods usually oversimplify the switching dynamic process caused by the different switching periods between the pulsed loads and converters, leading to oversizing or underpowering issues of the converts. To overcome this hurdle, this article proposes a millisecond-time-scale-based state-space averaging mode (MTS-SSAM) to analyze the dynamic process by taking pulsed loads period instead of the traditional converter period as the averaging operator. Based on MTS-SSAM, taking the system allowable voltage and current fluctuation rate and converter volume as the objective function, the converters' parameters are optimized considering the balance between buffering capacity and volume. The proposed parameters optimization method can save 49% converter volume compared with existing methods. The simulation and experimental results are presented to verify the proposed SSAM and optimization method.

关键词： Power system dynamics Capacitors Switches Voltage Load modeling Pulse width modulation Periodic structures Dynamic process millisecond-time-scale-based state-space averaging mode (MTS-SSAM) nsga-ii algorithm parameters optimization method pulsed power system

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Simulation-optimization approach for the multi-objective production and distribution planning problem in the supply chain: using nsga-ii and Monte Carlo simulation

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SOFT COMPUTING 2022年第17期26卷 8661-8687页

作者： Kabiri, Niloofar Nadim Emami, Saeed Safaei, Abdul Sattar Babol Noshiravani Univ Technol Dept Ind Engn Babol *** Iran

With the growth of multinational companies, increasing international and domestic competition between companies, upgrading information technology, and increasing customer expectations, accurate supply chain (SC) planning is essential. In such an environment, pollution has become more severe in recent decades, and with the weakening of the environment and global warming, green SC management strategies have become significant issues in recent decades. In this research, we consider the integrated production and distribution planning problem of a multi-level green closed-loop SC system, which includes multiple recycling, manufacturing/ remanufacturing, and distribution centers. We present a three-level bi-objective programming model to maximize profit and minimize the amount of greenhouse gas emissions. A hierarchical iterative approach utilizing the LP-metric method and the non-dominated sorting genetic algorithm (nsga-ii) is introduced to solve the proposed model. The Taguchi approach is applied to find optimum control parameters of nsga-ii. Moreover, Monte Carlo (MC) simulation is applied to tackle uncertainty in demand, and the nsga-ii algorithm is integrated with MC simulation (MCnsga-ii). Through numerical experiments on randomly generated instances, we observe that the average of the relative gaps nsga-ii and LP-metric method are 7%, 7%, and 1% for the three levels, respectively. Furthermore, it is observed that the value of convergence (C) and spacing (S) metrics of the MCnsga-ii algorithm are 0 and 1.82E + 07, which are better than nsga-ii.

关键词： Production and distribution planning Simulation-optimization Green closed-loop supply chain Monte Carlo simulation Three-level bi-objective programming nsga-ii algorithm

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THE OPEN LOCATION-ROUTING PROBLEM FOR MULTI-OBJECTIVE OPTIMIZATION OF SUSTAINABLE SUPPLY CHAIN CONSIDERING SOCIAL CONCERNS

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JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION 2023年第10期19卷 7423-7446页

作者： Eydi, Alireza Mansouri, Zahra Univ Kurdistan Fac Engn Sanandaj Iran Univ Kurdistan Ind Engn Sanandaj Iran

Taking into account the variety of real-world constraints and in-corp orating them into classical problems are essential in designing supply chain networks. Meanwhile, given the importance of outsourcing, the open location-routing problem (OLRP) is proposed to fulfill customers' demands and mini-mize costs by determining the optimal location of vehicle facilities and routes. In addition, supply chain sustainability is attracting increasing attention since it promotes a bright future for the coming generations by striking a balance between economic, environmental, and social performances in supply chain design. In this study, we contribute to the scarce literature on supply chain sustainability and OLRP. First, using OLRP, we model a sustainable supply chain that addresses all sustainability pillars. Second, we use the nsga-ii meta-heuristic method to solve the proposed model and finally compare its ef-ficiency with Cplex. The model characterized in this study can be considered a basic reference on the subject of supply chain sustainability and OLRP. More-over, we indicate that both of the proposed solution methods are capable of solving the developed model;however, the meta-heuristic method, nsga-ii, is significantly more efficient than the classical one, Cplex, in terms of compu-tation time, particularly in solving medium-and large-scale problems.

关键词： Sustainable supply chain management environmental and social im-pacts multi-objective optimization open location-routing nsga-ii algorithm

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Investigation of a falling film tube bank heat exchanger with baffle design for water recovery applications

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Energy and Built Environment 2024年第5期5卷 817-828页

作者： Liang Tang Xiaoling Cao Wei Zhong Long Yu Linlin Yin Shandong Electric Power Engineering Consulting Institute Corp. LTD.Jinan 250013PR China School of Mechanical Engineering Southwest Jiaotong UniversityChengdu 610031PR China

Shell and tube heat exchangers(STHE)are essential thermal equipment and widely used in daily life.A novel thermosyphon system called falling-film thermosyphon(FFTS)is introduced and integrated into STHE system,resulting in a better thermal *** this study,a rectangular solid tube bank of FFTS bundles with a baffle design is *** numerical simulation for heat and mass transfer of the FFTS heat exchanger is developed to predict the condensation rate of the vapor in the flue gas,and a lab-scale prototype is also built up in *** prediction is validated with the experimental data from references,and the model’s accuracy is verified within 10%-12%***,the Non-dominated Sorting Genetic algorithm,version 2(nsga-ii)is implemented to improve the thermal performance of rectangular tube banks in this *** parameters,e.g.,baffle number,tube number,and tube space,are *** a result,compact configurations with more baffles are preferred to enhance the performance associated with a high-pressure drop *** optimized layout for the lab-scale prototype can increase by 18 to 32%condensation with a pressure loss of less than 200 Pa.

关键词： Falling film Heat transfer Condensation nsga-ii algorithm Heat exchanger

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Multi-objective optimization of customized bus routes based on full operation process

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MODERN PHYSICS LETTERS B 2020年第25期34卷

作者： Wang, Chao Ma, Changxi Lanzhou Jiaotong Univ Sch Traff & Transportat Lanzhou 730070 Peoples R China

In order to rationally formulate a customized bus route plan to improve the operation efficiency of customized buses, in view of the problem of ignoring the distance between the boarding area and the alighting area, and setting it as a fixed value when performing custom bus route optimization modeling, as well as solving the problem of multiple custom bus parking lots. This paper proposes a method based on the nsga-ii algorithm using a three-stage hybrid coding method to solve. First, according to real life, the entire operation process of customized buses is divided into four phases. Second, based on the four stages, a multi-objective optimization model of customized bus routes that satisfies multiple parking lots, multiple cars, and multiple boarding and alighting stations is constructed to pursue the minimum total travel time of passengers and minimizes the operating costs of customized bus companies. Third, the nsga-ii algorithm is employed to solve the model, including three-stage hybrid coding, segmented crossover, and segmented mutation operators. Finally, the local road network in Lanzhou City is adopted for simulation research. The results show that it is feasible to use nsga-ii algorithm to solve the problem of customizing bus routes for multiple parking lots, multiple vehicles, and multiple boarding and alighting stations. The research results are of great value for exploring the optimization methods of customized bus routes and improving the operating efficiency of custom buses.

关键词： Customized bus multi-objective route optimization model full operation process nsga-ii algorithm three-stage hybrid coding

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Multi objective optimization model and algorithm of logistics service transaction matching on blockchain platform

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JOURNAL OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2021年第6期21卷 1843-1855页

作者： Wang, Xiaokun Zhao, Chenxi Wang, Yuan Xiao, Hong Dalian Jiaotong Univ Sch Econ & Management Dalian Liaoning Peoples R China Dalian Jiaotong Univ Res Inst Belt & Rd Dalian Liaoning Peoples R China Chongqing Jiaotong Univ Sch Econ & Management Chongqing 400074 Peoples R China

The logistics service transaction matching of the blockchain platform is an important part of the transaction. Firstly, the evaluation index system of the logistics service transaction satisfaction degree in the blockchain platform is constructed. According to the evaluation index of the logistics service users and providers, the actual situation of the logistics service transaction and the principle of maximizing the satisfaction degree of the logistics service users and providers, we set the expectation range of both sides and do data standardization, design the calculation method of satisfaction information amount for different expectation data types, build a multi-objective optimization model for logistics service transaction matching on blockchain platform, and seek the matching solution that makes all service users and providers the most satisfaction. Considering the large amount of data in blockchain, the concurrent design of nsga-ii algorithm based on Hadoop is carried out. Through the calculation of the example, in the matching of multi-objective optimization model of logistics service transaction matching on the blockchain platform, when the users and providers of logistics service are more satisfied about the indicators with each other, and then it gets more satisfactory matching results.

关键词： Blockchain platform logistics service satisfaction transaction matching model nsga-ii algorithm

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Multi-objective dragonfly algorithm for optimizing a sustainable supply chain under resource sharing conditions

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COMPUTERS & INDUSTRIAL ENGINEERING 2024年 187卷

作者： Golmohammadi, Amir-Mohammad Abedsoltan, Hamidreza Goli, Alireza Ali, Irfan Arak Univ Dept Ind Engn Arak Iran Univ Tehran Coll Engn Sch Ind Engn Tehran Iran Univ Isfahan Fac Engn Dept Ind Engn & Future Studies Esfahan Iran Aligarh Muslim Univ Dept Stat & Operat Res Aligarh 202002 India

This research addresses optimizing production, inventory, location, and routing in a multi-level supply chain. In the studied supply chain, products are first sent to several distribution centers (DC) after production. Next, these products are delivered to several companies. Companies are divided into two independent groups considering sharing logistics resources. In this regard, vehicle routing optimization is applied for each group. For this pur -pose, a mixed-integer linear programming model has been developed. This model simultaneously minimizes total supply chain costs and total negative environmental impacts. A multi-objective dragonfly algorithm (MODA) has been developed to solve this model. Then, the implementation results are compared with the Non-Dominated Sorting Genetic algorithm and Epsilon Constraint Method (EPC). Comparing the solution methods based on numerous test problems shows that the proposed MODA algorithm can be examined differently. The MODA algorithm has been able to have a significant advantage in providing solutions close to ideal points. Moreover, this algorithm has provided the most effective Pareto solutions in different test problems. However, the nsga-ii algorithm performs better regarding the spread of non-dominated solutions.

关键词： Shared logistics Location and routing Supply chain Multi-objective dragonfly algorithm nsga-ii algorithm Epsilon Constraint Method

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A Maximal Covering Problem in Supply Chain Considering Variable Radius and Gradual Coverage with the Choice of Transportation Mode

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ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2019年第8期44卷 7219-7233页

作者： Eydi, Alireza Torabi, Hossein Univ Kurdistan Dept Ind Engn Sanandaj Iran Univ Kurdistan Fac Engn Ind Engn Sanandaj Iran

Today, supply chain management is a fundamental principle of business infrastructure implementation in the world. One of the most important pillars of the supply chain management is distribution network design. A distribution network with appropriate structure reduces costs and enhances customer-perceived service level, thereby improving competitive advantages of the company. In supply chain analysis, it is essential to focus on customers, as they greatly affect the formation of chain. This requires a balance between associated costs and the level of service provided. Variable radius and gradual radius maximal covering problem focus on the service levels in relation to the costs incurred to the system. In this study, a bi-objective mixed-integer nonlinear programming model was presented to determine optimal number, location and capacity of factories, distribution centers, and retailers, select transportation modes between the chain elements, and evaluate coverage radius of retailers, in such a way to minimize total transportation costs, maximize the covered demand, and achieve gradual coverage of facilities in a variable radius scheme. The proposed model was validated on a number of sample problems produced and solved by GAMS optimization software. Being NP-Hard, the problem was proposed to be solved via nsga-ii algorithm when its dimensions go large. Analysis of the computational results and respective comparisons indicated good performance of the presented algorithm.

关键词： Supply chain design Multi-objective Variable radius and gradual covering Transportation mode selection nsga-ii algorithm

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