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Nonlinear fusion method for multistage product design decision-making using plant growth simulation algorithm

ADVANCED ENGINEERING INFORMATICS 2022年 53卷

作者： Yang, Yanpu Yang, Qinxia An, Weilan Gong, Zheng Changan Univ Sch Construct Machinery Xian 710064 Peoples R China

Design decision-making is a vital activity for selecting an optimal scheme for product development. Owing to the uncertainty and ambiguity of design requirements and constraints, several product design phases are often deployed for concept refinement, which makes multistage product design decision-making (MPDDM) and the effective fusion of MPDDM data indispensable. However, few existing methods have considered the nonlinear relationships among the MPDDM information. Therefore, a nonlinear fusion method for MPDDM was proposed in this study. This method applies a three-parameter interval grey number to depict decision-makers' judgement about product design schemes. Based on converting linguistic judgements into interval scales, an interval analytic hierarchy process (AHP) method was employed to calculate the weights of the design criteria, decision-makers, and decision-making stages. Considering the advantage of integrating multiple matrices without requiring external control parameters, a multistage decision-making fusion process using a plant growth simulation algorithm (PGSA) was proposed to aggregate multistage decision-making data for product design. A case study was conducted to collect multistage decision-making data, and the PGSA was developed. Through comparison with the extant method, the effectiveness and feasibility of the fusion of MPDDM was verified. The results indicate that (1) uncertainty perceived by decision-makers at three stages accounted for 96.7%, 95%, and 97.2%, respectively. The "center of gravity" of a three-parameter interval grey number, which reflects the largest possibility of decision-makers' preferences, is not always equally distant from its maximum or minimum value (73.9%). (2) The optimization model using interval AHP to calculate the weights of decision-making indicators and stages is conducive to reducing the decision-maker's uncertainty. (3) The global search mechanism of the PGSA can effectively realize the nonlinear fusion of MP

关键词： Product design Decision-making Nonlinear fusion Multistage plant growth simulation algorithm

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A plant growth simulation algorithm FOR DYNAMIC VEHICLE SCHEDULING PROBLEM WITH TIME WINDOW

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INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL 2018年第3期14卷 947-958页

作者： Wang, Yingchen Zhai, Wujuan Geng, Xiaoxiao China Univ Min & Technol Sch Management 1 Daxue Rd Xuzhou 221116 Jiangsu Peoples R China Hebei Univ Engn Sch Management Engn & Business 199 Guangming South St Handan 056038 Peoples R China Hebei Univ Engn Sch Architecture & Art 199 Guangming South St Handan 056038 Peoples R China

We are concerned with dynamic vehicle scheduling problem with time window (VSPTW). Based on practical situations that outsourcing vehicles are limited, delivery staff often work overtime and customer demand is random, a dynamic model based on the time axis is established to minimize the total delivery cost, that is, in this work we extend the classical VSPTW to a dynamic vehicle scheduling problem with time windows. In addition, the plant growth simulation algorithm (PGSA) is designed to solve the formulated dynamic VSPTW. Finally, with a specific example, the designed PGSA is compared with the genetic algorithm. Comparison results show that the algorithm can not only obtain the optimum solution but also improve the efficiency.

关键词： Dynamic vehicle scheduling problem with time windows plant growth simulation algorithm Outsourcing vehicles Overtime delivery

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An object localization optimization technique in medical images using plant growth simulation algorithm

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SPRINGERPLUS 2016年第1期5卷 1-20页

作者： Bhattacharjee, Deblina Paul, Anand Kim, Jeong Hong Kim, Mucheol Kyungpook Natl Univ Dept Comp Sci & Engn Daegu South Korea Sungkyul Univ Dept Media Software Anyang South Korea

The analysis of leukocyte images has drawn interest from fields of both medicine and computer vision for quite some time where different techniques have been applied to automate the process of manual analysis and classification of such images. Manual analysis of blood samples to identify leukocytes is time-consuming and susceptible to error due to the different morphological features of the cells. In this article, the nature-inspired plant growth simulation algorithm has been applied to optimize the image processing technique of object localization of medical images of leukocytes. This paper presents a random bionic algorithm for the automated detection of white blood cells embedded in cluttered smear and stained images of blood samples that uses a fitness function that matches the resemblances of the generated candidate solution to an actual leukocyte. The set of candidate solutions evolves via successive iterations as the proposed algorithm proceeds, guaranteeing their fit with the actual leukocytes outlined in the edge map of the image. The higher precision and sensitivity of the proposed scheme from the existing methods is validated with the experimental results of blood cell images. The proposed method reduces the feasible sets of growth points in each iteration, thereby reducing the required run time of load flow, objective function evaluation, thus reaching the goal state in minimum time and within the desired constraints.

关键词： Nature-inspired computing plant growth simulation algorithm Medical image segmentation Object recognition

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Application of plant growth simulation algorithm

Application of plant growth simulation algorithm

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2016 4th International Conference on Machinery,Materials and Computing Technology(ICMMCT 2016)

作者： Zhenen Fan Gansu Normal University for Nationalities

Permutation flow shop scheduling problem with total flow time criterion has been increasingly dealt with in recent years. A number of heuristics and meta-heuristics have been developed for this problem. However, the calculation of total flow time for job permutations spends too much computational time in the algorithms. Based on plant growth simulation algorithm, we propose a novel algorithm for solving permutation flow shop scheduling problems. The computation experiments based on the well-known benchmarks are provided. simulation results that the plant growth simulation algorithm(PGSA) has better feasibility and validity for solving permutation flow shop scheduling problem.

关键词： plant growth simulation algorithm Permutation flow shop scheduling problem Total flow time Heuristics

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A novel plant growth simulation algorithm and its application

A novel plant growth simulation algorithm and its applicatio...

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2015 International Conference on Advances in Mechanical Engineering and Industrial Informatics(AMEII 2015)

作者： Jun Lu Yueguang Li Gansu political science and law institute

This paper proposes a novel plant growth simulation algorithm. Through the optimization experimental of testing on the standard function, the results show that the novel plant growth simulation algorithm has reliable ... 详细信息

ISBN: (纸本)9781510806481

关键词： plant growth simulation algorithm function Influence factors Intelligent algorithm Test

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Application of plant growth simulation algorithm for permutation flow shop scheduling problem

Application of plant growth simulation algorithm for permuta...

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2015 4th National Conference on Electrical,Electronics and Computer Engineering(NCEECE 2015)

作者： Baohua Yan Gansu Normal University for Nationalities

ISBN: (纸本)9781510819085

Based on plant growth simulation algorithm, we propose a novel algorithm for solving permutation flow shop scheduling problems. Starting with the characteristic of permutation flow shop scheduling problems, combining disjunctive graph according to the sequence of scheduling, analyzing Scheduling options that decided by exchangeable set and alternative set. simulation results that the plant growth simulation algorithm(PGSA) has better feasibility and validity for solving permutation flow shop scheduling problem.

关键词： plant growth simulation algorithm Permutation flow shop scheduling problem intelligent algorithms global optimum problem

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A fuzzy k-coverage approach for RFID network planning using plant growth simulation algorithm

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JOURNAL OF NETWORK AND COMPUTER APPLICATIONS 2014年第1期39卷 280-291页

作者： Lu, Shilei Yu, Shunzheng Sun Yat Sen Univ Sch Informat Sci & Technol Guangzhou 510006 Guangdong Peoples R China

Optimization of network planning is important for the performance improvement of the radio frequency identification (RFID) networks before deployment. This paper proposes an efficient approach for RFID network planning based on k-coverage. A k-coverage model, which is formulated as a multi-dimensional optimization problem with constraint conditions, is developed to evaluate the network performance. The plant growth simulation algorithm (PGSA) is used to optimize the RFID networks by determining the optimal adjustable parameters in the model. In the proposed approach, the objective function and the constraints are separately processed and no external control parameter is required. The simulation results demonstrate the effectiveness of the proposed approach using PGSA in comparison to other algorithms. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： RFID network planning k-Coverage plant growth simulation algorithm Fuzzy optimization

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Research on group decision making with interval numbers based on plant growth simulation algorithm

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KYBERNETES 2014年第2期43卷 250-264页

作者： Li, Lei Xie, Xiaolu Guo, Rui Jiangnan Univ Sch Business Wuxi Peoples R China

Purpose - This paper aims at multi-attribute and multi-program group decision making when the attribute weights are completely unknown and the attribute value information is in the form of the interval number. Design/methodology/approach - This is an artificial intelligence algorithm for designing information gathering in group decision making. The authors propose the nonlinear programming model to gather information based on plant growth simulation algorithm (PGSA). The authors collect each program on each attribute group decision preference ordering interval and then use them to find the preference vector and the preference matrix. The entropy method is used to determine the weight of each attribute by the constructed preference matrix. According to the possibility degree matrix of each attribute, the combined effect vector is established by the priority weight vector method, which sorts and selects the best decision making program. Findings - To the authors' knowledge, the application of PGSA in the field of management decisions to collect program on each attribute group decision making preference interval number is the first trial in literature. It has retained more valuable decision making information from all experts without distortion. Practical implications - In practice, a real number may not be an accurate representation, but only gives a range of values to describe the attributes. This study provides a useful measurement of interval number information for managers to evaluate military science, venture capital, and environmental assessment, etc. Originality/value - The methodology considers the complete information to ensure no information distortion even with large and complex systems. The authors adopt computer artificial intelligence algorithms to obtain the objective evaluation, which is meaningful for both research studies and practical use.

关键词： Entropy method Interval number Large group decision making plant growth simulation algorithm Possibility degree matrix Priority weight vector method

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An algorithm for Cloud-based Web Service Combination Optimization Through plant growth simulation

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系统仿真学报 2025年第2期37卷 462-473页

作者： Li Qiang Qin Huawei Qiao Bingqin Wu Ruifang School of Big Data Shanxi Finance&Taxation CollegeTaiyuan 030027China School of Finance and Economics Taiyuan University of TechnologyTaiyuan 030027China

In order to improve the efficiency of cloud-based web services,an improved plant growth simulation algorithm scheduling *** model first used mathematical methods to describe the relationships between cloud-based web services and the constraints of system ***,a light-induced plant growth simulation algorithm was *** performance of the algorithm was compared through several plant types,and the best plant model was selected as the setting for the *** results show that when the number of test cloud-based web services reaches 2048,the model being 2.14 times faster than PSO,2.8 times faster than the ant colony algorithm,2.9 times faster than the bee colony algorithm,and a remarkable 8.38 times faster than the genetic algorithm.

关键词： cloud-based service scheduling algorithm resource constraint load optimization cloud computing plant growth simulation algorithm

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Improved PGSA algorithm for cable equivalent pre-tension determination of prestressed structure

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STRUCTURES 2025年 72卷

作者： Zhao, Wenyan Zha, Xiaoxiong Pan, Wenzhi Zeng, Yanyan Harbin Inst Technol Sch Civil & Environm Engn Shenzhen 518055 Peoples R China Zhejiang Jinggong Steel Bldg Grp Co Ltd Shaoxing 312030 Peoples R China

Pre-tension is achieved through a sequential tensioning process in prestressed structures. In the simulation of prestressed construction, the cable forces distribution at each phase is predetermined according to the initial conditions outlined in the design schematic such as cable lengths, material properties, and initial tension levels. A key part of this process is the calculation of the equivalent pre-tension for each stage within a specified range to maintain structural stability and prevent damage due to improper tension. Determining the equivalent pretension in prestressed spatial structures is challenging due to the complex, interdependent nature of force. This paper simplifies the problem by reducing it to solving nonlinear implicit equations and then introduces an improved plant growth simulation algorithm (PGSA). The proposed method offers significant advantages in terms of global search ability, computational efficiency, and an effective termination strategy. Using ribbed-type suspended dome structure and cable truss structure as examples, chosen for their complex geometry and significant coupling effects, the paper introduces the process of determining the equivalent pre-tension of the construction completed state. The results show that the pre-tension results obtained by PGSA method closely match theoretical values, compared to Ratio, Compensation and Newton method, while maintaining same accuracy. Furthermore, the algorithm is highly adaptable to different initial values, which is especially useful when initial conditions are uncertain or vary widely, and it demonstrates excellent stability and high efficiency for complex multivariable couple problems.

关键词： Prestressed spatial structures Equivalent pre-tension Force finding analysis plant growth simulation algorithm Numerical analysis

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