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Robust Optimization of Mixed-Load School Bus Route Based on Multi-Objective Genetic algorithm

ENGINEERING LETTERS 2022年第4期30卷 1543-1550页

作者： Zhao, Minghui Zhao, Yongpeng Ma, Changxi Wu, Xu Lanzhou Jiaotong Univ Sch Traff & Transportat Lanzhou 730070 Peoples R China

Various optimization methods for non-mixed-load school bus routes based on certain environments have been applied to practical problems. In practice, school buses can transport students from different schools;however, the travel time is uncertain. This study accounts for the interests of both the students and school bus company using the robust discrete optimization theory of Bertsimas. A robust optimization model of the multi-school mixed-load school bus route under the condition of uncertain road section time impedance is developed considering the minimum travel time of all students and total operating cost of all school buses as optimization goals. Moreover, a two-stage insertion method, nsga-ii, is designed to solve the problem. Then a certain area of Baotou City is considered as an example to conduct empirical research. The study results show that when the robust control parameters are 0, 30, and 60, a vehicle driving route resulting in excellent performance can be rapidly generated. The total travel time of students and total vehicle operational cost were reduced by 12.89% and 8.45%, respectively, compared with those of the multi-objective non-mixed-load school bus route plan. Compared with the multi-objective bat algorithm, nsga-ii saves 27.51% of the solution time. This indicates that the robust optimization of the multi-objective mixed-load school bus route examined in this study provides certain advantages and considerably improves the operating efficiency of the school buses.

关键词： Mixed-load school bus Robust optimization nsga-ii algorithm Route optimization

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Multi-objective Economic-Statistical Design of Cumulative Count of Conforming Control Chart

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INTERNATIONAL JOURNAL OF ENGINEERING 2014年第10期27卷 1591-1600页

作者： Moghaddam, A. Sherbaf Amiri, A. Bashiri, M. Shahed Univ Ind Engn Dept Fac Engn Tehran Iran

Cumulative Count of Conforming (CCC) charts are utilized for monitoring the quality characteristics in high-quality processes. Executive cost of control charts is a motivation for researchers to design them with the lowest cost. Usually, in most researches, only one objective named cost function is minimized subject to statistical constraints, which is not effective method for economic-statistical design of control charts. In this paper, a multi-objective model for the economic-statistical design of the CCC control chart is developed. Then, multi-objective evolutionary algorithm (nsga-ii) for obtaining the Pareto optimal solution of the model is proposed. A numerical example is applied to illustrate the effectiveness of the proposed model. This model leads to lower cost and smaller probability of Type I and Type ii errors, compared with economic model. In addition, a sensitivity analysis is done to investigate the effect of input parameters on the best solutions of the proposed model.

关键词： Statistical Process Control Cumulative Count of Conforming Charts, High-Quality Processes Multi-Objective Economic-Statistical Design nsga-ii algorithm

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Evaluation of the economic statistical design of the multivariate T² control chart with multiple variable sampling intervals scheme: nsga-ii approach

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JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION 2015年第12期85卷 2442-2455页

作者： Seif, Asghar Faraz, Alireza Sadeghifar, Magide Islamic Azad Univ Hamedan Branch Dept Math Hamadan Iran Univ Liege HEC Management Sch B-4000 Liege Belgium Bu Ali Sina Univ Dept Stat Hamadan Iran

The economic and statistical merits of a multiple variable sampling intervals scheme are studied. The problem is formulated as a double-objective optimization problem with the adjusted average time to signal as the statistical objective and the expected cost per hour as the economic objective. Bai and Lee's [An economic design of variable sampling interval over bar X control charts. Int J Prod Econ. 1998;54:57-64] economic model is considered. Then we find the Pareto-optimal designs in which the two objectives are minimized simultaneously by using the non-dominated sorting genetic algorithm. Through an illustrative example, the advantages of the proposed approach are shown by providing a list of viable optimal solutions and graphical representations, which indicate the advantage of flexibility and adaptability of our approach.

关键词： multivariate T-2 control chart nsga-ii algorithm multi-objective optimization economic statistical design variable sampling intervals scheme

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Topological Optimization of Vehicle ISD Suspension under Steering Braking Condition

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WORLD ELECTRIC VEHICLE JOURNAL 2023年第10期14卷

作者： Liu, Yanling Shi, Dongyin Du, Fu Yang, Xiaofeng Zhu, Kerong Jiangsu Univ Sch Automot & Traff Engn Zhenjiang 212013 Peoples R China Beijing Inst Technol Sch Mech Engn Beijing 100081 Peoples R China China North Vehicle Res Inst Chinese Scholartree Ridge Lab Beijing 100072 Peoples R China

Anti-roll and anti-pitch are important directions in the comprehensive research of automobiles. In order to improve the anti-roll and anti-pitch performance of the vehicle, an inerter was applied to the vehicle suspension system, and a 14 DOF vehicle nonlinear dynamics model was established. The influence of the change in inertance in the eight kinds of improved ISD (Inerter-Spring-Damper) suspension structures on the RMS (root mean square) value of performance indexes of roll, vertical, and pitch motion of the vehicle was studied. Based on this, the vehicle's ISD structure with better performance was selected, and the nsga-ii algorithm was adopted to optimize the selected structural parameters. The simulation results showed that the four kinds of suspension hadbetter comprehensive performance, and their structureswere, respectively, excluding the supporting spring in parallel, (1) an inerter in series with a spring and a damper in parallel, (2) a damper in series with a spring and an inerter in parallel, (3) an inerter and a damper in series, and (4) the damper in parallel with a spring and an inerter in series. The ISD suspension structure had better comprehensive performance under step steering braking, which was obviously better than the passive suspension, and effectively improved the vehicle ride comfort, anti-roll and anti-pitch performance. Under the hook steering braking, the lateral load transfer rate was used to evaluate the vehicle's anti-rollover ability. The results showed that the ride comfort and anti-rollover ability of ISD suspension were better than those of passive suspension. Under the condition of taking into account the anti-pitching ability, the suspension consists of a supporting spring in parallel with an inerter, and a damper in series was better.

关键词： ISD suspension vehicle model nsga-ii algorithm vehicle stability

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A Time-Varying Incentive Optimization for Interactive Demand Response Based on Two-Step Clustering

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INFORMATION 2022年第9期13卷

作者： Li, Fei Gao, Bo Shi, Lun Shen, Hongtao Tao, Peng Wang, Hongxi Mao, Yehua Zhao, Yiyi State Grid Hebei Elect Power Co Ltd Market Serv Ctr Shijiazhuang 050022 Hebei Peoples R China North China Elect Power Univ Sch Elect & Elect Engn Beijing 102206 Peoples R China

With the increasing marketization of electricity, residential users are gradually participating in various businesses of power utility companies, and there are more and more interactive adjustments between load, source, and grid. However, the participation of large-scale users has also brought challenges to the grid companies in carrying out demand-side dispatching work. The user load response is uneven, and users' behavioral characteristics are highly differentiated. It is necessary to consider the differences in users' electricity consumption demand in the design of the peak-valley load time-sharing incentives, and to adopt a more flexible incentive form. In this context, this paper first establishes a comprehensive clustering method integrating k-means and self-organizing networks (SONs) for the two-step clustering and a BP neural network for reverse adjustment and correction. Then, a time-varying incentive optimization for interactive demand response based on two-step clustering is introduced. Furthermore, based on the different clustering results of customers, the peak-valley load time-sharing incentives are formulated. The proposed method is validated through case studies, where the results indicate that our method can effectively improve the users' load characteristics and reduce the users' electricity costs compared to the existing methods.

关键词： consumer behavior two-step clustering demand response nsga-ii algorithm multi-objective optimization

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Travel Time Reliability-Based Rescue Resource Scheduling for Accidents Concerning Transport of Dangerous Goods by Rail

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algorithmS 2021年第11期14卷

作者： Liu, Lanfen Yang, Xinfeng Lanzhou Jiaotong Univ Sch Traff & Transportat Engn Lanzhou 730070 Peoples R China

The characteristics of railway dangerous goods accidents are very complex. The rescue of railway dangerous goods accidents should consider the timeliness of rescue, the uncertainty of traffic environment and the diversity of rescue resources. Thus, the purpose of this paper is to confront the rescue resources scheduling problem of railway dangerous goods accident by considering factors such as rescue capacity, rescue demand and response time. Based on the analysis of travel time and reliability for rescue route, a multi-objective scheduling model of rescue resources based on travel time reliability is constructed in order to minimize the total arrival time of rescue resources and to maximize total reliability. The proposed model is more reliable than the traditional model due to the consideration of travel time reliability of rescue routes. Moreover, a two-stage algorithm is designed to solve this problem. A multi-path algorithm with bound constraints is used to obtain the set of feasible rescue routes in the first stage, and the nsga-ii algorithm is used to determine the scheduling of rescue resources for each rescue center. Finally, the two-stage algorithm is tested on a regional road network, and the results show that the designed two-stage algorithm is valid for solving the rescue resource scheduling problem of dangerous goods accidents and is able to obtain the rescue resource scheduling scheme in a short period of time.

关键词： rescue resource multi-resource scheduling nsga-ii algorithm reliability multi-objective railway dangerous goods accident

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Distributed Data Real-Time Transaction Calculation Based on Collaborative Optimization and Multi-Objective Genetic algorithm

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INTERNATIONAL JOURNAL OF INTELLIGENT INFORMATION TECHNOLOGIES 2024年第1期20卷

作者： Liao, Li Chongqing City Vocat Coll Chongqing Peoples R China

Based on the above situation, this article elaborated on the methods that should be used to calculate the multi-information genetic algorithm (GA) in the current situation. The article mainly compared the non-dominated sorting genetic algorithm-ii (nsga-ii) and multi-objective particle swarm optimization (MOPSO) with elite strategy. By measuring the solving speed and quality of the two algorithms, it was found that the nsga-ii had a greater advantage. Based on the nsga-ii, optimization processing was carried out. The nsga-ii was compared before and after optimization. After analyzing 48 data samples, it was found that the results of the nsga-ii before and after optimization showed that the algorithm tended to be more stable after optimization, thus indicating that the improved data was more accurate. The results indicated that the nsga-ii was necessary for its improvement, and its results were also reasonable.

关键词： Distributed Data MOPSO algorithm Multi-Objective Genetic algorithm nsga-ii algorithm Real-Time Transaction Computing

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Application of Multi-objective Genetic algorithm in Personnel Scheduling among Warehouses 2021

Application of Multi-objective Genetic Algorithm in Personne...

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2021 3rd International Conference on E-Business and E-commerce Engineering

作者： Tianwei Zhou Jiayao Chen Yizhen Xu Baoyu Xiao Shenzhen University College of Management China

ISBN: (纸本)9781450387392

With the fast development in e-commence and logistics, how to guarantee reliable supplement with lowest cost becomes an important problem. However, warehouses often have the problem of seasonal fluctuations, resulting in staff insufficient in peak season and human resources redundancy in slack season. To save the wasted human resources and prevent the revenue drop, it is important to dispatch staff across warehouses. Focus on this problem, we establish a multi-objective warehouse staff scheduling model, and solve it based on nsga-ii with the designed coding schemes. Simulation shows the obtained scheduling scheme and the superiority of our proposed framework has been verified by comparing it with a single-objective model.

关键词： Warehouse personnel scheduling assignment problem Bi-objective and multi-objective programming nsga-ii algorithm Working satisfaction

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Multi-objective hydrodynamic optimization for ONR tumblehome ship

Multi-objective hydrodynamic optimization for ONR tumblehome...

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第二届全球华人水动学学术会议

作者： Jianwei Wu Xiaoyi Liu Decheng Wan State Key Laboratory of Ocean Engineering School of Naval ArchitectureOcean and Civil EngineeringShanghai Jiao Tong UniversityCollaborative Innovation Center for Advanced Ship and Deep-Sea Exploration

A numerical multi-objective optimization procedure is proposed here to describe the development and application of a practical hydrodynamic optimization tool,*** components including hull form modification module,hydrodynamic performance evaluation module and optimization module consist of this *** this paper,the free-form deformation（FFD） method are utilized as parametric hull surface modification techniques to generate a series of realistic hull forms subjected to some design constraints during the optimization *** performance evaluation module,Neumann-Michell（NM） theory is employed here to predict the wave-making drag at low computational ***,Kriging models are established based on OLHS samples as surrogates for optimization process,and a multi-objective genetic algorithm named nsga- ii has been employed to provide pareto-optimal *** Tumblehome model 5613 is taken as preliminary design,and the two objective functions have been chosen as the wave resistance at two speeds（Fr = 0.2,0.3）,Eventually,the pareto optimal set which provides over 4000 optimal hull forms is obtained by using nsga- ii algorithm,and three of them are chosen for further *** numerical optimization results are analyzed,and the availability of the OPTShip-SJTU is confirmed by this application.

关键词： OPTShip-SJTU Multi objective optimization nsga-ii algorithm Neumann-Michell theory wave drag

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Research on Optimal Allocation of Command Decision-making Authority Based on Operations Research Theory

Research on Optimal Allocation of Command Decision-making Au...

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第43届中国控制会议

作者： Zexuan Jin Jia Zhang Beijing Institute of Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

In order to improve the efficiency of command structure, it is necessary to study the optimization allocation of command and decision-making authority. Graph theory methods in operations research are used to describe the command relationship between command nodes and resource nodes and establish the optimization indexes such as decision transmission time, destructive resistance capability, and constraints such as resource constraints. Non-dominated sorting genetic algorithm Ⅱ(nsga-Ⅱ) is applied to solve the multi-indicator nonlinear planning problem and obtain the optimal solution of the command decision authority allocation problem. Simulation experiments are carried out in three kinds of scenarios. The solution obtained by the algorithm proposed in this paper is compared with that based on the proximity principle and that obtained using the MOEA/D algorithm. The results show that the solution obtained by the algorithm proposed in this paper is more effective and can achieve better command effectiveness.

关键词： command decision authority optimal assignment graph theory nonlinear programming nsga-ii algorithm

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