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multi-objective Finite-Frequency H8/GH2 Static Output-Feedback Control Synthesis for Full-Vehicle Active Suspension Systems: A metaheuristic Optimization Approach

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IEEE ACCESS 2023年 11卷 36309-36330页

作者： Kim, Yeongjae Kwak, Taeheon Kanno, Masaaki Kim, Tae-Hyoung Chung Ang Univ Dept Mech Engn Seoul 06974 South Korea Niigata Univ Inst Sci & Technol Acad Assembly Nishi Ku Niigata 9502181 Japan

In this paper, the problem of multi-objective control for active suspension systems with polytopic uncertainty is addressed via H-8/GH(2) static output feedback with a limited-frequency characteristic. For the overall analysis of the performance demanding both the vehicle-ride comfort related to vertical- and transversal-directional dynamics and the time-domain constraints related to the driving maneuverability, a seven-degree-of-freedom full-vehicle model with an active suspension system is investigated. The robust static output-feedback control strategy is adopted because some state variables may not be directly measured in a realistic implementation. In designing this control, the finite-frequency H-8 performance using the generalized Kalman-Yakubovich-Popov lemma is optimized to improve the passenger's ride comfort, while the GH(2) performance is optimized to guarantee the constraints concerning the suspension deflection limitation, road-holding ability, and actuator saturation problem. This control synthesis problem is formulated as non-convex bilinear matrix inequalities and requires simultaneous consideration of different finite-frequency domain ranges for vertical and transversal motions for evaluating the v performance. These design difficulties are overcome by the proposed multi-objective quantum-behaved particle swarm optimizer, which efficiently explores the relevant trade-offs between the considered multiple performance objectives and eventually provides the desired set of Pareto-optimal solutions. Further, the numerical simulation cases of a full-vehicle active suspension system are presented to illustrate the effectiveness of the proposed control synthesis methodology in both frequency and time domain.

关键词： Suspensions (mechanical systems) Vibrations Actuators Uncertainty metaheuristics Frequency control Time-domain analysis Active suspension system static output feedback finite frequency generalized Kalman-Yakubovich-Popov lemma bilinear matrix inequalities multi-objective metaheuristic algorithm

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A fuzzy multi-objective optimization model for a sustainable reverse logistics network design of municipal waste-collecting considering the reduction of emissions

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JOURNAL OF CLEANER PRODUCTION 2021年 318卷 128577-128577页

作者： Hashemi, Seyed Emadedin Islamic Azad Univ Arak Branch Dept Ind Engn Arak Iran

The most important reason for waste collection is the protection of the environment and the health of the population. Reverse logistics is applied in the sustainable management of municipal waste and is used in the collection, recycling and reuse, as well as the reduction of consumables and environmental compatibility. One of the challenges of sustainable management is costs and customer demand must be considered simultaneously. In this paper, we try to address a comprehensive approach by applying fuzzy mathematical programming to design a multi-objective model for a reverse logistics network. To cover all aspects of this system, we tried to minimize the cost of facility construction, vehicle fuel and environmental damage from the emission of polluting gases, as well as minimize the sum of the ratio of unanswered customer demand to the amount of their demand for all periods, as objective functions of the model. In order to obtain solutions on the Pareto front, a customized multi-objective genetic algorithm (NSGAII) and a customized bee colony algorithm (BCO) were applied. The results of the two algorithms according to the indicators of quality comparison, spacing, diversification and solution time have been compared. The results showed that in all cases, the bee colony algorithm was better able to explore and extract the area to a feasible solution and to achieve near-optimal answers. In terms of spacing metric and resolution time, the genetic algorithm performed better than the bee algorithm.

关键词： Reverse logistics Municipal waste-collecting Reduction of emissions Fuzzy mathematical programming multi-objective metaheuristic algorithm NSGA II Bee colony algorithm

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A bi-objective model for a multi-echelon supply chain design considering efficiency and customer satisfaction: a case study in plastic parts industry

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2018年第9-12期95卷 3631-3649页

作者： Ebrahimi, Seyed Babak KN Toosi Univ Technol Dept Ind Engn Pardis St Molasadra AveVanak Sq Tehran 193951999 Iran

One of the fundamental challenges of today's manufacturing systems is the contradiction between cost efficiency and customer satisfaction. Finding a good balance between good customer satisfaction and supply chain efficiency is a critical problem in the supply chain management. To achieve this goal, a bi-objective mathematical model is suggested in this paper to maximize the efficiency of network and also customer satisfaction. This multi-period and multi-product supply chain network design model consists of suppliers, factories, distribution centers (DCs), and customers. The proposed bi-objective mixed-integer non-linear programming (MINLP) model is a member of the NP-hard class of optimization problems. Hence, two well-known multi-objective metaheuristic algorithms namely, Non-dominated Sorting Genetic algorithm II (NSGA-II) and Non-dominated Ranked Genetic algorithm (NRGA) are employed to solve the proposed model. The author uses Taguchi method for tuning the parameters of algorithms in order to achieve better performances. Moreover, a case study in the plastic industry is performed to collect data from the north region of Iran. Some well-known multi-objective metrics such as analysis of variance (ANOVA) is used to measure the performance of the proposed framework. Finally, results demonstrate the efficiency of the proposed framework.

关键词： Supply chain network design Customer satisfaction multi-objective metaheuristic algorithm Plastic industry Taguchi method

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A fuzzy multi-objective optimization model for sustainable reverse logistics network design

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ECOLOGICAL INDICATORS 2016年 67卷 753-768页

作者： Govindan, Kannan Paam, Parichehr Abtahi, Amir-Reza Univ Southern Denmark Ctr Sustainable Engn Operat Management Dept Technol & Innovat Odense Denmark Kharazmi Univ Fac Management Dept Informat Technol Management Tehran Iran

Decreasing the environmental impact, increasing the degree of social responsibility, and considering the economic motivations of organizations are three significant features in designing a reverse logistics network under sustainability respects. Developing a model, which can simultaneously consider these environmental, social, and economic aspects and their indicators, is an important problem for both researchers and practitioners. In this paper, we try to address this comprehensive approach by using indicators for measurement of aforementioned aspects and by applying fuzzy mathematical programming to design a multi-echelon multi-period multi-objective model for a sustainable reverse logistics network. To reflect all aspects of sustainability, we try to minimize the present value of costs, as well as environmental impacts, and optimize the social responsibility as objective functions of the model. In order to deal with uncertain parameters, fuzzy mathematical programming is used, and to obtain solutions on Pareto front, a customized multi-objective particle swarm optimization (MOPSO) algorithm is applied. The validity of the proposed solution procedure has been analyzed in small and large size test problems based on four comparison metrics and computational time using analysis of variance. Finally, in order to indicate the applicability of the suggested model and the practicality of the proposed solution procedure, the model has been implemented in a medical syringe recycling system. The results reveal that the suggested MOPSO algorithm overtakes epsilon-constraint method from the aspects of quality of the solutions as well as computational time. Proper use of the proposed process could help managers efficiently manage the flow of recycled products with regard to environmental and social considerations, and the process offers a sustainable competitive advantage to corporations. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Reverse logistics Sustainability Social responsibility Fuzzy mathematical programming multi-objective metaheuristic algorithm Epsilon-constraint method

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