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Optimal Maintenance Policy for Offshore Wind Systems

ENERGIES 2021年第19期14卷 6082页

作者： Yu, Vincent F. Le, Thi Huynh Anh Su, Tai-Sheng Lin, Shih-Wei Natl Taiwan Univ Sci & Technol Dept Ind Management Taipei 106 Taiwan Natl Taiwan Univ Sci & Technol Ctr Cyber Phys Syst Innovat Taipei 106 Taiwan Univ Sci & Technol Univ Danang Fac Project Management Danang 550000 Vietnam Natl Pingtung Univ Sci & Technol Dept Ind Management Pingtung 912 Taiwan Chang Gung Univ Dept Informat Management Taoyuan 333 Taiwan Ming Chi Univ Technol Dept Ind Engn & Management New Taipei 243 Taiwan Linkou Chang Gung Mem Hosp Dept Neurol Taoyuan 333 Taiwan

Employing maintenance threshold plays a critical step in determining an optimal maintenance policy for an offshore wind system to reduce maintenance costs while increasing system reliability. Considering the limited works on this topic, we propose a two-stage procedure to determine the optimal maintenance thresholds for multiple components of an offshore wind power system in order to minimize maintenance costs while achieving the highest possible system reliability. First, using genetic algorithms, a dynamic strategy is developed to determine the maintenance thresholds of individual components where the cost of maintenance and the rate of failure are critical. Then, fuzzy multi-objective programming is applied to find the system's optimal maintenance threshold considering all components. A variety of factors including weather conditions, system reliability, power generation losses, and electricity market price are carefully considered to enhance the system's reliability and reduce the costs of maintenance. When maintenance threshold results are compared, component-wise versus system-wise, an average system savings of 1.19% for maintenance cost is obtained while the system reliability is increased by 1.62% on average.

关键词： offshore wind system fuzzy multi-objective programming failure rate maintenance threshold optimal maintenance policy

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fuzzy multi-objective optimization for multi-site integrated production and distribution planning in two echelon supply chain

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2019年第1-4期102卷 635-645页

作者： Badhotiya, Gaurav Kumar Soni, Gunjan Mittal, M. L. Malaviya Natl Inst Technol Jaipur Dept Mech Engn Jaipur Rajasthan India

This paper addresses an integrated production and distribution planning problem for a two-echelon supply chain network comprising of multiple manufacturers serving multiple selling locations. A novel fuzzy multi-objective mixed integer programming model is formulated considering multi-product, multi-period, and multi-site manufacturing environment. Minimization of total cost, delivery time, and backorder level are the three fuzzy objectives represented by piecewise linear membership function. Three important production and distribution aspects viz. capacity of the heterogeneous transportation, backordering for unfulfilled demand, and set-up cost/time for different products at manufacturing site are incorporated in an integrated manner to represent closeness to the real-life problem. An illustrative example inspired from a real-world case of an automobile industry is taken to demonstrate analytical results of the proposed approach. The outcome of the research indicates the practical applicability of the approach. Sensitivity analysis on objective function values is conducted for analyzing the effect of change in aspiration levels of objective function values on decision maker's satisfaction level.

关键词： multi-site manufacturing Production planning Distribution planning fuzzy multi-objective programming Optimization

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A reliability-and-cost-based fuzzy approach to optimize preventive maintenance scheduling for offshore wind farms

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MECHANICAL SYSTEMS AND SIGNAL PROCESSING 2019年 124卷 643-663页

作者： Zhong, Shuya Pantelous, Athanasios A. Goh, Mark Zhou, Jian Univ Cambridge Dept Engn Inst Mfg Cambridge CB3 0FS England Monash Univ Dept Econometr & Business Stat Clayton Vic 3800 Australia Natl Univ Singapore Logist Inst Asia Pacific Singapore 119613 Singapore Natl Univ Singapore NUS Business Sch Singapore 119613 Singapore Shanghai Univ Sch Management Dept Management Sci & Engn Shanghai 200444 Peoples R China

We study the preventive maintenance scheduling problem of wind farms in the offshore wind energy sector which operates under uncertainty due to the state of the ocean and market demand. We formulate a fuzzy multi-objective non-linear chance-constrained programming model with newly-defined reliability and cost criteria and constraints to obtain satisfying schedules for wind turbine maintenance. To solve the optimization model, a 2-phase solution framework integrating the operational law for fuzzy arithmetic and the non-dominated sorting genetic algorithm II for multi-objective programming is developed. Pareto-optimal solutions of the schedules are obtained to form the trade-offs between the reliability maximization and cost minimization objectives. A numerical example is illustrated to validate the model. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Offshore wind energy Preventive maintenance scheduling fuzzy chance-constrained programming fuzzy multi-objective programming Reliability Maintenance cost

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fuzzy multi-objective optimization for the allocation of multinational production resources considering import quota

Fuzzy multi-objective optimization for the allocation of mul...

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International Conference on Industrial Engineering and Systems Management (IESM)

作者： Wang, Weijie Du, Zhijiao Chen, Zhixiang Sun Yat Sen Univ Dept Management Sci Guangzhou Peoples R China

ISBN: (纸本)9781728115665

This paper develops a global supply chain network model considering global factors such as exchange rate, tariff and import quota. The model is a fuzzy multi-objective mixed integer programming model which aims to maximize manufacturer's profit and delivery quality of suppliers. We further discuss how to transform the fuzzy multi-objective programming model into a single-objective linear programming model. We use the interactive fuzzy multi-objective linear programming method to solve the model, which provides an interactive framework for decision makers and facilitates the decision-making process under the fuzzy environment. Additionally, the framework enables decision makers to interactively change membership functions to achieve the most satisfactory solution. Finally, an illustrative example verifies the feasibility and validity.

关键词： global supply chain fuzzy multi-objective programming import quota demand uncertainty

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fuzzy multi-objective programming for supplier selection and risk modeling: A possibility approach

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2010年第3期200卷 774-787页

作者： Wu, Desheng Dash Zhang, Yidong Wu, Dexiang Olson, David L. Reykjavik Univ Sch Sci & Engn IS-103 Reykjavik Iceland Univ Toronto RiskLab Toronto ON M5S 3G8 Canada SUNY Buffalo Dept Ind & Syst Engn Buffalo NY 14260 USA Univ Sci & Technol China Sch Management Hefei 230026 Anhui Peoples R China Univ Nebraska Dept Management Lincoln NE 68588 USA

Selection of supply chain partners is an important decision involving multiple criteria and risk factors. This paper proposes a fuzzy multi-objective programming model to decide on supplier selection taking risk factors into consideration. We model a supply chain consisting of three levels and use simulated historical quantitative and qualitative data. We propose a possibility approach to solve the fuzzy multi-objective programming model. Possibility multi-objective programming models are obtained by applying possibility measures of fuzzy events into fuzzy multi-objective programming models. Results indicate when qualitative criteria are considered in supplier selection, the probability of a certain supplier being selected is affected. (C) 2009 Elsevier B.V. All rights reserved.

关键词： Supplier selection Risk fuzzy multi-objective programming multiple criteria Chance constraint

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fuzzy multi-objective approach for optimal selection of suppliers and transportation decisions in an eco-efficient closed loop supply chain network

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JOURNAL OF CLEANER PRODUCTION 2017年第Nov.1期165卷 1598-1619页

作者： Govindan, Kannan Darbari, Jyoti Dhingra Agarwal, Vernika Jha, P. C. Univ Southern Denmark Dept Technol & Innovat Ctr Sustainable Supply Chain Engn Odense M Denmark Univ Delhi Dept Operat Res Delhi India

Establishment of a closed loop supply chain (CLSC) network has attracted immense significance due to government policies and societal demand for environmental consciousness. However, to enhance the financial and ecological impact of the network, the forward and reverse supply chain networks must integrate well so that decisions taken in both areas complement each other. In this study, we propose an eco-efficient CLSC design for extending the existing supply chain of an Indian firm that assembles inkjet printers. The network design is configured as a multi-objective model in a multi-period setting and is mathematically formulated into a mixed integer programming problem with fuzzy objectives. Fuzziness provides flexibility to the decision makers because they must accommodate the conflicting nature of the objectives. The fuzzy multi-objective model incorporates the firm's economic and environmental concerns into the decision making process by selecting environmentally responsible suppliers to procure components based on sustainable criteria, choosing appropriate recovery options for end-of-use (EOU) inkjet printers, and planning an efficient transportation network design for reducing the carbon emission of the distribution and collection activities. The uniqueness of the proposed fuzzy CLSC optimization model lies in providing an integrated decision making framework that can aid the manufacturer in making crucial strategic, tactical, and operational decisions of optimal selection of suppliers, component order allocation, recovery flow allocation, and vehicle routing planning. The novelty of the model also lies in simultaneously minimising the overall cost of the activities undertaken, maximizing the performance of the component suppliers and minimising the carbon emissions of the associated transportation activities. A weighted fuzzy mathematical programming approach is utilised for generating a fuzzy, properly efficient solution as the desired compromised solution fo

关键词： fuzzy multi-objective programming Supplier selection Factor analysis AHP k-means clustering Carbon emission

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The fuzzy multi-objective distribution planner for a green meat supply chain

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2017年 184卷 47-58页

作者： Mohammed, Ahmed Wang, Qian Univ Portsmouth Sch Engn Portsmouth PO1 3DJ Hants England

It is often a complex task for developing a product distribution plan of a supply chain (SC) network and a supportive decision tool can be useful for easing the role of decision-making. On the other hand, it has been increasingly becoming a demand to design a supply chain network considering the environmental impact as a new dimension as required by authorities in many countries. This paper describes a development of a product distribution planner for a three-echelon green meat supply chain (MSC) design in terms of issues including numbers and locations of facilities that should be opened in association with the product quantity flows. These issues were formulated into a fuzzy multi-objective programming model (FMOPM) with an aim to minimize the total cost of transportation and implementation, the amount of CO2 emissions in transportation and the distribution time of products from farms to abattoirs and from abattoirs to retailers, and maximize the average delivery rate in satisfying product quantity as requested by abattoirs and retailers. To optimize the four objectives simultaneously, three solution methods were investigated and used;Which are the LP-metrics method, the c-constraint method and the goal programming method. The best solution was determined using the Max-Min method by comparing the obtained Pareto solutions. A case study was examined based on the developed model that demonstrates its applicability in making an optimal product distribution plan in trade-offs among the four objectives.

关键词： Distribution plan Food supply chain design fuzzy multi-objective programming Green supply chain RFID

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fuzzy multi-objective programming Application for Time-Cost Trade-off of CPM in Project Management

Fuzzy Multi-objective Programming Application for Time-Cost ...

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2nd International Conference on Computational Collective Intelligence: Technologies and Applications

作者： Yang, Gino K. Department of Computer Science and Information Management Hungkuang University Taiwan

ISBN: (纸本)9783642166921

In pragmatic project management cases, many complex resources and large-scale related activities are involved. Moreover, when situations are under the conflict and incommensurate of time and cost, it becomes more difficult for managers to make their decisions. Hence, we construct fuzzy multi-objective programming model from CPM technique. Through emphasizing the selectable flexibility among the feasible projects, we describe the decision problem brought from uncertainty and complex in project. In our research, taking the conflict and incommensurate of time and cost as two major factors, we measure weight and priority to denote the importance degree between the objectives. Adopting Tiwari et al., we also develop the result when trading off the decision vs. the vague environment of time and cost and the past' single objective' method has become the exceptional case of multi-objective models. Secondly, we broaden the consumed time and cost of activity events when assumptions are certain to merge the practical situation. We applied fuzzy number to express estimate time and cost. It based on Lee and Li method to solve this problem. Finally, we employ numerical example to explain it with LINGO package to calculate.

关键词： Project management CPM fuzzy number fuzzy multi-objective programming

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Active Portfolio Management from a fuzzy multi-objective programming Perspective

Active Portfolio Management from a Fuzzy Multi-objective Pro...

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Evo Applications 2010 Conference

作者： Thomaidis, Nikos S. Univ Aegean Management & Engn Lab Dept Financial & Management Engn GR-82100 Chios Greece

ISBN: (纸本)9783642122415

We consider the problem of structuring a portfolio that outperforms a benchmark index, assuming restrictions on the total number of tradable assets. We experiment with non-standard formulations of active portfolio management, outside the mean-variance framework, incorporating approximate (fuzzy) investment targets and portfolio constraints. To deal with the inherent computational difficulties of cardinality-constrained active allocation problems, we apply three nature-inspired optimisation procedures: simulated annealing, genetic algorithms and particle swarm optimisation. Optimal portfolios derived from these methods are bench-marked against the Dow Jones Industrial Average index and two simpler heuristics for detecting good asset combinations, based on Monte-Carlo simulation and fundamental analysis.

关键词： Active portfolio management fuzzy multi-objective programming Cardinality constraints Evolutionary computation Simulated annealing Genetic algorithms Particle swarm optimisation

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fuzzy multi-objective programming Approach To Hazard Materials Treatment Center Location

Fuzzy Multi-objective Programming Approach To Hazard Materia...

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International Conference on Artificial Intelligence and Computational Intelligence

作者： Dai, Wenqiang Huang, Qian Univ Elect Sci & Technol China Sch Management & Econ Chengdu 610054 Sichuan Peoples R China Xian Physical Educ Univ Dept Sports Sociol Xian 710068 Peoples R China

ISBN: (纸本)9780769538167

This paper mainly focus on the hazard materials treatment center location problem using the fuzzy multi-objective programming approach. We consider the factor of treating volume of each treatment center into the classical MAX-MIN model. The problem is formulated as a bi-objective problem, which is rarely studied previously. Additionally, to provide a more realistic model structure, decision makers imprecise aspiration levels for the goals are incorporated into the model through fuzzy modelling approach. In the decision process, a fuzzy goal programming method is developed. We also discuss the computing approach and prove that the fuzzy optimal solution has a good performance.

关键词： Location Hazard Materials fuzzy multi-objective programming

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