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A web-based methodology for convergent product fuzzy networks using the Steiner tree

JOURNAL OF INDUSTRIAL AND PRODUCTION ENGINEERING 2013年第7期30卷 415-432页

作者： Hassanzadeh, Reza Mahdavi, Iraj Mahdavi-Amiri, Nezam Mazandaran Univ Sci & Technol Dept Ind Engn Babol Sar Iran Sharif Univ Technol Fac Math Sci Tehran Iran

An important manufacturing technology spectrum is to consider rapid and sensitive assemblies through convergent product (CP) in digital environment. We integrate functions and sub-functions using a comprehensive mathematical optimization process. To form the CP, a web-based fuzzy network is considered in which a collection of base functions and sub-functions configure the nodes and each arc in the network is to be a link between two nodes. The aim is to find an optimal tree of functionalities in the network adding value to the product in the web environment. First, a purification process is performed in the product network to assign the links among bases and sub-functions. Then, fuzzy numbers as benefits, costs and customers' value are determined. Next, the fuzzy Steiner tree methodology is adapted to a multi-objective model of the network to find the optimal tree determining the value adding sub-functions to bases in a CP. A new fuzzy multi-objective optimization is developed to work out the problem. Finally, an example is worked out to illustrate the proposed approach.

关键词： convergent product web-based (digital) network fuzzy multi-objective programming Steiner tree fuzzy number

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multi-choice multi-objective linear programming problem

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JOURNAL OF INTERDISCIPLINARY MATHEMATICS 2009年第5期12卷 606-636页

作者： Biswal, M. P. Acharya, Srikumar Indian Inst Technol Dept Math Kharagpur 721302 W Bengal India

We consider a multi-objective linear programming problem where some of the right hand side parameters of the constraints are multi-choice in nature. For some right hand side parameters of the constraints, there may exist multiple choices, out of which exactly one is to be chosen. The selection from the sets should be in such a manner that the combination of choices for each set should provide best compromise solution. In order to solve the proposed multi-choice multi-objective linear programming problem, this paper proposes an equivalent mathematical model, which can be solved with the help of existing non-linear programming method. The proposed model can accommodate a maximum of sixteen choices for a single parameter. An illustrative example is presented in support of the proposed model.

关键词： multi-objective linear programming fuzzy multi-objective programming multi-choice programming non-linear programming

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Transportation planning with modified S-curve membership functions using an interactive fuzzy multi-objective approach

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APPLIED SOFT COMPUTING 2011年第2期11卷 2656-2663页

作者： Peidro, David Vasant, Pandian Univ Politecn Valencia Res Ctr Prod Management & Engn CIGIP Valencia Spain Univ Teknol PETRONAS Fundamental & Appl Sci Dept Petronas Malaysia

In this paper, we consider the transportation planning decision (TPD) problem with fuzzy goals, available supply and forecast demand. An interactive method is designed for solving the multi-objective TPD problem where the fuzzy data are represented by modified S-curve membership functions. The proposed method attempts to simultaneously minimize the total production and transportation costs and the total delivery time with reference to budget constraints and available supply, machine capacities at each source, as well as forecast demand and warehouse space constraints at each destination. An interactive fuzzy approach is applied to solve the multi-objective TPD problem and to find a preferred compromise solution. Finally, the performance of S-curve membership functions that represent uncertainty goals and constraints in TPD problems with linear membership functions in an industrial case is compared. (C) 2010 Elsevier B.V. All rights reserved.

关键词： Transportation planning S-curve membership function fuzzy multi-objective programming

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Resource efficiency improvement: zero waste discharge planning in a pulp-and-paper firm under uncertainties

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MANAGEMENT OF ENVIRONMENTAL QUALITY 2021年第3期32卷 646-664页

作者： Jeng, Shiou-Yun Lin, Chun-Wei Tseng, Ming-Lang Jantarakolica, Korbkul Tan, Raymond Asia Univ Inst Innovat & Circular Econ Taichung Taiwan Asia Univ Dept Business Adm Taichung Taiwan China Med Univ Dept Med Res Taichung Taiwan Rajamangala Univ Technol Rattanakosin Salaya Nakhon Pathom Thailand De La Salle Univ Manila Philippines

Purpose - This study develops an integrated zero waste discharge planning approach for improving resource efficiency in a pulp-and-paper manufacturing firm. Design/methodology/approach - The objectives of this study are to (1) identify the environmental, technical and social metrics in resource efficiency;(2) utilize fuzzy multi-objective programming and the hybrid particle swarm optimization algorithm to solve the fuzzy problem;and (3) develop an assessment for resource efficiency improvement in an industrial case study. Findings - The findings demonstrate the superiority of hybrid particle swarm optimization algorithm in generating optimal results for a pulp-and-paper manufacturing firm. Practical implications - The findings demonstrate the superiority of hybrid particle swarm optimization algorithm in generating optimal results for a pulp-and-paper manufacturing firm. Originality/value - Resource efficiency is a multi-objective problem in an uncertain environment. In particular, zero waste discharge planning involves minimizing the total cost and maximizing the waste material recovery rate, wastewater reuse, and waste heat recovery.

关键词： Resource efficiency Zero waste discharge planning fuzzy comprehensive evaluation fuzzy multi-objective programming Hybrid particle swarm optimization

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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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Balancing fuzzy multi-objective two-sided assembly lines via Bees Algorithm

Balancing fuzzy multi-objective two-sided assembly lines via...

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1st International Symposium on fuzzy Systems

作者： Ozbakir, Lale Tapkan, Pinar Erciyes Univ Dept Ind Engn Kayseri Turkey

Many real life problems contain imprecise variables, constraints and objectives. fuzzy set theory gives an opportunity to handle imprecise terms in such situations. Two-sided assembly line balancing (2sALB) problem which is a generalization of the well known simple assembly line balancing problem can also be modeled more realistically by employing fuzzy approaches. Such an approach is presented in this study to model and solve 2sALB problem by employing fuzzy mathematical programming and Bees Algorithm (BA). 2sALB problem is a combinatorial complex problem. For this reason BA is employed as a search mechanism for obtaining good solutions to it. BA is a relatively new member of swarm intelligence based meta-heuristics that tries to mimic natural behavior of real honey bees in food foraging in solving complex optimization problems. BA is generally applied to continuous optimization in the literature. Its application to combinatorial problems is rare. This study also presents one of the first application of BA to an assembly line balancing problem which is member of combinatorial optimization.

关键词： fuzzy multi-objective programming two-sided assembly line balancing problem Bees Algorithm soft computing

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A Novel Hybrid Modelling for Aggregate Production Planning in a Reconfigurable Assembly Unit for Optoelectronics 22nd

A Novel Hybrid Modelling for Aggregate Production Planning i...

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22nd International Conference on Neural Information Processing (ICONIP)

作者： Sisca, Francesco G. Fiasche, Maurizio Taisch, Marco Politecn Milan Dept Management Econ & Ind Engn I-20133 Milan Italy

ISBN: (纸本)9783319265353;9783319265346

In this work it is presented a novel fuzzy multi-objective linear programming (FMOLP) model based on hybrid fuzzy inference systems for solving the general management framework fort the integration of a self-contained robotic reconfigurable assembly unit in a pre-existing shop-floor. It is developed an aggregate production planning in a fuzzy environment where the product price, unit inventory cost, unit assembly cost, resource-product suitability cost, availability of the assembly line, the assembly time and the market demands are fuzzy in nature. The proposed model attempts to minimize total production costs, maximizing the shop floor resources utilization and the profits, considering nominal capacity and inventory towards zero. Pareto solutions optimization is computed with different techniques and results are presented and discussed with interesting practical implications.

关键词： Aggregate production planning APP Hybrid fuzzy systems fuzzy multi-objective programming MOLP

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Sustainable microgrid design with multiple demand areas and peer-to-peer energy trading involving seasonal factors and uncertainties

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RENEWABLE & SUSTAINABLE ENERGY REVIEWS 2022年第0期161卷

作者： Yu, Vincent F. Thi Huynh Anh Le Gupta, Jatinder N. D. 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 Danang Univ Sci & Technol Fac Project Management Danang 550000 Vietnam Univ Alabama Coll Business Huntsville AL 35899 USA

The intermittent nature of renewable sources, uncertain demand load, and the location of microgrids cause challenges for the proper energy balance between supply and demand. To overcome the issues caused by such challenges and to be economically efficient while minimizing environmental impacts, microgrid design with renewable energy sources has recently attracted the attention of researchers. However, the sustainable microgrid design involving multiple types of demand areas (residential and industrial areas) and seasonal factors has not been explored by researchers. Therefore, this paper investigates the sustainable microgrid design problem with multiple types of demand areas and peer-to-peer energy trading involving seasonal factors and uncertainties to maximize total profit and to minimize environmental costs while satisfying demand. The problem is to determine optimal decisions on the number, location, and capacity of renewable distributed generation sources, energy flows, and seasonal electricity sales prices for the system that includes peer-to-peer trading. A fuzzy multi-objective programming model is developed to handle the uncertainties of demand load and capacity of renewable distributed generation sources. A genetic algorithm is applied to solve the proposed model. Results of computational experiments to assess its effectiveness and efficiency show that the proposed model increases total profit by over 12% and reduces environmental costs by almost 30% compared to the cases of no peer-to-peer energy trading and seasonal factors.

关键词： Sustainable microgrids Seasonal electricity price Residential and industrial areas Peer-to-peer energy trading Uncertain demand patterns fuzzy multi-objective programming Genetic algorithm

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Optimal Maintenance Policy for Offshore Wind Systems

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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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A study of an interactive fuzzy multi-objective optimal power flow

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Electrical Engineering in Japan 1999年第1期130卷

作者： Junji Kubokawa Yoshito Okubo Hiroshi Sasaki Ryuichi Yokoyama Hiroshima University Japan Tokyo Metropolitan University Japan

As the necessity of high-quality electric power supply increases, it has been required to develop sophisticated power system operations in which several requirements stemming from economy, security, and environmental aspects are simultaneously satisfied. In general, a problem of satisfying several noncommensurable criteria is called a multiobjective optimization problem. Although the most powerful means to obtain desirable system operations is optimal power flow (OPF), a straightforward application of the conventional OPF optimizes only one objective and the remaining objectives must be treated as constraints. However, since such objectives are in trade-off relationships with each other, it is necessary to develop an efficient multiobjective OPF. In this paper, we propose a solution method of multiobjective OPF by means of fuzzy coordination. In the first step, the degree of Decision Maker (DM) satisfaction on each objective would be maximized with a prespecified membership function. The membership function would be updated in accordance with the DM's preference information and target value of the objective function. The degree of satisfaction will be improved step by step by updating the membership functions. Finally, the satisficing solution for the DM would be obtained. The proposed method has been applied to the IEEE 57 and 118 test systems, producing successful results. © 1999 Scripta Technica, Electr Eng Jpn, 130(1): 59–67, 2000

关键词： fuzzy multi-objective programming optimal power flow calculation method OPF

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