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Optimal components assignment problem for a flow network with node failure using fuzzy optimization

AIN SHAMS ENGINEERING JOURNAL 2022年第4期13卷

作者： Hassan, M. R. Hamdy, H. Alkhalaf, Salem Eldin, Ayman M. Bahaa Ahmed, Mahrous Hemeida, A. M. Aswan Univ Fac Sci Math Dept Comp Sci Branch Aswan Egypt Qassim Univ Coll Sci & Arts Ar Rass Dept Comp Ar Rass Saudi Arabia Misr Int Natl Univ Cairo Egypt Taif Univ Coll Engn Dept Elect Engn POB 11099 Taif 21944 Saudi Arabia Aswan Univ Fac Energy Engn Elect Engn Dept Aswan Egypt

The optimal components assignment problem in a flow network with node failure in the presence of system reliability and total lead-time constraints is studied in this paper. By using fuzzy membership functions, we formulated the problem as fuzzy linear optimization. Genetic optimization algorithm with fuzzy optimization is suggested for solving the presented problem. The suggested approach succeeded in finding an optimal solution that distinguishes with increasing reliability and minimizing total lead-time. The suggested technique is examined on various models, four nodes, six nodes, and eight nodes computer networks. (C) 2021 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Ain Shams University.

关键词： Network reliability Components assignment problem Stochastic-flow networks fuzzy multi-objective linear programming Node failure Genetic algorithms

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Reverse logistics optimization of an industrial air conditioner manufacturing company for designing sustainable supply chain: a fuzzy hybrid multi-criteria decision-making approach

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WIRELESS NETWORKS 2020年第8期26卷 5759-5782页

作者： Ali, Sadia Samar Paksoy, Turan Torgul, Belkiz Kaur, Rajbir Coll Engn Dept Ind Engn GC Jeddah Saudi Arabia Fac Engn & Nat Sci Dept Ind Engn Konya Turkey

Magnified resource consumption and depletion of natural resources calls for non-flexible or strict regulations and penalties on industrial operations, increased rate of processing and reuse of waste material as a substitute for raw material and political and legal interventions at global scale. Product recovery involves reuse, repair, refurbishing, remanufacturing and materials recycling, requires an efficient network design known as reverse logistic network and offers economical benefits in terms of fewer procurement of raw material, inventory management and less disposal. In current study, a mixed integer linear programming model designed on a multi-stage reverse logistics network for product recovery is proposed which considers different recovery options-product remanufacturing, component reprocessing and material recycling for sustainable outcomes. The model is designed to find optimal solutions for fulfilling demand and revenue needs by focusing on strategic locations for collection centers, reprocessing centers, remanufacturing plants and transportation options and simultaneously achieving sustainability goals. The model is applied on an Indian based manufacturing unit of a Saudi Arabian Industrial Air conditioner manufacturing organization and the case is presented here. The model is converted into a multi-objective programming model in accordance with the importance of each objective suiting the business needs. All relevant objective functions are evaluated using BWM, AHP and FAHP methods to obtain weights for integration into a fuzzy linear programming model which eventually provides three separate results. The model applied has originality and uniqueness for applications to solve multi-objective problems under uncertain environment and tends to strike a balance between economic and environmental objectives. The study provides for a base for further scope covering uncertainty about the amount and quality of returned products and even can be implemented by p

关键词： BWM fuzzy multi-objective linear programming Mixed-integer linear programming Network design Product recovery Reverse logistics

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fuzzy multi-objective decision making approach for nuclear power plant installation

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JOURNAL OF INTELLIGENT & fuzzy SYSTEMS 2020年第5期39卷 6339-6350页

作者： Cakir, Esra Ulukan, Ziya Galatasaray Univ Dept Ind Engn Ciragan Cad 36 TR-34349 Ortakoy Istanbul Turkey

Due to the increase in energy demand, many countries suffer from energy poverty because of insufficient and expensive energy supply. Plans to use alternative power like nuclear power for electricity generation are being revived among developing countries. Decisions for installation of power plants need to be based on careful assessment of future energy supply and demand, economic and financial implications and requirements for technology transfer. Since the problem involves many vague parameters, a fuzzy model should be an appropriate approach for dealing with this problem. This study develops a fuzzy multi-objective linear programming (FMOLP) model for solving the nuclear power plant installation problem in fuzzy environment. FMOLP approach is recommended for cases where the objective functions are imprecise and can only be stated within a certain threshold level. The proposed model attempts to minimize total duration time, total cost and maximize the total crash time of the installation project. By using FMOLP, the weighted additive technique can also be applied in order to transform the model into fuzzy multiple Weighted-objective linear programming (FMWOLP) to control the objective values such that all decision makers target on each criterion can be met. The optimum solution with the achievement level for both of the models (FMOLP and FMWOLP) are compared with each other. FMWOLP results in better performance as the overall degree of satisfaction depends on the weight given to the objective functions. A numerical example demonstrates the feasibility of applying the proposed models to nuclear power plant installation problem.

关键词： Project management nearest interval approximation method goal programming fuzzy multi-objective linear programming nuclear power plant

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Optimization of land use structure to balance economic benefits and ecosystem services under uncertainties: A case study in Wuhan, China

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JOURNAL OF CLEANER PRODUCTION 2021年 311卷 127537-127537页

作者： Ma, Shuhua Wen, Zhuzhu Nanjing Normal Univ Business Sch Wenyuan Rd 1 Nanjing 210023 Peoples R China Tsinghua Univ PBC Sch Finance 43 Chengfu Rd Beijing 100083 Peoples R China

Rapid economic growth and urbanization in China have led to significant changes in land use structure and seriously threatened the sustainability of urban ecosystems. A fuzzy multi-objective linear programming (FMLP) model is developed in this paper to determine an optimal land use structure with social, economic and ecological benefits of lands considered comprehensively. Ecosystem service assessment is integrated into the FMLP model for emphasizing the ecological benefits of land use, and the uncertainty in the optimization process have been addressed. Wuhan is selected as a case study. The results indicate that (1) the relative equilibrium between economic and ecological benefits can be achieved by establishing the FMLP model. (2) The optimized land use structure can increase the ecosystem service value (ESV) at a lower cost of economic benefits. (3) The optimal land use allocation can contribute to a growth of ecological benefit by 1.51 billion RMB and economic benefit by 348.6 billion RMB compared to the government's land use planning. (4) The ESVs of 11 types of ecosystem service functions are all increased in varying degrees through land use structure optimization. (5) There are huge differences in economic and ecological benefits between the central and remote urban areas of Wuhan. The economic benefit is 603 folds of the ecological benefit in central urban area while the ESV in remote urban area is 25 folds of that of the central urban area in Wuhan. These findings could provide valuable decisionmaking support for the sustainable land use planning in Wuhan. The FMLP model is proven to be feasible and applicable for land use planning under uncertain conditions and thus could be applied to other cities with unbalanced land use structure.

关键词： fuzzy multi-objective linear programming Land use optimization Ecosystem services value Urbanization Wuhan

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A fuzzy multi-objective decision system for recoverable remanufacturing planning

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JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES 2021年第1期42卷 135-154页

作者： Su, Tai-Sheng Wu, Chin-Chun Natl Pingtung Univ Sci & Technol Dept Ind Management 1 Hsueh Fu Rd Pingtung 912 Taiwan I SHOU Univ Dept Informat Management 1Sec 1Syuecheng Rd Kaohsiung 84001 Taiwan

This study develops a novel fuzzy multi-objective decision system (FMODS) that uses the Simplex method, Access database technology and the JAVA programming language, for recoverable product of remanufacturing planning. The system can be used to determine optimal purchase quantities and lot release sizes to make decision system for remanufacturing planning more effective, more convenient and smarter. The system has both single-objective linear programming (SOLP) and fuzzy multi-objective linear programming (FMOLP) functions to help managers in practical situations. The results in this investigation indicate that the proposed FMODS has a very favorable solution time in cases of large demand, and can significantly shorten the production planning time.

关键词： fuzzy multi-objective decision system Remanufacturing planning multiple products fuzzy multi-objective linear programming

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A hybrid approach for selecting sustainable suppliers and determining order allocation based on interval type-2 fuzzy sets

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JOURNAL OF ENTERPRISE INFORMATION MANAGEMENT 2020年第5期33卷 923-945页

作者： Calik, Ahmet KTO Karatay Univ Dept Int Trade & Logist Konya Turkey

Purpose This study aims to create a model for defining the best supplier for a company and allocating order that considers sustainability criteria beyond the traditional selection criteria. Design/methodology/approach In this paper, sustainable supplier Selection and order allocation (SSS and OA) problem is managed based on a multiobjective linear programming (MOLP) model that incorporates sustainability dimensions. First, an interval type-2 fuzzy analytic hierarchy process (FAHP) method is applied for the main criteria and subcriteria to determine the weight of the selected criteria. Then, these values are used to convert the proposed MOLP model into a single-objective model. Findings The economic criterion (0.438) was the most important criterion for SSS in the agricultural machinery sector, followed by the social criterion (0.333) and the environmental criterion (0.229). Practical implications The results show that the proposed framework can be utilized by the agricultural machinery industry for SSS and OA. Originality/value The proposed framework provides to develop an integrated model by interval type-2 fuzzy sets for SSS and OA, taking into account the relationships between qualitative and quantitative evaluation criteria with different priorities. The validity of the developed model is confirmed by a case study of the agricultural machinery industry in Turkey.

关键词： fuzzy multi-objective linear programming Interval type-2 FAHP Nominal group technique Sustainable supplier selection

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Compromised supply chain planning under dominant systems with inventory policies and cost uncertainty

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EUROPEAN JOURNAL OF INDUSTRIAL ENGINEERING 2019年第6期13卷 794-815页

作者： Kaorapapong, Chaidanai Yenradee, Pisal Thammasat Univ Sirindhorn Int Inst Technol Sch Mfg Syst & Mech Engn Pathum Thani 12120 Thailand

In practice, companies with dominant power influence partner operations for their benefits. This paper proposes the supply chain (SC) planning models that determine the optimal sale, pricing, production, and inventory plans of each SC member based on the dominant policy. The theoretical contributions of this paper include a development of linear mathematical functions and explicitly considering the inventory turnover as one of the business performance measures in addition to profit and revenue. The fuzzy multi-objective linear programming models (FMOLP) under dominant systems are developed. A case study in plastic fashion accessory industry in Thailand is performed. The performance measures are translated into satisfaction levels and plotted in a radar chart with an area of possibility, which clearly shows the sensitivity degree of uncertainty. Practical contribution is that this paper recommends suitable pricing and inventory plans based on the dominant policy. [Submitted: 15 August 2018;Accepted: 18 March 2019]

关键词： supply chain planning dominant policies inventory policies multiple objectives compromised solution fuzzy costs fuzzy multi-objective linear programming FMOLP

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A model for the selection of transportation modes in the context of sustainable freight transportation

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INDUSTRIAL MANAGEMENT & DATA SYSTEMS 2019年第8期119卷 1764-1784页

作者： Fulzele, Vijayta Shankar, Ravi Choudhary, Divya Shiv Nadar Univ Sch Management & Entrepreneurship Dept Decis Sci Operat Management & Informat Syst Greater Noida India Indian Inst Technol Delhi Dept Management Studies New Delhi India Indian Inst Management Sambhalpur Burla India

Purpose A sustainable freight transportation system involves freight processes that are economically efficient, socially inclusive and environment friendly. For enhancing sustainability in the freight operations, mode selection is a crucial strategic decision. Therefore, the purpose of this paper is selecting the best mode, or a combination of modes based on various criteria to carry shipments from origin to destination. Design/methodology/approach This study has used an integrated grey relational analysis based intuitionistic fuzzy multi-criteria decision-making process (GRA-IFP) and fuzzy multi-objective linear programming model. Three scenarios have been developed for analyzing sensitivity of decision variables with the variations in parameters under relevant conditions. A real case of Indian third-party logistics service provider has been used to demonstrate the effectiveness of the model. Findings The most relevant criterion emerged out in this study for multi-mode selection problem is costs. It can be concluded from the study that multi-modal freight transportation has the potential to improve the sustainability of freight transportation by reducing the costs, damages, emissions, traffic congestion and by increasing the speed of delivering the shipment. The sensitivity analysis further shows that road is the economical mode, whereas sea and rail together are the greenest as well as socially responsible modes of transportation. Originality/value This study provides an integrated tool, which can be used by freight transporters to decide upon the sustainable modes of transportation for their various shipments.

关键词： fuzzy multi-objective linear programming Intuitionistic fuzzy numbers multi-mode freight transportation Sustainable freight transportation system

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Evaluating decision-making units under uncertainty using fuzzy multi-objective nonlinear programming

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INFOR 2017年第1期55卷 1-15页

作者： Angiz, Madjid Langroudi Zerafat Nawawi, Mohd Kamal Mohd Khalid, Ruzelan Mustafa, Adli Emrouznejad, Ali John, Robert Kendall, Graham Univ Utara Malaysia Sch Quantitat Sci Sintok Malaysia Univ Sains Malaysia Sch Math Sci Gelugor Malaysia Aston Univ Aston Business Sch Birmingham W Midlands England Univ Nottingham Sch Comp Sci ASAP Res Grp Nottingham England Univ Nottingham Malaysia Campus Sch Comp Sci Semenyih Malaysia

This paper proposes a new method to evaluate decision-making units (DMUs) under uncertainty using fuzzy data envelopment analysis (DEA). In the proposed multi-objective nonlinear programming methodology, both the objective functions and the constraints are considered fuzzy. This model is comprehensive in dealing with uncertainty, in the sense that coefficients of the decision variables in the objective functions and in the constraints, as well as the DMUs under assessment, are assumed to be fuzzy numbers with triangular membership functions. A comparison between the current fuzzy DEA models and the proposed method is illustrated by a numerical example.

关键词： fuzzy DEA membership function fuzzy multi-objective linear programming possibility programming

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Application of fuzzy multi-objective linear programming Model in a multi-Period multi-Product Production Planning Problem

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INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS 2011年第2期4卷 228-243页

作者： Taghizadeh, Kaveh Bagherpour, Morteza Mahdavi, Iraj Mazandaran Univ Sci & Technol Dept Ind Engn Babol Sar Iran Iran Univ Sci & Technol Dept Ind Engn Tehran Iran

The multi-Period multi-Product (MPMP) production planning, as a well known problem in literature, attempts to match production rates of individual products with fluctuated market demand over planning horizon. This study, demonstrates how the conventional MPMP linear programming (LP) model may fail to utilize available capacity of machines, and also a novel multi objective linear programming (MOLP) model is developed to simultaneously minimize net present value of production costs and maximize machine utilization. The proposed model consists of production constraints such as available labor, inventory, maximum subcontracting levels and also forecasted demands. The proposed MOLP model is further converted to a fuzzy multi objective linear programming (FMOLP) model utilizing piecewise linear membership functions. The model, accommodates the Decision Maker (DM) with a more systematic decision making approach enabling the DM to adjust the search direction during the solving procedure to achieve the most satisfactory result.

关键词： multi-Period multi-Product production planning Aggregate production planning fuzzy multi-objective linear programming Piecewise linear membership functions Mixed Integer linear programming

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