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Optimizing vendor selection in food supply chains: a goal programming approach using interval type-2 trapezoidal fuzzy numbers

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INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT 2025年第4期16卷 1607-1631页

作者： Gupta, Srikant Gupta, Neha Kamal, Murshid Chatterjee, Prasenjit Jaipuria Inst Management Dept Operat & Decis Sci Jaipur India Amity Univ Uttar Pradesh Amity Sch Business Noida India Aligarh Muslim Univ Dept Stat & Operat Res Aligarh India Vilnius Gediminas Tech Univ Inst Sustainable Construct Lab Smart Bldg Syst LT-10223 Vilnius Lithuania Yuan Ze Univ Coll Engn Taoyuan Taiwan

The selection of an effective and efficient vendor plays a crucial role in achieving a competitive advantage in food supply chain management. This study focuses on the complex decision-making process of vendor selection problem, considering multiple quantitative and qualitative factors. The primary objectives of this research are to minimize net ordering costs, transportation costs, and late deliveries. Recognizing the presence of uncertainty in input parameters, Interval type-2 trapezoidal fuzzy numbers are used to effectively capture and represent this uncertainty. Through the calculation of expected values, a precise equivalent form is derived. The study employed exponential smoothing forecasting analysis to estimate product demand accurately, reducing the risk of shortages and associated financial losses. To attain a mutually satisfactory solution, a fuzzy goal programming methodology was applied. A numerical example was presented to illustrate the methodology's practical applicability and provide deeper insights into its underlying concepts. The solution successfully minimized the net ordering cost for aggregate demand to a value of 6,115,073. The total net cost of transportation for all products was reduced to 279,361, and the number of vendors' late deliveries was minimized to 153,152. The order quantities for the selected vendors were determined as 5236, 9376, 6358, and 4360 units, respectively. Vendors 1, 3, and 4 exhibited superior performance, whereas Vendor 2 experienced a substantial reduction in allocation due to poor performance.

关键词： Vendor selection Fuzzy goal programming multi-objective programming Time series Interval type-2 trapezoidal fuzzy numbers

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A multi-objective optimization approach for sustainable management of computers E-waste in a closed-loop supply chain network

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JOURNAL OF CLEANER PRODUCTION 2025年 506卷

作者： Diaz, Jorge David Restrepo Amin, Saman Hassanzadeh Toronto Metropolitan Univ Dept Mech Ind & Mechatron Engn Toronto ON M5B 2K3 Canada

This study explores the integration of reverse and forward supply chains in a Closed-Loop Supply Chain (CLSC) for electronic waste management, driven by business and government regulatory concerns. It highlights the economic benefits and efficient management of Electronic Waste (E-waste), particularly focusing on End-of-Life (EoL) products to tackle the global E-waste crisis. This research introduces a novel multi-objective mixed-integer linear programming model adapted for an E-waste CLSC network. This model incorporates hybrid manufacturing facilities and Triple Bottom Line (TBL) objectives to maximize profits and social innovations while minimizing gas emissions to reduce landfill waste. An application involving a computer manufacturing network in Ontario, Canada, utilizing Google Maps for distance calculations, illustrates the design and optimization impact of an electronic CLSC network. This study employs computational experiments and sensitivity analyses, using three solution methods, including weighted-sum, epsilon-constraint, and hybrid approaches within a multiperiod framework to validate the model's robustness. These methods help decision-makers integrate a TBL approach into the CLSC network which reflects economic, environmental, and social factors. By generating Pareto optimal solutions using these methods, decision-makers can evaluate different options through trade-off analysis. The findings show that the epsilon-constraint method offers a greater number of efficient solutions, enabling a better balance of objectives. Finally, this study concludes with managerial insights and recommendations based on the research outcomes. The findings provide insights into product and part flows, facilities utilization, and distribution across the network segments.

关键词： Closed-loop supply chain (CLSC) Electronic waste (E-waste) Reverse logistics (RL) multi-objective programming Sustainability

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FLEXIBLE MATCHING OF multi-SKILLED WORKERS AND OPERATION UNITS IN THE HYBRID ROTATING SERU PRODUCTION SYSTEM: AN OPTIMIZATION MODEL-BASED METHOD

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JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION 2025年第2期21卷 1007-1038页

作者： Huang, Kunyuan Jiang, Yanping Xu, Mengyang Zheng, Tingwen Northeastern Univ Sch Business Adm Shenyang Peoples R China

In the hybrid rotating seru production system (HRSPS), how to match multi-skilled workers and operation units is an important problem. The operation units include rotating serus and assembly line processes. This paper proposes a flexible matching method of multi-skilled workers and operation units considering possible absences of multi-skilled workers in the HRSPS. First, the principles of matching scheme generation and the principles of matching scheme adjustment under absences are proposed. Second, according to the preference information of multi-skilled workers and operation units, the preference degree calculation methods are proposed. Furthermore, a multi-objective programming model for the flexible matching of multi-skilled workers and operation units is constructed, and an improved multi-objective particle swarm optimization algorithm (IMOPSO) is proposed to solve the model better. The numerical experiment results demonstrate that the method proposed in this paper can generate and adjust matching schemes in a relatively short time, and what is more, the obtained matching schemes and matching adjustment schemes have advantages in the satisfaction of multi-skilled workers and operation units. Therefore, the method proposed in this paper is feasible and effective.

关键词： multi-skilled worker HRSPS Flexible matching multi-objective programming IMOPSO

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Modeling third-party reverse logistics for healthcare waste recycling in the post-pandemic era

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2025年第2期63卷 651-686页

作者： Singh, Meenu Jauhar, Sunil Kumar Pant, Millie Paul, Sanjoy Kumar VSB Tech Univ Ostrava Fac Elect Engn & Comp Sci Ostrava Czech Republic Indian Inst Management Operat Management & Decis Sci Kashipur Uttaranchal India Indian Inst Technol Dept Appl Math & Sci Comp Roorkee Uttaranchal India Indian Inst Technol Mehta Family Sch Data Sci & Artificial Intelligenc Roorkee Uttaranchal India Univ Technol Sydney UTS Business Sch Sydney Australia Indian Inst Technol Mehta Family Sch Data Sci & Artificial Intelligenc Roorkee 247001 Uttaranchal India

The COVID-19 pandemic has increased the demand for life-saving devices known as 'ventilators,' which help critically ill patients breathe. Owing to the high global demand for ventilators and other medical equipment, many Indian nonmedical equipment companies have risen to meet this demand. This unexpected demand for ventilators during the COVID-19 pandemic, similar to that for other EOL electronic medical devices, has become a severe problem for the nation. Consequently, the healthcare industry must efficiently handle EOL ventilators, which can be outsourced to 3PRLPs. 3PRLPs play a vital role in a company's reverse logistics activities. This study emphasises the 3PRLP selection process as a complex decision-making problem and the optimisation of order allocation to qualified 3PRLPs. As a result, this study proposes a two-phase hybrid decision-making problem. First phase combines the two multi-attribute decision-making methods to select 3PRLPs based on their assessed SPS and Second phase, the evaluated SPS was utilised as one of the objectives of a multi-objective linear programming model to allocate orders to the selected 3PRLPs. To solve the proposed model, both classical and modern approaches were used. The results show that the proposed framework can be successfully implemented in the current scenario of the healthcare industry.

关键词： Reverse logistics waste recycling multi-objective programming order allocation healthcare industry

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Promoting ecological sustainability in the arid farming-pastoral ecotone through optimal water allocation

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JOURNAL OF HYDROLOGY 2025年 652卷

作者： Ji, Jiachen Zhao, Tianqi Wu, Zihan Zhang, Fan Yan, Jing Lu, Naijing Beijing Forestry Univ Sch Soil & Water Conservat Jixian Natl Forest Ecosyst Observat & Res Stn CNERN Beijing 100083 Peoples R China China Inst Water Resources & Hydropower Res Yinshanbeilu Grassland Ecohydrol Natl Observat & R Beijing 100038 Peoples R China

The ecological fragility of arid farming-pastoral ecotones is pronounced, and the promotion of regional ecological sustainability under the constraints of limited resources has become a crucial issue for these zones. This study presents a novel framework for evaluating ecological sustainability, quantifying its relationship with ecological water consumption, and optimizing water resources allocation for improving ecological sustainability. A fuzzy credibility-constrained stochastic multi-objective programming (FCCSMOP) model is applied to optimize regional water allocation schemes. The proposed approach has advantages in: (1) quantifying the water-driven dynamics of ecological sustainability at the county scale;(2) balancing economic, ecological, and social benefits;and (3) addressing randomness and fuzziness caused by hydrological variability and water managers' preferences. This approach was applied to the northern foot of Yinshan Mountain (NFYM), Inner Mongolia Autonomous Region, China, leading to the following findings: (1) ecological sustainability in NFYM is poor, with 70.31% of the region having an ecological sustainability score below 0.43 in 2019;(2) there is a positive relationship between ecological sustainability and water consumption with the relatively high correlation (R2 is an element of [0.39, 0.87]);(3) the FCCSMOP model can effectively address the multiple conflicting objectives, randomness, and fuzziness when generating optimal water allocation schemes. A comparison between the optimization results (normal year, beta=0.75) and the status quo shows improvements of 5.60%, 19.45%, and 6.35% in ecological sustainability, water use efficiency, and the index of water use structure balance, respectively. The models and methods can also be applied to similar regions suffering water and ecological crisis.

关键词： Ecological sustainability Water-driven dynamics Optimal water allocation multi-objective programming Arid farming-pastoral ecotones

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An Application of Fully Intuitionistic Fuzzy multi-objective Linear Fractional programming Problem in E-education System

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INTERNATIONAL JOURNAL OF FUZZY SYSTEMS 2022年第8期24卷 3544-3563页

作者： Malik, Manisha Gupta, S. K. Indian Inst Technol Roorkee Dept Math Roorkee 247667 Uttar Pradesh India

This article addresses a special class of non-linear programming problems, viz., linear fractional programming problems having multiple objectives. In solving the real-life linear fractional optimization problems, the ambiguity and hesitation in the decision are inherent and ever-present, therefore, it is perfectly viable to formulate and solve these optimization models using the intuitionistic fuzzy environment. The purpose of this study is to propose a simple and computationally efficient approach to obtain the solution of multiple objective linear fractional programming problems having all the decision variables and parameters expressed in terms of triangular intuitionistic fuzzy numbers. The proposed solution algorithm is primarily based on the goal programming approach, fuzzy-based linearization technique, and a membership function strategy. The original linear fractional programming problem is first converted to its equivalent deterministic/crisp multi-objective linear fractional optimization problem using the weighted goal programming methodology along with the linear membership technique to resolve the intuitionistic fuzzy constraints into the crisp one. Finally, the variable transformation technique for the under- and over-deviational variables of the goal programming model is employed to linearize all the fractions involved in the problem so as to convert the original problem to an equivalent linear optimization problem. Further, this linear programming problem can be solved using any available commercial packages. Moreover, a numerical illustration is provided to demonstrate the steps of the proposed technique followed by the analysis and solution of an E-education set-up problem. The discussion and comparisons of the practical case establish the relevancy and usefulness of the proposed model.

关键词： multi-objective programming Triangular intuitionistic fuzzy number Goal programming Linear fractional programming problem Fuzzy mathematical programming

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Solving multi-objective fuzzy probabilistic programming problem

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2014年第2期26卷 935-948页

作者： Acharya, S. Ranarahu, N. Dash, J. K. Acharya, M. M. KIIT Univ BBSR Sch Appl Sci Bhubaneswar Orissa India SOA Univ BBSR Dept Math Bhubaneswar Orissa India

Most of the real world decision making problems involve uncertainty, which arise due to incomplete information or linguistic information on data. Stochastic programming and fuzzy programming are two powerful techniques to solve such type of problems. Fuzzy stochastic programming is concerned with optimization problems in which some or all parameters are treated as fuzzy random variables in order to capture randomness and fuzziness under one roof. A method for solving multi-objective fuzzy probabilistic programming problem is proposed in this paper. The uncertain parameters are considered as fuzzy log-normal random variables. Since the existing methods are not enough to solve fuzzy probabilistic programming problem directly, therefore the mathematical programming model is transformed to an equivalent multi-objective crisp model. Finally, a fuzzy programming technique is used to solve the multi-objective crisp model. The resulting model is then solved by standard non-linear programming methods. In order to illustrate the methodology a numerical example is provided.

关键词： Stochastic programming multi-objective programming fuzzy programming fuzzy log-normal random variables

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Advantages, sensitivity and application efficiency of the new iterative method to solve multi-objective linear fractional programming problem

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CENTRAL EUROPEAN JOURNAL OF OPERATIONS RESEARCH 2023年第3期31卷 751-767页

作者： Peric, Tunjo Matejas, Josip Babic, Zoran Univ Zagreb Fac Econ & Business Dept Math Trg J F Kennedya 6 Zagreb 10000 Croatia Univ Split Rudera Boskovica 31 Split 21000 Croatia

In the paper we consider advantages, sensitivity and application efficiency of the new method for solving multi-objective linear fractional programming problems. The proposed method is an iterative and numerically simple method that provides a unique solution in each iteration. The obtained solution is iteratively evaluated with the possibility of coarse and fine adjustment based on aspirations and cooperation among decision makers. Some relevant examples from the literature were used to present the stated properties and advantages of the proposed method in relation to the existing ones.

关键词： multi-objective programming Linear fractional programming Iterative method Sensitivity Efficient solution

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Fuzzy random multi-objective optimization using a novel mixed fuzzy random inverse DEA model in input-output production

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JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 2025年 470卷

作者： Huang, Lizhen Chen, Lei Fuzhou Univ Sch Econ & Management Fuzhou 350108 Fujian Peoples R China

Inverse data envelopment analysis (DEA), which is an effective tool for determining inputs and outputs, is commonly applied in areas such as output prediction, resource allocation, and target setting. However, existing inverse DEA methods typically assume precise and deterministic data, which limits applicability in uncertain production environments, particularly when both random and fuzzy environments are present. This study introduces a novel inverse DEA approach for optimizing inputs and outputs in mixed uncertainty environments. The proposed model allows decision-makers to achieve target efficiency and meet various input/output targets under different production scale assumptions. First, a new optimality principle for multi-objective fuzzy random problems is presented and the necessary theoretical conditions for input/output calculations are derived. Second, an equivalent linear model is introduced to solve the inverse DEA problem with fuzzy random variables, thereby overcoming the challenges associated with nonlinear programming. Notably, the proposed model offers enhanced flexibility as it does not rely on specific fuzzy numbers or predefined assumptions regarding random distributions. Finally, the effectiveness of the model is validated through numerical examples and a case study, demonstrating its practical application in complex decision-making scenarios.

关键词： Inverse data envelopment analysis Mixed uncertainty Fuzzy random variable multi-objective programming

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Stochastic two-stage multi-objective unit commitment of distributed resource energy systems considering uncertainties and unit failures

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RELIABILITY ENGINEERING & SYSTEM SAFETY 2025年 253卷

作者： Liu, Jingfan Zhang, Shijie Chinese Acad Sci Inst Engn Thermophys Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

Compared to centralized generation technology, distributed energy resource systems are susceptible to energy risks caused by boundary uncertainties and unit failures. This study introduces a stochastic two-stage multi- objective optimization method to address reliability-based unit commitment issues. In the day-ahead stage, operational state and reserve capacity are determined to minimize prescheduled operation costs based on forecasted parameters. In the real-time stage, a decision-dependent stochastic reliability method is proposed to simulate outage scenarios. Reserve resources within available units are allocated to mitigate forecasting errors and unit failures. Additionally, the grid interaction ratio and penalty cost are added to restrict the depth and frequency access to the grid. Four comparative cases analyze the effects of the proposed methodology. This method innovatively achieves the simulation of stochastic multi-unit outages and delete faulty units in the operation scheme. The optimal results show that the risks of electricity and cooling supply are underestimated, while the risks of heating are overestimated, compared to N-1 reliability. Furthermore, Pareto analysis of the multi-objective problem enhances independent operational capacity through utilization of reserve resources. Grid dispatch pressure is reduced since purchased power can be used as day-ahead planning. Thus, the methodology achieves collaborative optimization of reliability with a reduction of operation costs, offering effective guidance for engineering applications.

关键词： Distributed energy resource system Uncertainties and outages Stochastic two-stage UC Energy and reserve scheduling multi-objective programming

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