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Artykuły w czasopismach na temat "Dynamic supply chain-Fuzzy logic"
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Poornikoo, Mehdi, and Muhammad Azeem Qureshi. "System dynamics modeling with fuzzy logic application to mitigate the bullwhip effect in supply chains." Journal of Modelling in Management 14, no. 3 (2019): 610–27. http://dx.doi.org/10.1108/jm2-04-2018-0045.
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Purpose A plethora of studies focused on the cause and solutions for the bullwhip effect, and consequently many have successfully experimented to dampen the effect. However, the feasibility of such studies and the actual contribution for supply chain performance are yet up for debate. This paper aims to fill this gap by providing a holistic system-based perspective and proposes a fuzzy logic decision-making implementation for a single-product, three-echelon and multi-period supply chain system to mitigate such effect. Design/methodology/approach This study uses system dynamics (SD) as the central modeling method for which Vensim® is used as a tool for hybrid simulation. Further, the authors used MATLAB for undertaking fuzzy logic modeling and constructing a fuzzy inference system that is later on incorporated into SD model for interaction with the main supply chain structure. Findings This research illustrated the usefulness of fuzzy estimations based on experts’ linguistically and logically defined parameters instead of relying merely on the traditional demand forecasting based on time series. Despite the increased complexity of the calculations and structure of the fuzzy model, the bullwhip effect has been considerably decreased resulting in an improved supply chain performance. Practical implications This dynamic modeling approach is not only useful in supply chain management but also the model developed for this study can be integrated into a corporate financial planning model. Further, this model enables optimization for an automated system in a company, where decision-makers can adjust the fuzzy variables according to various situations and inventory policies. Originality/value This study presents a systemic approach to deal with uncertainty and vagueness in dynamic models, which might be a major cause in generating the bullwhip effect. For this purpose, the combination between fuzzy set theory and system dynamics is a significant step forward.
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Jamegh, Riyadh, Dr AllaEldin Kassam, and Dr Sawsan Sabih. "DEVELOPMENT OF FUZZY LOGIC APPROACH TO OPTIMIZE SAFETY STOCK LEVEL IN DETERIORATED PRODUCTS/A SUPPLY CHAIN DAIRY INDUSTRIES CASE STUDY." Al-Qadisiyah Journal for Engineering Sciences 11, no. 3 (2019): 332–44. http://dx.doi.org/10.30772/qjes.v11i3.564.
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In today's complex environment, a high responding ability represents a core for each organization to survive in a competitive environment. To grip your position in intense competition market, the organization must design high efficiency inventory system that has the ability to respond to changes in demand and at the same time reduce holding cost of accommodation to the lowest possible value by controlling inventory drivers such as safety stock level (SS). The traditional approaches of safety stock are limited to deal with dynamic behavior of market. Advanced approaches based on soft computing allow the dynamic updating of SS level. In this paper, a highly advanced dynamic fuzzy logic (DFL) has been suggested as an innovation step to identify safety stock level in dairy industries with objective of minimizing total cost and meet with customer requirements. The proposed approach consists of three main steps firstly, identifying demand uncertainty conditions by applying fuzzy logic steps embedded by identifying dynamic (N) factor which represents the increasing level in demand in period time. Secondly, identifying of raw material availability conditions by applying fuzzy logic steps, and finally, identification of inventory on hand conditions by applying fuzzy logic steps. It is necessary to identify the level of SS dynamically in fuzzy logic as an output embedded with identifying of period specification concept which describes states of demand in a specific period in which the demand is high, medium, or low which leads to identify maximum values of universe of discourse of output (safety stock). Here Matlab program was used. The provided solution demonstrates the proposed model validity. There has been a significant reduction in safety stock level ranging from (7-98)% depending on product type and period specification with a reduction also in holding cost, while keeping the requirements fulfillment of customers demand
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Xu, Bowei, Weiting Liu, and Junjun Li. "Resilience Regulation Strategy for Container Port Supply Chain under Disruptive Events." Journal of Marine Science and Engineering 11, no. 4 (2023): 732. http://dx.doi.org/10.3390/jmse11040732.
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There are many inevitable disruptive events, such as the COVID-19 pandemic, natural disasters and geopolitical conflicts, during the operation of the container port supply chain (CPSC). These events bring ship delays, port congestion and turnover inefficiency. In order to enhance the resilience of the CPSC, a modified two-stage CPSC system containing a container pretreatment system (CPS) and a container handling system (CHS) is built. A two-dimensional resilience index is designed to measure its affordability and recovery. An adaptive fuzzy double-feedback adjustment (AFDA) strategy is proposed to mitigate the disruptive effects and regulate its dynamicity. The AFDA strategy consists of the first-level fuzzy logic control system and the second-level adaptive fuzzy adjustment system. Simulations show the AFDA strategy outperforms the original system, PID, and two pipelines for improved dynamic response and augmented resilience. This study effectively supports the operations manager in determining the proper control policies and resilience management with respect to indeterminate container waiting delay and allocation delay due to disruptive effects.
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Matawale, Chhabi Ram, Saurav Datta, and S. S. Mahapatra. "A fuzzy embedded leagility assessment module in supply chain." Benchmarking: An International Journal 23, no. 7 (2016): 1937–82. http://dx.doi.org/10.1108/bij-12-2013-0113.
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Purpose In today’s ever-changing global business environment, successful survival of manufacturing firms/production units depends on the extent of fulfillment of dynamic customers’ demands. Appropriate supply chain strategy is of vital concern in this context. Lean principles correspond to zero inventory level; whereas, agile concepts motivate safety inventory to face and withstand in turbulent market conditions. The leagile paradigm is gaining prime importance in the contemporary scenario which includes salient features of both leanness and agility. While lean strategy affords markets with predictable demand, low variety and long product life cycle; agility performs best in a volatile environment with high variety, mass-customization and short product life cycle. Successful implementation of leagile concept requires evaluation of the total performance metric and development of a route map for integrating lean production and agile supply in the total supply chain. To this end, the purpose of this paper is to propose a leagility evaluation framework using fuzzy logic. Design/methodology/approach A structured framework consisting of leagile capabilities/attributes as well as criterions has been explored to assess an overall leagility index, for a case enterprise and the data, obtained thereof, has been analyzed. Future opportunities toward improving leagility degree have been identified as well. This paper proposes a Fuzzy Overall Performance Index to assess the combined agility and leanness measure (leagility) of the organizational supply chain. Findings The proposed method has been found fruitful from managerial implication viewpoint. Originality/value This paper aimed to present an integrated fuzzy-based performance appraisement module in an organizational leagile supply chain. This evaluation module helps to assess existing organizational leagility degree; it can be considered as a ready reference to compare performance of different leagile organization (running under similar supply chain architecture) and to benchmark candidate leagile enterprises; so that best practices can be transmitted to the less-performing organizations. Moreover, there is scope to identify ill-performing areas (barriers of leagility) which require special managerial attention for future improvement.
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Aengchuan, Prasert, and Busaba Phruksaphanrat. "Inventory System Design by Fuzzy Logic Control: A Case Study." Advanced Materials Research 811 (September 2013): 619–24. http://dx.doi.org/10.4028/www.scientific.net/amr.811.619.
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Existing inventory lot-sizing models assume certain demand and sufficient supply, which are not practical for industry. Dynamic inventory models can serve uncertain demand, but supply is assumed to be available. However, in the real world situation, supply is not always offered. So, the method that can deal with both uncertain demand and supply should be developed. Fuzzy logic control is now being the effective methodology in many applications under uncertainty. Therefore, a fuzzy logic approach for solving the problem of inventory control under uncertainty was proposed for a case study factory. In the proposed Fuzzy Inventory System (FIS), both demand and availability of supply are described by linguistic terms. Then, the developed fuzzy rules are used to extract the fuzzy order quantity and the fuzzy reorder point continuously. The order quantity and reorder point are both adjusted according to the FIS system. In this research, the suitable ranges for the inputs of the FIS model are justified for the case study factory. Moreover, the effect of trend demands for both increase and decrease are also analyzed with the proposed range. Inventory costs of the proposed fuzzy inventory system are compared with the existing model based on historical data of the case study factory. It found that the proposed range can obtain lower cost than the previous research FIS lot-sizing model, which is better than conventional approaches.
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Pérez-Pimentel, Yolanda, Ismael Osuna-Galán, Carlos Avilés-Cruz, and Juan Villegas-Cortez. "Power Supply Management for an Electric Vehicle Using Fuzzy Logic." Applied Computational Intelligence and Soft Computing 2018 (November 5, 2018): 1–9. http://dx.doi.org/10.1155/2018/2846748.
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The technology of power electronic systems has diversified into industrial, commercial, and residential areas. Developing a strategy to improve the performance of the electrical energy of an electric vehicle (EV) requires an analysis of the model that describes it. EVs are complex mechatronic systems described by nonlinear models and, therefore, its study is not an easy task. It can improve the performance of a battery bank by creating new batteries that allow for greater storage or by developing a management energy system. This article shows the development of a power supply management system based on fuzzy logic for an electric vehicle, in order to minimize the total energy consumption and optimize the battery bank. The experimental result is shown using the fuzzy controller under standard operating conditions. An increase in battery performance and overall performance of energy consumption is shown. Speed signals acquired show improvements in some dynamic, such as overshoot, settling time, and steady-state error parameters. It is shown that this fuzzy controller increases the overall energy efficiency of the vehicle.
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Al-Zabidi, Ayoub, Ateekh Ur Rehman, and Mohammed Alkahtani. "An Approach to Assess Sustainable Supply Chain Agility for a Manufacturing Organization." Sustainability 13, no. 4 (2021): 1752. http://dx.doi.org/10.3390/su13041752.
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Worldwide business organizations realize that agility of sustainable supply-chain is a requisite need for survival in a dynamic, competitive, and unpredictable market. The contribution of this research is to explore and evaluate sustainable agility in supply chains for a dairy manufacturing organization located in Saudi Arabia. Other contributions of this research are to update the literature about the different factors contributing to achieve agile supply chain, propose conceptual framework and assessment approach incorporating the relationships between sustainable supply-chain capabilities, enablers, and attributes, and shortlisting the agility barriers and how they would facilitate manufacturing organizations’ performance. The paper presents supply chain agility evaluation approach, which covers identification of agile supply-chain capabilities and drivers. It also presents a conceptual model and a framework to define agility level and barriers within the supply-chain. In the paper, fuzzy logic approach is preferred, owing to its capability to incorporate and deal with problems involving impreciseness and vagueness phenomena. Threshold-value in this study for the case organization is set to 0.24829. The outcome of the adopted approach indicates that 21 attributes performed below the threshold value; these attributes are further categorized as agility barriers. These are the barriers within their supply chain that impact the agility-level. For the case organization, the foremost priority is to enhance maintainability and serviceability to make it flexible and inexpensive to establish an agile responsive supply chain. At the same time, it should have priority to focus on development and integration of their core competencies to deal with cross-functional and cross-enterprise issues in supply chain. For the case organization, the agility level was found “very agile,” although it is below the “extremely agile.” Thus, a study was developed to understand the behaviour of the supply chain agility and assess/evaluate it to support decision makers in order to develop a strategic solution for different organizational barriers.
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Richey, R. Glenn, Chadwick B. Hilton, Michael G. Harvey, Lauren Skinner Beitelspacher, Mert Tokman, and Miriam Moeller. "Aligning operant resources for global performance: An assessment of supply chain human resource management." Journal of Management & Organization 17, no. 3 (2011): 364–82. http://dx.doi.org/10.1017/s1833367200001528.
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AbstractPurpose:The intent of the paper is to develop the service marketing logic (S-D logic) strategy that is centered on service as a means to differentiate global strategy from those of competitors. The context of the paper is to examine S-D logic in global supply chains. Design/Methodology:The paper is a theory driven conceptual piece.Findings:Globalization emphasizes complex interconnected systems, while S-D logic emphasizes the importance of leveraging operant resources in order to achieve sustainable competitive advantage. Both S-D logic and globalization apply in the supply chain context. This paper focuses on the global supply chain and the importance of leveraging service based operant resources. Because the focus of management has shifted from a domestic to a more complex, three-dimensional network, it is critical for practitioners and researchers to understand how to optimize service based operant resources in the global marketplace.Practical Implications:Because the focus of management has shifted from a domestic to a more complex, three-dimensional global network, it is critical for practitioners and researchers to understand how to optimize service based operant resources in the global marketplace. We suggest that in this dynamic marketplace, both globalization and S-D logic are required to fully explain supply chain performance. Specifically, we suggest that managers develop a global ‘supply-chain management’ perspective allowing for the key operant resource – human capital – to create synergistic partner relationships and customer experiences resulting in superior performance.Originality/Value:This is one of the first (if not the first) paper that examines S-D logic in a global context. This move forward from the domestic orientation of many/most of the recent literature provides the foundation for future global research into the S-D logic.
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Richey, R. Glenn, Chadwick B. Hilton, Michael G. Harvey, Lauren Skinner Beitelspacher, Mert Tokman, and Miriam Moeller. "Aligning operant resources for global performance: An assessment of supply chain human resource management." Journal of Management & Organization 17, no. 3 (2011): 364–82. http://dx.doi.org/10.5172/jmo.2011.17.3.364.
Pełny tekst źródłaStreszczenie:
AbstractPurpose:The intent of the paper is to develop the service marketing logic (S-D logic) strategy that is centered on service as a means to differentiate global strategy from those of competitors. The context of the paper is to examine S-D logic in global supply chains. Design/Methodology:The paper is a theory driven conceptual piece.Findings:Globalization emphasizes complex interconnected systems, while S-D logic emphasizes the importance of leveraging operant resources in order to achieve sustainable competitive advantage. Both S-D logic and globalization apply in the supply chain context. This paper focuses on the global supply chain and the importance of leveraging service based operant resources. Because the focus of management has shifted from a domestic to a more complex, three-dimensional network, it is critical for practitioners and researchers to understand how to optimize service based operant resources in the global marketplace.Practical Implications:Because the focus of management has shifted from a domestic to a more complex, three-dimensional global network, it is critical for practitioners and researchers to understand how to optimize service based operant resources in the global marketplace. We suggest that in this dynamic marketplace, both globalization and S-D logic are required to fully explain supply chain performance. Specifically, we suggest that managers develop a global ‘supply-chain management’ perspective allowing for the key operant resource – human capital – to create synergistic partner relationships and customer experiences resulting in superior performance.Originality/Value:This is one of the first (if not the first) paper that examines S-D logic in a global context. This move forward from the domestic orientation of many/most of the recent literature provides the foundation for future global research into the S-D logic.
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Kamal, Esraa, Amal F. Abdel Abdel-Gawad, and Shereen Zaki. "Neutrosophic-based Machine Learning Techniques in the Context of Supply Chain Management: A Survey." International Journal of Neutrosophic Science 21, no. 2 (2023): 142–60. http://dx.doi.org/10.54216/ijns.210213.
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Supply Chain Management (SCM) plays a critical role in the success of any business organization. Individuals involved in business activities often have to make decisions regarding different aspects of the supply chain, including planning, procurement, production, inventory management, transportation, distribution, and customer relationship management. The combination of neutrosophic logic and machine learning has gained significant attention in the field of SCM as a means to tackle uncertainties and improve decision-making. This paper highlights the potential benefits and applications of integrating neutrosophic reasoning and machine learning in SCM. Neutrosophic reasoning provides a framework for handling imprecise and uncertain information, while machine learning techniques offer powerful tools for data analysis, pattern recognition, and predictive modeling. By leveraging machine learning algorithms within the context of neutrosophic logic, SCM practitioners can enhance demand forecasting accuracy, optimize inventory management, improve transportation and routing decisions, and strengthen supply chain collaboration. The integration of neutrosophic logic and machine learning enables the handling of complex supply chain data, accommodates dynamic and uncertain environments, and supports proactive decision-making. Furthermore, the combination of these approaches can contribute to improved supply chain resilience, sustainability, and customer satisfaction. This paper applied the neutrosophic AHP method as a feature section to select the highest importance criteria as an input to machine learning. Then we applied two machine learning models named random forest and decision. The results show the random forest has the highest accuracy followed by a decision tree.