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A quantitative model for disruption mitigation in a supply chain
یک مدل کمی برای کاهش ضعف در یک زنجیره تامین-2017
In this paper, a three-stage supply chain network, with multiple manufacturing plants, distribution cen ters and retailers, is considered. For this supply chain system we develop three different approaches, (i) an ideal plan for an infinite planning horizon and an updated plan if there are any changes in the data, (ii) a predictive mitigation planning approach for managing predictive demand changes, which can be predicted in advance by using an appropriate tool, and (iii) a reactive mitigation plan, on a real-time basis, for managing sudden production disruptions, which cannot be predicted in advance. In predictive mitigation planning, we develop a fuzzy inference system (FIS) tool to predict the changes in future de mand over the base forecast and the supply chain plan is revised accordingly well in advance. In reactive mitigation planning, we formulate a quantitative model for revising production and distribution plans, over a finite future planning period, while minimizing the total supply chain cost. We also consider a series of sudden disruptions, where a new disruption may or may not affect the recovery plans of earlier disruptions and which consequently require plans to be revised after the occurrence of each disruption on a real-time basis. An efficient heuristic, capable of dealing with sudden production disruptions on a real-time basis, is developed. We compare the heuristic results with those obtained from the LINGO optimization software for a good number of randomly generated test problems. Also, some numerical examples are presented to explain both the usefulness and advantages of the proposed approaches.
Keywords: Supply chain | Mitigation | Production disruption | Quantitative model | Heuristic
بازیابی و بازیافت لاستیکهای زباله در لهستان
سال انتشار: 2017 - تعداد صفحات فایل pdf انگلیسی: 6 - تعداد صفحات فایل doc فارسی: 11
هدف این مقاله مشخص کردن بازار بازیابی و بازیافت لاستیک زباله در لهستان و نشان دادن روند توسعه در این منطقه است. در این مطالعه، شرایط سازمانی و حقوقی برای بازیابی و بازیافت لاستیک های دست دوم مورد تجزیه و تحلیل قرار گرفته است. علاوه بر این، مشکلات عمده و چشم انداز توسعه بازار بازیافت و بازیابی زباله لاستیک ها برجسته شده است. روش های تحقیقاتی مانند تجزیه و تحلیل متون مکتوب، قوانین و تجزیه و تحلیل داده های آماری مورد استفاده قرار گرفته است. یافته های اصلی تحلیل ها این است که لاستیک های استفاده شده از ضایعات مشکل ساز تبدیل به مواد خام مطلوب در صنعت می شوند. این امر به لطف اجرای ابزارهای موثر مدیریتی در مدیریت ضایعات امکان پذیر بود.
کليدواژگان: بازيافت | بهبود | مدیریت زباله | لاستیک های دست دوم
|مقاله ترجمه شده|
Risk-cost optimization for procurement planning in multi-tier supply chain by Pareto Local Search with relaxed acceptance criterion
بهینه سازی هزینه ریسک برای برنامه ریزی تدارکات در زنجیره تامین چند لایه با جستجوی محلی پارکتو با معیار پذیرش آرام-2017
We address a 2-objective optimization problem to minimize a retailer’s procurement cost and risk that is evaluated as recovery time of the retailer’s business after the procurement is suspended by a catastrophic event. In order to reduce the recovery time, the retailer needs to decentralize ordering to multiple suppli ers and have contingency stock, which costs the retailer. In multi-tier supply chains, not only the retailer’s procurement plan but also their suppliers’ procurement plans affect the retailers’ risk and cost. Due to the huge combinations of their plans, it is difficult to find Pareto optimal solutions of the 2-objective optimization problem within a short space of time. We apply Pareto Local Search (PLS) based on heuris tics to generate neighbors of a solution by changing suppliers’ plans in the closer tier to the retailer. The original PLS accepts the solutions that are nondominated neighbor solutions for the next search, but the acceptance criterion is too strict to find all Pareto optimal solutions. We relax the acceptance crite rion in order to include dominated solutions whose Pareto rank is equal to or less than a threshold. The threshold is updated based on changes of Pareto rank during local searches.
Keywords: Risk-cost optimization | Multi-tier supply chain | Pareto Local Search
Closed loop supply chain networks: Designs for energy and time value efficiency
شبکه های زنجیره تامین حلقه بسته: طرح های بازده انرژی و زمان-2017
Product recovery has become a viable option for many industries to realize economic gains while pro tecting the environment. However, insufficient investment and inefficient supply chains have hampered the viability of reuse and/or recycling because of the extended time intervals between the recycling process of recovery and reuse. Manufacturers and distributors face the challenge and necessity to reduce these process delays in order to recover the maximum value of the returned products through an effective, responsive closed loop supply chain (CLSC). This paper quantitatively measures the effective responsiveness of the CLSC model in terms of time and energy efficiency. The proposed multi-objective mixed integer linear programming (MOMILP) model evaluates delay parameters with decision variables that maximize profit, optimize customer surplus and minimize energy use. The model suggests decision makers may achieve an optimal tradeoff among differing objectives in a multiple-objective CLSC sce nario. We employed a multi-objective particle swarm optimization (MOPSO) approach to solve the proposed MOMILP model and compared our approach with the Non-Dominated Sorted Genetic Algo rithm (NSGA-II) for optimal solution. Results of the comparative evolutionary approaches shows that MOPSO outperforms NSGA-II in almost all cases in achieving the best trade-off solutions. Sensitivity analysis carried out to test the robustness of the model confirms that substantially less cost is feasible through the reduction of return process delays. This paper aims to formulate a multi-objective CLSC problem based on a network-flow model measuring the time value to recover maximum assets lost due to delay at different stages of the recycle process. We also developed a particle swarm approach for a multi-objective CLSC. Our study also offers valuable insights for designers wishing to create a product flow network with an optimal capacity level in case of prioritized objectives scenarios.
Keywords: Closed loop supply chain | Product recovery | Time-sensitive product returns | Multi-objective particle swarm | optimization
Minimization of disruption-related return flows in the supply chain
به حداقل رساندن بازگشت مربوط به اختلال جریان در زنجیره تامین-2017
Recent research on closed-loop supply chains (SC) and reverse logistics extensively emphasises the crucial role of reducing negative return flows such as emissions, waste, etc. In this study, we consider the return flows in the SC in light disruptive events in the SC. The objective of this study is to compare the performance impact of different recovery policies on return flows subject to the simultaneously opti mized re-configuration plans for material flows. We formulate a multi-objective problem with return flow reduction function for a multi-period, multi-stage, multi-product SC. We consider a recovery pro blem with ripple effect, performance impact assessment and re-planning decisions. The developed multi objective hybrid linear programming-system dynamics model allows simultaneously re-computing the material flows in a multi-stage SC after a disruption and comparing the performance impact of different recovery policies subject to return flows, gradual capacity recovery, variable recovery costs and time. The results suggest that the consideration of gradual capacity recovery leads to minimization of disruption related return flows in both upstream and downstream SC parts. Fast and expensive recovery strategy provides the lowest return costs in the upstream SC part as compared to normal and slow recovery policies. Similar, the profits and service levels are increased. In the fast and expensive recovery policy, the performance in the upstream and downstream does not change with the introduction of the gradual recovery considerations. The effects of gradual capacity recovery introduction become evident if smaller time sub-periods are considered within the recovery period.
Keywords: Supply chain | Return flows | Disruptions | Recovery | Ripple effect
Carbon emissions and energy effects on a two-level manufacturer-retailer closed-loop supply chain model with remanufacturing subject to different coordination mechanisms
مدل زنجیره تامین انتشار کربن و اثرات انرژی در دو سطح تولید کننده خرده حلقه بسته با موضوع بازسازی به هماهنگی های مختلف-2017
This paper presents two models (classical and VMI-CS coordination) for a two-level closed-loop supply chain with a manufacturer and a retailer with a facility to remanufacture used items. The paper considers three critical environmental issues, which are the energy used in production (manufacturing and re manufacturing) processes, GHG emissions from production and transportation activities (subject to a penalty tax), and the number of times to remanufacture (recover) a used item. Numerical results show that the traditional optimization approach, which minimises the sum of inventory related costs, sug gested less remanufacturing, fewer recovery times and more GHG emissions and energy usage; a result of operating at high production rates. The VMI-CS model was shown to be more economical than the classical model for a wide range of manufacturing rates, but not necessarily a more environmentally responsible choice. An extensive numerical analysis was conducted to enrich the discussion and to draw some managerial insights on how to make environmentally conscious decisions.
Keywords: Closed-loop supply chains | Green supply chains | Greenhouse gas emissions | Carbon emissions | Remanufacturing | Energy
A proactive model in sustainable food supply chain: Insight from a case study
یک مدل بیش فعال در زنجیره تامین پایدار مواد غذایی: بینشی از یک مطالعه موردی-2017
Recently more and more companies are adopting proactive sustainable strategies and developing sus tainable supply chain management practices. Researchers identify Closed-Loop Supply Chain (CLSC) models as one of the major contributors to realising sustainable operations. Such models typically use flows concerning the products only as the unit of analysis. This paper intends to provide a basis for developing new CLSC models, extending them to recovery resources from general outputs (e.g. unavoidable waste) with no value in terms of products. The new models affect also the configuration of the CLSC, with different set of resource suppliers and logistics providers. The case study analysed in this paper derives from the food sector, in which the waste produced is reused as a resource, avoiding the disposal of different materials through resource-recovery activities that allow waste to be returned to the main supply chain as valuable inputs to configure a new supply chain. The principal objective of this study is to create a new sustainable model of CLSC using and re covering waste from meat processing. A profitability indicator, an energy self-sufficiency one and a qualitative assessment of social implications are introduced to evaluate global sustainability opportu nities for activating new loops.
Keywords: Closed-loop supply chain | Food industry | Case study | Resources recovery | Sustainability
Closed-loop supply chain network design under uncertain quality status: Case of durable products
طراحی شبکه زنجیره تامین حلقه بسته به وضعیت کیفیت نامطلوب: موردی از محصولات با دوام-2017
This paper proposes a two-stage stochastic mixed-integer programming model for a closed-loop supply chain network design problem in the context of modular structured products in which the reverse network entails several types of recovery options. It accounts for uncertainty in the quality status of the return stream, modeled as binary scenarios for each component in the reverse bill of material corre sponding to such products. To deal with the intractable number of scenarios in the proposed model, a scenario reduction scheme is adapted to the problem of interest to preserve the most pertinent scenarios based on a modified Euclidean distance measure. The reduced stochastic large-scale optimization pro blem is then solved via a L-shaped algorithm enhanced with surrogate constraints and Pareto-optimal cuts. Numerical results indicate that the scenario reduction algorithm provides good quality solutions to the stochastic problem in a reasonable amount of time through applying the enhanced L-shaped method.
Keywords: Stochastic closed-loop supply chain |Uncertain quality status |Durable products |Scenario reduction |L-shaped
Two-way product recovery in a closed-loop supply chain with variable markup under price and quality dependent demand
بازیابی محصول دو طرفه در زنجیره تامین حلقه بسته با نشانه گذاری متغیر تحت قیمت و تقاضای وابسته به کیفیت-2017
This article considers a two-way product recovery in a two-echelon closed-loop supply chain which comprises one manufacturer and one retailer for trading a single product. The market demand of the product is linearly dependent on selling price and product quality. The retailer sets the selling price with a variable markup on the wholesale price of the manufacturer. The manufacturer also sets his wholesale price with a fixed markup on the production cost of the product. The retailer recovers the used product in two ways. He collects from consumers the used products, which is a fraction of newly sold products in the forward channel. He also collects the used products through an exchange offer and replaces a fraction of the collected used products by new ones. We analyze the proposed model under four different decision structures: decentralized (Nash game), manufacture led and retailer-led Stackelberg games and centralized (cooperative game) structures. We then compare these policies to identify the best policy. We also examine the feasibility of the cooperative game through a bargaining model. To examine the effects of key model-parameters on the decisions, we perform a sensitivity analysis for a numerical example.
Keywords: Two-way product recovery | Exchange offer | Product quality | Variable markup |Closed-loop supply chain
Humanoid push recovery using sensory reweighting
بازیابی فشار انسان نما با استفاده از تطبیق وزن حسی-2017
Article history:Available online 6 May 2017Keywords:Humanoid fall avoidance Sensory reweightingIn this paper we propose a novel system that uses sensory input from both vision and inertial sensors for an improved perception of the robot current status of equilibrium. We use MonoSLAM vision odometry as a basis for the visual perception and a gyro for angular velocity measurements; and we devise a reweighting method within a Kalman filter framework. Moreover, our approach is designed to be robust against visual and measurement noise such as blur, poor lighting conditions, and faulty sensory output. The novelty in this work is a robust humanoid fall avoidance system, which relies on the fusion of sensory input, mainly gyroscope and visual odometry, taking into account changes in the environment. The fusion of the mentioned sensors in addition to the image quality assessment, ensure a more human-like fall avoidance in comparison to currently existing systems. We implement our method on the NAO humanoid, where seven sets of experiments are performed to assess the effectiveness of our approach. The fusion of camera and gyro information not only enables a more human-like behavior, but also provides more humanoid stability and faster recovery, and thus leads to more robust fall avoidance.© 2017 Elsevier B.V. All rights reserved.
Keywords:Humanoid fall avoidance | Sensory reweighting