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نتیجه جستجو - multi-objective optimization

تعداد مقالات یافته شده: 77
ردیف عنوان نوع
1 Pricing decisions in a decentralized biofuel supply chain with RIN mechanism considering environmental impacts
تصمیمات قیمت گذاری در زنجیره تأمین سوخت زیستی غیرمتمرکز با مکانیسم RIN با در نظر گرفتن تأثیرات زیست محیطی-2021
This study develops pricing models in a decentralized biofuel supply chain focusing on both economic and environmental aspects. Environmental impacts are used as a measure to reflect the environmental objective function calculated based on ReCiPe method. A bi-level multi-objective stackelberg game model considering farmers and biorefineries as followers and the blender as leader is proposed. An ε-constraint method is utilized to convert the multi-objective model to a single-objective one. The bi-level model is then transformed to a solvable integrated model. Finally, a real case study of switchgrass bioethanol is presented to illustrate the performance of the proposed model. Results show that focusing on environmental goals results in the increasement of selling prices and profits of farmers and biorefineries and decreasment of about %7 in economic profit of the blender. Therefore, tradeoff analyses are performed for objective functions leading to 10 Pareto optimal solutions which give managerial insights to the blender. Moreover, sensitivity analyses are provided with respects to price elasticity and final fuel’s price and results show logical trends in selling prices.
Keywords: Biofuel supply chain | Pricing | Decentralized decision making | Environmental impacts | Multi-objective optimization
مقاله انگلیسی
2 A multi-objective robust optimization model for upstream hydrocarbon supply chain
یک مدل بهینه سازی قوی چند هدفه برای زنجیره تأمین هیدروکربن بالادست-2021
The hydrocarbon supply chain (HCSC) is a significant part of the world’s energy sector. The energy market has experienced erratic behavior over the last few years results in financial risks such as exceeding certain limits of the budget or not achieving the desired levels of cash in-flow, i.e., revenue. In this work, robust optimization and multi-objective mathematical programming are used to develop a model that eliminates or at least mitigates the impact of uncertain market behavior. Robust optimization provides tactical plans that are feasible and robust over market scenarios. The model assesses the trade-offs between alternatives and guides the decision-maker towards the effective management of the HCSC. The economic objectives are to minimize total cost and maximize revenue, while the non-economic objective is to minimize the depletion rate. The model considers the environmental aspect by limiting the emission of CO2 and the sustainability aspect by reducing the depletion rate of natural resources. Uncertain behavior of the oil market is modeled on scenario representation. A case study based on real data from Saudi Arabia HCSC is provided to demonstrate the model’s practicality, and a sensitivity analysis is conducted to provide some managerial insights. The results indicate that Saudi Arabia can cover its entire expenditure, break-evenpoint, by producing oil at 7.18 MMbbld and gas at 3,543.48 MMcftd. Besides, the robust approach provides a preferred plan with the highest cash inflow and the lowest sustainability over other approaches, e.g., deterministic, stochastic, and risk-based. The differences show that the robust model increases oil production to compensate for the variability of the scenario.
KEYWORDS: Hydrocarbon supply chain | Multi-objective optimization | Robust optimization | Scenario-Based Optimization | Tactical planning
مقاله انگلیسی
3 Multi-objective optimization modelling of sustainable green supply chain in inventory and production management
مدلسازی چند هدفه بهینه سازی زنجیره تأمین سبز پایدار در مدیریت موجودی و تولید-2021
The ever increasing pressure to conserve the environment from global warming cannot be overemphasized. Emission from the inventory and production process contributes immensely to global warming and hence, the need to device a sustainable green inventory by the operational managers. In this paper, a multi-item multi-objective inventory model with back-ordered quantity incorporating green investment in order to save the environment is proposed. The model is formulated as a multi-objective fractional programming problem with four objectives: maximizing profit ratio to total back-ordered quantity, minimizing the holding cost in the system, minimizing total waste produced by the inventory system per cycle and minimizing the total penalty cost due to green investment. The constraints are included with budget limitation, space restrictions, a constraint on cost of ordering each item, environmental waste disposal restriction, cost of pollution control, electricity consumption cost during production and cost of greenhouse gas emission in the production process. The model effectiveness is illustrated numerically, and the solution obtained to give a useful suggestion to the decision-markers in the manufacturing sectors.
KEYWORDS: Multi-objective fractional programming | Fuzzy goal programming | Sustainable green supply chain | Inventory and production management
مقاله انگلیسی
4 Analysis of the innovation strategies for green supply chain management in the energy industry using the QFD-based hybrid interval valued intuitionistic fuzzy decision approach
تجزیه و تحلیل استراتژی های نوآوری برای مدیریت زنجیره تامین سبز در صنعت انرژی با استفاده از فاصله ترکیبی مبتنی بر QFD ، ارزش تصمیم گیری فازی شهودی-2021
This study aims to analyze the innovation strategies for the green supply chain management with QFD (quality function deployment) multidimensionally. The novelty of the study is to define the criteria of green supply chain for each stage of QFD and propose a hybrid model by IVIF (interval-valued intuitionistic fuzzy) DEMATEL (decision making trial and evaluation laboratory) and IVIF MOORA (Multi-Objective Optimization by Ratio Analysis) respectively. The results demonstrate that understanding the customer expectations with customer relation management is the most important innovation strategy for the green supply chain management in en- ergy industry with the consecutive stages of QFD whereas benchmarking the competitive market environment has relatively the last seat in the ranking. Hence, it is recommended that energy companies should have an effective customer relationship management. In this context, these companies should make a detailed analysis to learn what their customers directly expect from them. With the help of this issue, these companies should generate their product and services based on these expectations. Additionally, it is also stated that new service and product development is also essential for energy companies to improve their innovativeness. For this pur- pose, a research and development department should be created, and the qualified people should be employed. Additionally, different opinions should be collected from various parties, such as customers, employees, and suppliers. Since customers who are satisfied will prefer these companies, the energy companies can catch the opportunity to increase their market share.
Keywords: GSCM | Energy industry | Innovation | QFD | IVIF DEMATEL | IVIF MOORA
مقاله انگلیسی
5 A methodological design framework for hydrogen and methane supply chain with special focus on Power-to-Gas systems: application to Occitania region, France
یک چارچوب طراحی روش برای زنجیره تأمین هیدروژن و متان با تمرکز ویژه بر روی سیستم های نیرو به گاز: کاربرد در منطقه اوکسیتانیا ، فرانسه-2021
This work presents a methodological design framework for Hydrogen and Methane Supply Chains (HMSC). An innovative approach is to focus on Power-to-Hydrogen (PtH) and Power-to-Methane (PtM) concepts, and their interactions with other technologies, and energy carriers (i.e., Steam Methane Reforming – SMR, and natural gas). The overall objective of this work is to perform single objective and multi-objective optimizations for HMSC design to provide effective support for deployment scenarios. The methodological framework developed is based on a Mixed Integer Linear Programming (MILP) approach with augmented ε-constraint implemented in the GAMS environment according to a multi-period approach (2035-2050). Several available energy sources (wind, PV, hydro, national power grid, and natural gas) for hydrogen production through electrolysis and SMR are included. Carbon dioxide sources stem mainly from methanization and gasification processes, which are used to produce methane through methanation. The objective to be minimised in the single optimization approach is the total annual cost considering the externality of greenhouse gas emissions through the carbon price for the whole HMSC over the entire period studied. The multi-objective optimization includes as objectives the total annual cost, greenhouse gas emissions, and the total methane production from methanation. The Levelized Cost of Energy (LCOE), and the greenhouse gas emissions for each energy carrier are also computed. The results show that renewable hydrogen from PtG can be competitive with SMR through the implementation of carbon prices below 0.27 €/kgCO2. In the case of synthetic methane, the available resources can meet the demand through PtG, and even if synthetic methane for natural gas network injection is thus far from competitive with natural gas, power-to-gas technologies have the potential to decarbonize the fossil economy and achieve a circular economy through CO2 recovery.
KEYWORDS: Power-to-Gas | Methanation | Hydrogen | MILP | supply chain | optimization
مقاله انگلیسی
6 Resilience cloud-based global supply chain network design under uncertainty: Resource-based approach
انعطاف پذیری مبتنی بر ابر طراحی شبکه جهانی زنجیره تامین تحت عدم اطمینان: رویکرد مبتنی بر منابع-2021
This study presents a fuzzy multi-objective mathematical programming model to design an efficient and resil- ience global supply chain network structure based on the service-oriented approach. Service composition and transportation within globally scattered resources are considered under the cloud manufacturing paradigm. The proposed comprehensive model is adapted to a global electrical medical device manufacturing system. Key performance measures include robustness, agility, leanness, and flexibility as resiliency pillars are considered in designing the network under uncertainty. To efficiently deal with the computational tractability of this non- linear and multi-objective optimization problem, a new hybrid solution algorithm is developed that in- corporates fuzzy multi-criteria decision-making methods and augmented ε-constraint method. Obtained computational results of a real case study present that the proposed service-oriented global supply chain network design can respond to its global customers’ demands in a resilient as well as efficient manner.
Keywords: Resilience supply chain | Cloud manufacturing | Resource-based approach | Uncertainty | Multi-objective
مقاله انگلیسی
7 A set of efficient heuristics and meta-heuristics to solve a multi-objective pharmaceutical supply chain network
مجموعه ای از روشهای اکتشافی و کارآیی کارآمد برای حل یک شبکه زنجیره تامین دارویی چند هدفه-2021
In this paper, we propose a new multi-objective optimization approach for the pharmaceutical supply chain network (PSCN) design problem to minimize the total cost and the delivery time of pharmaceutical products to the hospital and pharmacy, while maximizing the reliability of the transportation system. A new mixed-integer non-linear programming model was developed for the production-allocation-distribution-inventory-ordering- routing problem. Three new heuristics (H-1), (H-2), and (H-3) have been proposed and to validate the model, two new meta-heuristic algorithms, namely, an Improved Social Engineering Optimization (ISEO) and Hybrid Firefly and Simulated Annealing Algorithm (HFFA-SA) have been developed. The proposed mathematical model has been evaluated through extensive simulation experiments by analyzing different criteria. The results show that the proposed model along with the solution method provides a reliable and powerful instrument to solve the PSCN design problem.
Keywords: Pharmaceutical supply chain network | Heuristic algorithms | Improved social engineering optimization | Hybrid firefly and simulated annealing | algorithm | Multi-objective optimization
مقاله انگلیسی
8 Unpacking the role of primary packaging material in designing green supply chains: An integrated approach
Unpacking the role of primary packaging material in designing green supply chains: An integrated approach-2021
Due to the adverse impact of packaging materials on several ecosystems, the circular and sustainable approaches to manage packaging waste have been receiving increasing attention worldwide. Plastic pails are widely used primary packaging materials that are cost-effective, lightweight, yet long-lasting. In the present study, we pro- pose a closed-loop supply chain (CLSC) network design model to jointly optimize the decisions related to the location of collection, sorting, and recycling centers, and the quantity of plastic pales to be recycled and/or freshly produced and distributed. The proposed model is augmented with an incentive mechanism to acquire used plastic pails from customers as well as a green supplier selection procedure. In addition to the traditional objective of profit maximization, the proposed model also minimizes carbon emission, maximizes the return of used plastic pails, and prioritize suppliers for the procurement of sustainable packaging raw materials. A set of non-dominated solutions to the proposed multi-objective model are obtained using the Augmented ε-constraint method (AUGMECON). The results of AUGMECON are also compared with other methods such as weighted sum method and Augmented Tchebycheff method. It is oberseved that AUGMECON produces diverse set of pareto- optimal solutions for the considered problem. The applicability of the model is explained using an illustrative example of an adhesive manufacturer in India. Further, several managerial insights are drawn by carrying out sensitivity analysis through scenario building.
Keywords: Primary packaging | Closed-loop supply chain network design | Incentives | Supplier selection | Multi-objective optimization | Augmented ε-constraint method
مقاله انگلیسی
9 A preference-based demand response mechanism for energy management in a microgrid
مکانیسم پاسخ تقاضا مبتنی بر اولویت برای مدیریت انرژی در یک ریز شبکه -2020
In this work, a preference-based, demand response (DR) multi-objective optimization model based on real-time electricity price is presented to solve the problem of optimal residential load management. The purpose of such a model is threefold: 1) to minimize the costs associated with consumption; 2) to minimize the inconvenience caused to consumers; and 3) to minimize environmental pollution. Potential solutions to the underlying multi-objective optimization problem are subject to a set of electrical and operational constraints related to home appliances categories and the utilization of distributed energy resources (DER) and energy storage systems (ESS). The use of the proposed model is illustrated in a realistic microgrid scenario where suitable solutions were found by the Non-Dominated Sorting Genetic Algorithm III (NSGA-III). These solutions determine new operational periods for home appliances as well as the utilization of DER and ESS for the planning horizon while considering consumer preferences. Besides helping consumers to take advantage of the benefits offered by DR, the experimental results show that the multi-objective DR model together with the NSGA-III algorithm can effectively minimize energy-consumption costs as well as reduce inconvenience costs and environmental pollution.
Keywords: Demand Response | Microgrid | Optimization | NSGA-III | Smart grid
مقاله انگلیسی
10 A bi-objective optimization approach for selection of passive energy alternatives in retrofit projects under cost uncertainty
یک روش بهینه سازی دو هدفه برای انتخاب گزینه های انرژی منفعل در پروژه های مقاوم سازی تحت عدم اطمینان هزینه-2020
Improving energy performance of buildings is of particular importance in new construction and existing buildings. Building refurbishment is considered a practical pathway towards energy efficiency as the replacement of older buildings is at a slow pace. There are various ways of incorporating energy conservation measures in buildings through refurbishment projects. As such, we have to choose among various passive or active measures. In this study, we develop an integrated assessment model to direct energy management decisions in retrofit projects. Our focus will be on alternative passive measures that can be included in refurbishment projects to reduce overall energy consumption in buildings. We identify the relative priority of these alternatives with respect to their non- monetary (qualitative) benefits and issues using an analytic network process. Then, the above priorities will form a utility function that will be optimized along with the energy demand and retrofit costs using a multi-objective optimization model. We also explore various approaches to formulate the uncertainties that may arise in cost estimations and incorporate them into the optimization model. The applicability and authenticity of the proposed model is demonstrated through an illustrative case study application. The results reveal that the choice of the optimization approach for a retrofit project shall be done with respect to the extent of variations (uncertainties) in expected utilities (benefits) and costs for the alternative passive technologies.
Keywords: Construction technologies | assive energy measures | Building retrofit | Multi-Objective Optimization | Cost uncertainty | Fuzzy set theory
مقاله انگلیسی
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