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نتیجه جستجو - GAMS

تعداد مقالات یافته شده: 16
ردیف عنوان نوع
1 یک مدل ریاضی چند منظوره برای زنجیره تامین داروسازی با توجه به تراکم دارو در کارخانه‌ها
سال انتشار: 2022 - تعداد صفحات فایل pdf انگلیسی: 15 - تعداد صفحات فایل doc فارسی: 47
مدیریت زنجیره تامین ( SCM ) , به روش یکی از مسائل مهم در جنبه مدیریتی , نقش مهمی در مقابله با مسایل انسانی و مشکلات ایفا می‌کند . به دلیل برخی محدودیت‌ها ( به عنوان مثال , ظرفیت تولید و ظرفیت ذخیره‌سازی ) و خواسته ها( به عنوان مثال , کاهش هزینه و افزایش درآمد ) , مدیران زنجیره تامین همیشه به دنبال بهترین پاسخ به مقدار و نوع ارتباط بین سطوح مختلف SCM هستند . در تحقیقات آتی , یک زنجیره تامین دارو ( PSC ) با سه تابع هدف توسعه‌یافته , با هدف به حداقل رساندن هزینه‌های کلی , خواسته‌های برآورده نشده , و کاهش زمان انتظار در ورودی کارخانه . در تحقیقات آتی , موضوع کلی و تحقیقات در مدل‌سازی PSC و حل مساله مورد بحث قرار گرفته‌اند . سپس یک مدل برنامه‌ریزی غیرخطی با تحقیقات قبلی برای حل کاستی‌های موجود پیشنهاد شده‌است.
همچنین روش‌های تصمیم‌گیری چند هدفه برای انطباق با اهداف متناقض مدل به طور همزمان استفاده می‌شوند . سپس نرم‌افزار تجاری GAMS برای حل مشکل اندازه‌های مختلف به کار می‌رود . در نهایت ، تحلیل حساسیت گسترده و ارزیابی نتایج مورد بحث قرار می‌گیرد و پیشنهادهای توسعه آتی ارایه می‌شوند.
واژه های کاربردی : زنجیره تامین دارو | فسادپذیری | زمان‌بندی | فهرست | نظریه کیوینگ
مقاله ترجمه شده
2 Bi-objective optimal design of hydrogen and methane supply chains based on Power-to-Gas systems
طراحی بهینه دو هدفه زنجیره های تأمین هیدروژن و متان بر اساس سیستم های نیرو به گاز-2021
This paper presents a methodological design framework for Hydrogen and Methane Supply Chains (HMSC) based on Power-to-Gas (PtG) systems. The novelty of the work is twofold, first considering a specific demand for hydrogen for electromobility in addition to the hydrogen demand required as a feedstock to produce synthetic methane from the methanation process. and performing a bi-objective optimization of the HMSC to provide effective support for the study of deployment scenarios. The approach is based on a Mixed Integer Linear Programming (MILP) approach with augmented epsilon-constraint implemented in the GAMS environment according to a multi-period approach (2035-2050) with several available energy sources (wind, PV, hydro, national network) for hydrogen production. Carbon dioxide sources stem mainly from mechanization and gasification processes. The objectives to be minimized simultaneously are the Total Annual Cost and the greenhouse gas emissions related to the whole HMSC over the entire period studied.
KEYWORDS: Power-to-Gas | Methanation | Hydrogen | MILP | Augmented epsilon constraint | GAMS | optimization approach
مقاله انگلیسی
3 Data Driven Robust Optimization for Handling Uncertainty in Supply Chain Planning Models
بهینه سازی قوی مبتنی بر داده ها برای مدیریت عدم قطعیت در مدل های برنامه ریزی زنجیره تامین-2021
While addressing supply chain planning under uncertainty, Robust Optimization (RO) is regarded as an efficient and tractable method. As RO involves calculation of several statistical moments or maximum / minimum values involving the objective functions under realizations of these uncertain parameters, the accuracy of this method significantly depends on the efficient techniques to sample the uncertainty parameter space with limited amount of data. Conventional sampling techniques, e.g. box/budget/ellipsoidal, work by sampling the uncertain parameter space inefficiently, often leading to inaccuracies in such estimations. This paper proposes a methodology to amalgamate machine learning and data analytics with RO, thereby making it data-driven. A novel neuro fuzzy clustering mechanism is implemented to cluster the uncertain space such that the exact regions of uncertainty are optimally identified. Subsequently, local density based boundary point detection and Delaunay triangulation based boundary construction enable intelligent Sobol based sampling to sample the uncertain parameter space more accurately. The proposed technique is utilized to explore the merits of RO towards addressing the uncertainty issues of product demand, machine uptime and production cost associated with a multiproduct, and multisite supply chain planning model. The uncertainty in supply chain model is thoroughly analysed by carefully constructing examples and its case studies leading to large scale mixed integer linear and nonlinear programming problems which were efficiently solved in GAMS framework. Demonstration of efficacy of the proposed method over the box, budget and ellipsoidal sampling method through comprehensive analysis adds to other highlights of the current work.
Keywords: Uncertainty Modelling | Supply chain Management | Data driven Robust Optimization | Neuro Fuzzy Clustering | Multi-Layered Perceptron
مقاله انگلیسی
4 A Multi-Objective Green Hub Location Problem with Multi Item-Multi Temperature Joint Distribution for Perishable Products in Cold Supply Chain
یک مشکل مکان یابی Green Hub چند هدفه با توزیع مشترک چند ماده ای - چند دما برای محصولات فاسدشدنی در زنجیره تامین سرد-2021
This paper investigates a bi-objective green hub location problem, in which multiple perishable products with various storage temperatures can be distributed simultaneously in a cold supply chain (CSC). The objectives of this problem include minimizing the system’s total cost (including transportation, hub establishment, adjustment of the storage compartments’ temperatures, and carbon emission costs) and maximizing the quality of the delivered product to the customer via the proposed model. Mixed-integer linear programming (MILP) in the GAMS software was employed to formulate this problem. Then, the ε-Constraint method was adopted to solve the presented bi-objective model to obtain the Pareto frontier and consequently, a numerical example based on the CAB (Civil Aeronautics Board) database is presented to validate the applicability of the model. The solutions of the model provide information regarding the hub location (HL), allocating customers to the hubs, allocating customers to the vehicles, and the sequence of vehicles’ services for the Multi Item-Multi Temperature Joint Distribution of perishable products in CSCs. Moreover, the final results revealed the existence of a contradictory exchange between the two objectives of this paper, implying that the higher is the quality of the delivered perishable product to the customer, the greater is the system’s total cost. The novelty of the proposed model compared to other hub location problems (HLPs) lies in the integration of the tactical/operational decisions with strategic decisions to provide logistic solutions in CSCs by considering the carbon emissions as an environmental factor in the transportation systems for the simultaneous distribution of dissimilar storage temperatures perishable products within a CSC. The proposed model in this research can help the distributers of perishable products by maintaining the quality of the delivered items and reducing the system’s total costs and considering the carbon emissions of transportation systems. This study has practical implications for the logistics and CSCs managers to not only establish a distribution network for multiple perishable products on the basis of the findings, but also respond to the environmental sustainability.
Keywords: Hub Location | Perishable Products | Cold Supply Chain | Transportation | Multi-objective
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 A multi-functional tri-objective mathematical model for the pharmaceutical supply chain considering congestion of drugs in factories
یک مدل ریاضی سه هدفه چند منظوره برای زنجیره تأمین دارویی با توجه به ازدحام داروها در کارخانه ها-2021
Supply Chain Management (SCM), by way of one of the critical issues in the managerial aspect, plays a significant role in tackling humanitarian problems and difficulties. Due to some limitations (e.g., production capacity and storage capacity) and desires (e.g., cost reduction and rising revenues), supply chain managers always seek the best response to the amount and type of communication between different SCM levels. In the upcoming research, a Pharmaceutical Supply Chain (PSC) with three objective functions is developed, aiming to simultaneously minimize total costs, unfulfilled demands, and reduce the waiting time at the factory entrance. In the forth- coming research, the subject literature and research in the PSC modeling and problem-solving are discussed. A nonlinear programming model is then proposed in line with the previous research to solve the existing short- comings. Also, multi-objective decision-making methods are used to match the conflicting objectives of the model simultaneously. Then, GAMS commercial software is used to solve the problem of different sizes. Finally, the wide sensitivity analysis and evaluation of the results are discussed, and future development suggestions are presented.
Keywords: Pharmaceutical supply chain | Perishability | Scheduling | Inventory | Queuing theory
مقاله انگلیسی
7 Risk-averse supplier selection and order allocation in the centralized supply chains under disruption risks
انتخاب تامین کننده متنفر از ریسک و تخصیص سفارش در زنجیره های تأمین متمرکز تحت خطرات اخلال-2021
This paper proposes a mixed-integer non-linear programming (MINLP) model for the integrated supplier selec- tion and order allocation in a centralized supply chain considering the disruption risks and a risk-averse decision- maker. In order to capture a realistic scenario of considering the geographical characteristics of the suppliers, we assume that the suppliers belong to two regions: the buyer’s region (domestic suppliers) and outside of the buyer’s region (foreign suppliers). Considering this realistic feature, the supply chain might face two types of disruption risk: first, local disruption risks which might uniquely occur inside each supplier such as equipment breakdowns, and second, regional disruption risks that might occur in the region of the suppliers located in the same geographical region such as natural hazards. We formulate the problem considering a risk-neutral decision- maker as a benchmark, and then a risk-averse model is presented. In the latter case, we apply two types of risk assessment tools introduced in the finance literature to analyze the decision maker’s behavior: value-at-risk (VaR) and conditional value-at-risk (CVaR). We show that developed models are non-convex programming, and therefore, we apply the particle swarm optimization (PSO) algorithm as the solution approach. We also compare the developed PSO algorithm with the Genetic algorithm (GA) and the commercial GAMS solver to verify the efficiency of the solution method. The computational experiments indicate the impact of the decision maker’s attitude on the supplier selection and the order quantity.
Keywords: Supplier selection | Disruption risks | Order allocation | Conditional value-at-risk | Meta-heuristic algorithms
مقاله انگلیسی
8 An IGDT-based risk-involved optimal bidding strategy for hydrogen storagebased intelligent parking lot of electric vehicles
یک استراتژی مناقصه بهینه مبتنی بر خطر IGDT برای ذخیره سازی هیدروژن مبتنی بر پارکینگ هوشمند وسایل نقلیه برقی-2020
In a near future, electric vehicles (EVs) will constitute considerable part of transportation systems due to their important aspects such as being environment friendly. To manage high number of EVs, developing hydrogen storage-based intelligent parking lots (IPLs) can help power system operators to overcome caused problems by high penetration of EVs. In this work, a new method is applied to get optimal management of IPLs in an uncertain environment and provide optimal bidding curves to take part in power market. The main purpose of this work is to get optimal bidding curves with considering power price uncertainty and optimal operation of IPLs. To model uncertainty of power price in the power market and develop optimal bidding curve, the opportunity, deterministic and robustness functions of the information gap decision theory (IGDT) technique has been developed. Obtained results has been presented in three strategies namely risk-taker, risk-neutral, and risk-averse corresponding to opportunity, deterministic, and robustness functions of the IGDT technique. In order to demonstrate the effects of demand response program (DRP), each strategy is optimized with and without DRP cases. The mixed-integer non-linear programming model is used to formulate the proposed problem which is solved using the GAMS optimization software under DICOPT solver.
Keywords: Social welfare of owners of electric vehicles | Intelligent parking lot | Optimal bidding curve | Power price policy | IGDT technique | Energy management and business
مقاله انگلیسی
9 Optimal energy management in the smart microgrid considering the electrical energy storage system and the demand-side energy efficiency program
مدیریت بهینه انرژی در میکروگرید هوشمند با توجه به سیستم ذخیره انرژی الکتریکی و برنامه بهره وری انرژی طرف تقاضا-2020
Smart MicroGrids (MGs) are known as a powerful platform for exploiting the Electrical Energy Storage Systems (EESSs). On the other hand, the Energy Efficiency Programs (EEPs) are recognized as an integral and highly valuable element of smart MGs investments and operations. While the EEPs are known to be long-term programs, they affect the short-term programs such as day ahead energy management. In this paper, the optimal energy management program model associated with EESSs and EEPs namely EMPEESSs EEPs has been proposed. The problem takes the investment rate on the EEPs into account while solving optimal energy management problem. To do this, the EEPs have been applied to the demand model. Furthermore, the proposed demand model has been used in the optimal energy management of the smart microgrids. The proposed objective function has been modeled as Mixed Integer Non-Linear Programming (MINLP) for the optimal energy management. Moreover, the GAMS software is used to solve the formulated optimization problem. The results of different scenarios confirm that the EEPs and EESSs are effective programs for the smart MGs energy management. The results are analyzed, and the best cost optimal solution is identified.
Keywords: Energy Efficiency Programs (EEPs) | Electrical demand | Thermal demand | Distributed Generation (DG) | Energy storage | Energy management
مقاله انگلیسی
10 An IGDT-based risk-involved optimal bidding strategy for hydrogen storage-based intelligent parking lot of electric vehicles
یک استراتژی پیشنهاد بهینه مبتنی بر ریسک IGDT برای پارکینگ هوشمند وسایل نقلیه الکتریکی مبتنی بر ذخیره هیدروژن-2020
In a near future, electric vehicles (EVs) will constitute considerable part of transportation systems due to their important aspects such as being environment friendly. To manage high number of EVs, developing hydrogen storage-based intelligent parking lots (IPLs) can help power system operators to overcome caused problems by high penetration of EVs. In this work, a new method is applied to get optimal management of IPLs in an un- certain environment and provide optimal bidding curves to take part in power market. The main purpose of this work is to get optimal bidding curves with considering power price uncertainty and optimal operation of IPLs. To model uncertainty of power price in the power market and develop optimal bidding curve, the opportunity, deterministic and robustness functions of the information gap decision theory (IGDT) technique has been developed. Obtained results has been presented in three strategies namely risk-taker, risk-neutral, and risk-averse corresponding to opportunity, deterministic, and robustness functions of the IGDT technique. In order to demonstrate the effects of demand response program (DRP), each strategy is optimized with and without DRP cases. The mixed-integer non-linear programming model is used to formulate the proposed problem which is solved using the GAMS optimization software under DICOPT solver.
Keywords: Social welfare of owners of electric vehicles | Intelligent parking lot | Optimal bidding curve | Power price policy | IGDT technique | Energy management and business
مقاله انگلیسی
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