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نتیجه جستجو - Mathematical Programming

تعداد مقالات یافته شده: 9
ردیف عنوان نوع
1 An integrated data envelopment analysis-mathematical programming approach to strategic biodiesel supply chain network design problem
رویکرد برنامه ریزی تجزیه و تحلیل یکپارچه داده ها و ریاضی به مسئله طراحی شبکه شبکه زنجیره تامین استراتژیک-2017
Global warming, environmental issues, food crisis and energy security are the main concerning problems which have triggered a sense of urgency among policymakers and development practitioners to find sustainable and viable solutions in the area of bioenergy. Among various edible and non-edible bio energy feedstocks specified for biodiesel production, Jatropha curcas L. (JCL) and waste cooking oil (WCO) have been introduced to be promising and sustainable. In this study, an integrated hybrid approach based on a data envelopment analysis (DEA) and mathematical programming techniques is presented for the strategic design of biodiesel supply chain network in Iran. In the first phase, JCL cultivation areas are assessed according to climatic and social criteria by a unified DEA (UDEA) model. In the second phase, the locations which have achieved desired efficiency scores are considered as candidate locations for JCL cultivation within a mathematical programming model developed for designing the biodiesel supply chain network. The proposed mathematical programming model optimizes the numbers, locations and capacities of JCL cultivation centers, JCL seeds and WCO collection centers, bio-refineries, and distribution centers. The proposed approach is implemented in Iran for 10 years planning horizon. The results show the usefulness and efficiency of the proposed method in assisting the policymakers to take suitable strategic and tactical level decisions related to biodiesel supply chain planning.
Keywords: Jatropha curcas L | Biofuel supply chain optimization | Data envelopment analysis | Mathematical programming techniques | Sustainable | development
مقاله انگلیسی
2 A mathematical model for green supply chain coordination with substitutable products
یک مدل ریاضی برای هماهنگی زنجیره تامین سبز با محصولات جایگزین-2017
This paper investigates the green channel coordination issue within a two-stage supply chain (SC). The investigated SC sells a non-green traditional product and also plans for releasing a new substitutable green product beside the current traditional product. Demand for both products is a function of the retail price as well as products’ green quality and retailer’s sales efforts. Both retail price and sales effort level for the green product are decided by the retailer while the product green quality is the manufacturer’s decision variable. Three decision scenarios are modelled and compared: (1) decentralized scenario where each member decides independently based on own profit, (2) integrated scenario where there is a one decision maker in the system, and (3) collaborative scenario that aims to enhance the overall channel profit subject to Pareto improvement for each member. Closed-form expressions of optimal retail price, sales effort and green quality are derived for the first two scenarios, and a mathematical programming model is developed for the collaborative scenario. Our numerical investigations revealed that the pro posed collaboration model is capable of enhancing the SC profit fairly close to the centralized model and also ensures higher profits for both channel members than the decentralized decision making.
Keywords:Green supply chain coordination|Substitutable products|Consumer environmental awareness|Environmental quality|Sales efforts|Collaborative |decision making
مقاله انگلیسی
3 Design of biofuel supply chains with variable regional depot and biorefinery locations
طراحی زنجیره های تامین سوخت زیستی با مکان های مختلف منطقه ای و دفن زباله-2017
We propose a multi-period mixed-integer linear programming (MILP) model for the design and oper ational planning of cellulosic biofuel supply chains. Specifically, the proposed MILP model accounts for biomass selection and allocation, technology selection and capacity planning at regional depots and biorefineries. Importantly, it considers the location of regional depots and biorefineries as continuous optimization decisions. We introduce approximation and reformulation methods for the calculation of the shipments and transportation distance in order to obtain a linear model. We illustrate the applica bility of the proposed methods using two medium-scale examples with realistic data.
Keywords:Cellulosic ethanol|Biorefinery|Mathematical programming|Optimization|Reformulation
مقاله انگلیسی
4 Competition, cooperation, and coopetition of green supply chains under regulations on energy saving levels
رقابت، همکاری و همکاری زنجیره تامین سبز تحت مقررات مربوط به میزان صرفه جویی در انرژی-2017
We develop price-energy-saving competition and cooperation models for two green supply chains (GSCs) under government financial intervention. First, we study the best response strategies of the chains for the given tariffs of a government. Second, we formulate 16 mathematical programming models regarding governments’ energy-saving, social welfare, and revenue-seeking policies. We find that the government can orchestrate GSCs to fulfil the financial, social, and environmental objectives by an appropriate tariff mechanism. Moreover, cooperation in a GSC and between GSCs may facilitate the government’s sustain able development policies. A comprehensive analysis on case study of brick production GSCs reveals some important managerial insights.
Keywords:Energy saving efforts|Governmental regulation|Game theory|Green supply chain|Sustainable development policy
مقاله انگلیسی
5 Closed-loop supply chain configuration for new and reconditioned products: An integrated optimization model
پیکربندی زنجیره تامین حلقه بسته برای محصولات جدید و تعویض شده: یک مدل بهینه سازی یکپارچه-2017
Closed-Loop Supply Chain Management (CLSCM) is considered as a strategic response to the call for cor porate sustainability while further expanding the scope of value creation to include product reconstruction. The Closed-Loop Supply Chain (CLSC) performance is directly related to the CLSC network design. The CLSC network design, with long-term and strategic connotations, involves selection of an integrated network of partner organizations to be engaged on one hand in the forward supply chain processes relevant to families of existing and new products and also involved in reverse supply chain activities relevant to reconstruction of the returned products. At the tactical level, Closed-Loop Supply Chain Configuration (CLSCC) attempts to address issues pertinent to launch of a new product and its reconstruction. The CLSC network design is well studied in the current literature, but addressing the CLSCC is neglected. To study the CLSCC problem we: (a) develop an integrated optimization model for problem; (b) present a real-world case study of a battery manufacturer; (c) based on the case study, we conduct a comprehensive set of computational experiments followed by a series of what-if analyses to compare profitability of the Forward Supply Chain Configuration (FSCC) versus the CLSCC; and (c) discuss the key observations and managerial implications drawn from the computational experiments, applicable to other real-world instances. The significant outcomes of the study suggest that: (i) performance of the firms base case integrated CLSCC model is significantly better than the current supply chain model (ii) the sales-price ratio of new battery is found to be negatively related with the maximum acquiring price of used batteries; (iii) combination of sales price ratios of new and reconditioned batteries determines the total net profit for a given return rate. Finally, important managerial insights and scope for future research are discussed.
Keywords: Operations management | Marketing | Case study | Product life cycle | Production planning and control |Mathematical programming
مقاله انگلیسی
6 طراحی و بهره برداری از شبکه حمل و نقل چند وجهی در منطقه مرمره ترکیه
سال انتشار: 2015 - تعداد صفحات فایل pdf انگلیسی: 18 - تعداد صفحات فایل doc فارسی: 35
این مقاله یک مدل بهینه سازی چند هدفه را برای ادغام حالات متفاوت حمل و نقل در طراحی و بهره برداری از یک شبکه حمل و نقل چند وجهی در یک منطقه جغرافیایی ارائه می‌دهد. مسئله به عنوان یک مسئله بهینه سازی آمیخته با اعداد صحیح فرمول شده است که سرعت وسیله نقلیه را بسته به زمان و ازدحام در نظر می‌گیرد. رویکرد مدل سازی، تحلیل داده و شمایی از مشخصه‌های مهم مسئله برنامه نویسی ریاضی را برای حداقل سازی زمان و هزینه حمل و نقل به صورت همزمان با استفاده از محدودیت-ε را ارائه می‌دهیم. رویکرد پیشنهادی در یک مورد جهان واقعی با استفاده از اطلاعاتی از منطقه مرمره که تقریبا 50% سرویس‌ها و کالاهای صنعتی آن در ترکیه تولید شده است، تشریح می‌شود.
کلمات کلیدی : حمل و نقل چند وجهی | بهینه سازی آمیخته با اعداد صحیح | بهینه سازی دو هدفه
مقاله ترجمه شده
7 Pathway-level disease data mining through hyper-box principles
داده کاوی بیماری های سطح-مسیر از طریق اصول فراجعبه-2015
In microarray data analysis, traditional methods that focus on single genes are increasingly replaced by methods that analyse functional units corresponding to biochemical pathways, as these are considered to offer more insight into gene expression and disease associations. However, the development of robust pipelines to relate genotypic functional modules to disease phenotypes through known molecular interactions is still at its early stages. In this article we first discuss methodologies that employ groups of genes in disease classification tasks that aim to link gene expression patterns with disease outcome. Then we present a pathway-based approach for disease classification through a mathematical programming model based on hyper-box principles. Association rules derived from the model are extracted and discussed with respect to pathway-specific molecular patterns related to the disease. Overall, we argue that the use of gene sets corresponding to disease-relevant pathways is a promising route to uncover expression-to-phenotype relations in disease classification and we illustrate the potential of hyper-box classification in assessing the predictive power of functional pathways and uncover the effect of specific genes in the prediction of disease phenotypes.
Keywords: Disease classification | Pathway-based classification | Mathematical programming | Hyper-box-representation | Mixed integer optimisation
مقاله انگلیسی
8 Managing solar uncertainty in microgrid systems with stochastic unit commitment
مدیریت عدم قطعیت خورشیدی در سیستم های شبکه میکرو با تعهد واحد تصادفی-2015
As renewable energy becomes more prevalent in transmission and distribution systems, it is vital to understand the uncertainty and variability that accompany these resources. Microgrids have the poten tial to mitigate the effects of resource uncertainty. With the ability to exist in either an islanded mode or maintain connections with the main-grid, a microgrid can increase reliability, defer T&D infrastructure and effectively utilize demand response. This study presents a co-optimization framework for a micro grid with solar photovoltaic generation, emergency generation, and transmission switching. Today, unit commitment (UC) models ensure reliability with deterministic criteria, which are either insufficient to ensure reliability or can degrade economic efficiency for a microgrid that has a large penetration of vari able renewable resources. A stochastic mixed integer program for day-ahead UC is proposed to account for uncertainty inherent in PV generation. The model incorporates the ability to trade energy and ancillary services with the main-grid, including the designation of firm and non-firm imports, which captures the ability to allow for reserve sharing between the two systems. In order to manage the computational com plexities, Benders’ decomposition is applied. The commitment schedule is validated with solar scenario analysis, i.e., Monte-Carlo simulations are conducted to test the proposed dispatch solution. Keywords: Stochastic programming Solar energy Power system reliability Power generation economics Day-ahead scheduling Mathematical programming
مقاله انگلیسی
9 استفاده از الگوریتم ژنتیک برای حداکثرسازی بهره وری فنی در تحلیل پوششی داده ها
سال انتشار: 2015 - تعداد صفحات فایل pdf انگلیسی: 10 - تعداد صفحات فایل doc فارسی: 20
تحلیل پوششی داده ها (DEA) یک روش غیر پارامتری برای تخمین بهره وری فنی مجموعه ای از واحدهای تصمیم گیرنده (DMUها) از یک پایگاه داده شامل ورودی ها و خروجی ها است. این مقاله مدل های DEA مبتنی بر حداکثرسازی راندمان فنی را مطالعه می کند، که هدف تعیین کردن مسافت حداقلی از DMU ارزیابی شده برای مرز تولید است. معمولا، این مدل ها از طریق روش های نامطلوب مورد استفاده برای مسائل NP-hard ترکیبی حل می شوند. در اینجا مسئله توسط روش های فراابتکاری بررسی می شود و راه حل ها با روش هایی از متدولوژی مبتنی بر تعیین تمامی جنبه های مرزی در DEA مقایسه می شود. استفاده از فراابتکاری ها راه حل های نزدیک به بهینه گی با زمان اجرای پائین را ارائه می-کنند.
کلمات کلیدی: تحلیل پوششی داده ها | نزدیک ترین اهداف | برنامه نویسی ریاضیاتی | متدولوژی های بهره وری | الگوریتم های ژنتیک
مقاله ترجمه شده
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