مقاله انگلیسی رایگان در مورد مدیریت ریسک برای برنامه ریزی جنگلداری – الزویر ۲۰۱۸

elsevier

 

مشخصات مقاله
انتشار مقاله سال ۲۰۱۸
تعداد صفحات مقاله انگلیسی ۲۴ صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
منتشر شده در نشریه الزویر
نوع نگارش مقاله مقاله پژوهشی (Research article)
نوع مقاله ISI
عنوان انگلیسی مقاله Risk management for forestry planning under uncertainty in demand and prices
ترجمه عنوان مقاله مدیریت ریسک برای برنامه ریزی جنگلداری تحت عدم قطعیت در تقاضا و قیمت
فرمت مقاله انگلیسی  PDF
رشته های مرتبط منابع طبیعی
گرایش های مرتبط جنگلداری
مجله مجله اروپایی تحقیقات عملیاتی – European Journal of Operational Research
دانشگاه Estadística e Investigación Operativa – Universidad Rey Juan Carlos – Spain
کلمات کلیدی OR در منابع طبیعی، برنامه ریزی جنگلداری، بهینه سازی تحت عدم اطمینان، مدیریت ریسک، ثبات در اقدامات خطرناک
کلمات کلیدی انگلیسی OR in natural resources, Forestry planning, Optimization under uncertainty, Risk management, Consistency in risk-averse measures
شناسه دیجیتال – doi
https://doi.org/10.1016/j.ejor.2017.12.022
کد محصول E8573
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بخشی از متن مقاله:
۱٫ Introduction

Forest companies must plan the sustainable harvest of their resources over a given time horizon. Cut timber is then sold in specific local and international markets. They have to meet demand, primarily from pulp plants and sawmills. The main aim of the companies is to maximize profit while complying with environmental regulations. In previous studies we formulated and solved a specific problem addressing various issues that arise in forestry planning, namely, planning the harvest of forest land designated for timber production and the construction of access roads needed to transport the timber. Good surveys of forest-based supply chain planning cover such aspects as planting, cutting, construction of access roads for transportation. See Bredstrom, Lundgren, Rönnqvist, Carlsson, and Mason (2004), Marques, Borges, Sousa, and Pinho (2011), Pinho, Moreira, Veiga, and Boaventura-Cunha (2015), and Rönnqvist (2003), among others. Starting in the 70s, environmental and wildlife issues were increasingly considered in forest management models at different planning levels. In the last 30 years the twin problems of planning harvesting and access road construction have been addressed jointly using mathematical optimization models and computational tools. The advantage of integrating the two processes in a single mixed 0– ۱ model was demonstrated in Jones, Hyde, and Meachan (1986), whose solutions are from 15 to 45% better than with models that optimized the processes separately. There exist relevant studies on the different phases of forestry planning, especially regarding access road construction and harvesting. The problem we deal with may be formulated in terms of a partition of the forest into harvesting units, called stands. For a chosen time horizon one must determine which stands will be cut in each period, which roads need to be constructed to access those stands and when, and what quantity of wood will be transported from one point to another. These decisions are made in Andalaft et al. (2003) and references therein, among others. Our approach did benefit from these earlier reports. Some ion to an optimization criterion, typically profit maximization. A model for solving the harvesting problem considering road building and adjacency is provided in Candia (2010), which constrains the possibility of harvesting adjacent stands for observing the maximum clearfell areas regulations. Selling prices of forest products are a key element in forestry planning. Price fluctuations have a direct impact on profits from sales and figure prominently in the planners’ decision-making. The role played by randomness in forestry planning is closely related to the length of the chosen time horizon. Planners who must make tactical decisions are therefore concerned about price variations during a time horizon of two to five years. Although the most relevant source of uncertainty is prices, uncertainty in tree growth, timber demand and losses due to fires is also significant. The approach developed in this paper analyzes decision-making under uncertainty in wood selling prices and demand. We assume that they can be modeled over time by means of a set of scenarios with different associated probabilities.

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