Designing an Appropriate Cultivation Pattern for an Arid RegionWith Application of Compromise Programming(Case study: Sistan region in Iran)
Publish Year: 1390
نوع سند: مقاله کنفرانسی
زبان: English
View: 1,556
This Paper With 12 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
NCAGM01_170
تاریخ نمایه سازی: 7 آذر 1391
Abstract:
In this paper, compromise programming used to solve a multiple-objective model for designing the bestCultivation Pattern. In this model, objectives are simultaneously achieved by minimizing the distance betweencurrent objective values and the ideal ones. The case study is Sistan region in Sistan and Balouchistan Provinceof Iran. There are serious water problems in this region. In used data and information for this study, relates to the years of 2004-2011, when the area was under drought. To satisfy future water demands for farming, compromise programming is applied to aid decision makers, which are local decision-maker (PWSC) and national DM (NWSC), to select the best possible cultivating scenario among others in the region. At first, nine alternativescenarios were chosen. Then, after solving the model, considering to importance of the water and among threegood scenarios (the scenarios number 4, number 5 and number 6), scenario number 6, which is compromisesolution from DMs‟ view, is the best one. This scenario consist all considered criteria in this paper. Therefore, itis recommended for Sistan region with 245000 ha arable land. This cultivating pattern is allocation of165289(ha) to cultivate rapeseed, 68965(ha) to melon and other crops in this group The obtained results revealthat the method is capable of being employed by decision-makers for farm management plan studies.
Keywords:
Authors
Sarah Rafiei Rad
MA educated of zabol university
Ahmad Ali Kehkha
Professor of zabol university
Parinaz Jansouz
MA educated of zabol university
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :