Land Suitability Analysis for Solar Farms Exploitation Using GIS and Fuzzy Analytic Hierarchy Process (FAHP)—A Case Study of Iran

Considering the geographical location and climatic conditions of Iran, solar energy can provide a considerable portion of the energy demand for the country. This study develops a two-step framework. In the first step, the map of unsuitable regions is extracted based on the defined constraints. In the next step, in order to identify the suitability of different regions, 11 defined criteria, including solar radiation, average annual temperatures, distance from power transmission lines, distance from major roads, distance from residential area, elevation, slope, land use, average annual cloudy days, average annual humidity and average annual dusty days, are identified. The relative weights of defined criteria and sub-criteria are also determined applying fuzzy analytical hierarchy process (FAHP) technique. Next, by overlaying these criteria layers, the final map of prioritization of different regions of Iran for exploiting solar photovoltaic (PV) plants is developed. Based on Iran’s political divisions, investigation and analysis of the results have been presented for a total of 1057 districts of the country, where each district stands in one of the five defined classes of excellent, good, fair, low, and poor level. The obtained data indicate that 14.7% (237,920 km2), 17.2% (278,270 km2), 19.2% (311,767 km2), 11.3% (183,057 km2), 1.8% (30,549 km2) and 35.8% (580,264 km2) of Iran’s area are positioned as excellent, good, fair, low, poor and unsuitable areas, respectively. Moreover, Kerman, Yazd, Fars, Sisitan and Baluchestan, Southern Khorasan and Isfahan are included in the regions as the most excellent suitable provinces for exploiting solar PV plants

Strategic design of competing supply chain networks with foresight

We consider models for duopolistic competitive supply chain network designing with sequential acting and variable delivered prices. These models design a multi-tier chain operating in markets under deterministic price-depended demands and with a rival chain present. The existing rival chain tends to open some new retailers to recapture some income in a near future. These rival chains’ structures are assumed to be set ‘‘once and for all’’ in a sequential manner but further price adjustments are possible. This problem is modeled for each of the following two strategies: (1) the von Stackelberg strategy in which we assume the existing chain will choose its future entry sites in the way to optimize its market share. This problem is modeled by a linear binary bi-level program and solved by a combinatorial meta-heuristic. (2) the minimum regret strategy in which we assume the existing chain’s future entry sites are totally unpredic, it is playing a ‘‘game against nature’’. This problem is modeled by linear binary programs