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After the Green Building Regulations in the Zhejiang Province was put into effect in May 2016, cities and prefectures in the province were given directives to set their own individual targets for the provision of green buildings. The city of Ningbo decided to use this opportunity to develop a systematic procedure, using Fuzzy Analytical Hierarchy Process (FAHP), to identify which allotments within the municipal area have the greatest potential of delivering green buildings, ensuring the set targets are fair and deliverable. This paper explains in detail the use of FAHP in the production of the Specific Plans for Green Buildings for the city of Ningbo in the Zhejiang Province of China. This innovative multi-faceted method incorporates the level of development in each of the 3213 land allotments in the municipal area, assessing each one for critical aspects such as environmental potential, local economic development land-use and land prices in order to determine an individual roadmap for the ratio of green buildings to be built in each region within the city. This method incorporates a scientific process, in which Pairwise Comparison Analysis was conducted for the selected criteria and aspects to determine the weighting factors and scores in each case. This allowed planners to rank all allotments in the municipal area in terms of their potential to provide green buildings, and thus make the setting of targets to provide these accordingly. This approach breaks away from the traditional method which relies on simple estimation, which is often unjustified. Over the two years since this method was introduced, the effects had been positive, within all the allotments abiding to the set targets. Other cities and regions in China, such as the provinces of Liaoning and Hebei, have also adopted this process. The Specific Plans for Green Buildings in Ningbo also include the adoption rate of prefabricated buildings and the mandatory date for when by which new residential buildings should be fully-furnished before they are sold (this is not currently the case in most residential buildings in China). These aspects are also discussed in this paper. (C) 2020 Elsevier B.V. All rights reserved.

In this article, two different multiobjective fuzzy portfolio selectionmodels are presented. The significant criteria considered for portfolio selection are risk (variance or conditional value at risk), return, liquidity, and entropy. Here, the return of the portfolio is considered to be satisfied by a minimum return threshold constraint. Also, to introduce some degree of diversification in the model, a lower and upper bound constraint on investment in an asset is used along with the capital budget and no short selling constraints. Trapezoidal fuzzy returns are considered to incorporate the inherent uncertainty of the stockmarket, which is handled by using the credibility theory. The weighted sum approach is used to aggregate the objectives and characterize different investor attitudes. Random sample portfolios with progressively increasing sample sizes are generated that obey the constraints of the portfolio models. These random sample portfolios with multiple inputs (risk and entropy) and multiple outputs (return and liquidity) are evaluated in terms of their performance by using data envelopment analysis. Furthermore, a frontier improvement technique existing in the literature is used to rebalance the inefficient random sample portfolios to make them efficient, so that an investor may have more avenues to select efficient portfolios. A detailed numerical illustration with a simulation study using different sample sizes is presented to substantiate the proposed study.