Samsun İlinde Kurulabilecek Kompost Tesislerinin COCOSO ve WASPAS Yöntemiyle Optimallik Sıralaması

The compost product, which offers many benefits such as the evaluation of organic wastes, improvement of soil structure, neutralization of toxins and pH balance of the soil, has significant potential for the improvement of our country's lands. Considering the development of animal existence in our country, the production of compost product to be obtained from feces, which is the product of these animal beings, is an issue that needs to be emphasized. The choice of plant location, which must be determined for an investment to be made for the acquisition of this product emerges as a separate problem. For this reason, in this study, the order of optimality among the alternatives for compost plant installation is considered as a multi-criteria decision making problem. For this purpose, the criteria determined for 10 clusters with the potential of 35,829 animals that can produce compost in Samsun were weighted by the SWARA method. The optimal ranking of these 10 compost clusters was carried out using the COCOSO and WASPAS methods, by means of the criteria weights taken into consideration. According to the ranking results obtained from both methods, it was determined that the cluster number 27 was in the first rank, the cluster no 13 was in the second rank, and the cluster no 14 was in the third rank.

Web Page Recommender System using hybrid of Genetic Algorithm and Trust for Personalized Web Search

The main challenge to effective information retrieval is to optimize the page ranking in order to retrieve relevant documents for user queries. In this article, a method is proposed which uses hybrid of genetic algorithms (GA) and trust for generating the optimal ranking of trusted clicked URLs for web page recommendations. The trusted web pages are selected based on clustered query sessions for GA based optimal ranking in order to retrieve more relevant documents up in ranking and improves the precision of search results. Thus, the optimal ranking of trusted clicked URLs recommends relevant documents to web users for their search goal and satisfy the information need of the user effectively. The experiment was conducted on a data set captured in three domains, academics, entertainment and sports, to evaluate the performance of GA based optimal ranking (with/without trust) and search results confirms the improvement of precision of search results.

Dynamic supplier selection through optimal ranking under two-echelon system

Purpose With the increasing competition among the industries, they remain under pressure as how to select the best set of suppliers for the competitive edge. Often, it has been challenging to develop an effective set of suppliers due to varied and asymmetric mode of criteria. The purpose of this paper is to develop a responsive chain under original equipment manufacturer (OEM). Design/methodology/approach This study proposes a responsive chain under a two-echelon system (TES) of OEM, which needs to collaborate with a set of suppliers at each echelon through an integrated methodology of AHP and TOPSIS. According to the OEM’s criteria, demands and suppliers’ capacity vary with time, therefore they are not static for a longer period. Hence, supplier selection (SS) problem possesses dynamicity in real practice. For this, MILP is used for finding optimal order quantities based on the optimal ranking at each echelon in the multi-period scenario. Subsequently, sensitivity analysis (SA) is conducted through Taguchi method of parameter design (TMPD) to achieve an optimal ranking in the TES. Findings This study suggests optimal criteria’s weight, percentage contribution, and flexibility for the suppliers and manufacturers involving through maximum demand strategy at each echelon of OEM. It also provides robust group of suppliers and manufacturers in the TES through optimal ranking and simultaneously in the order allocations. Furthermore, it restricts the number of suppliers and manufactures at each echelon through proposed methodology to obtain the solution in a very short running time. Originality/value To validate this model, a real data set for the case of chain conveyor company is used. This adopted methodology can suggest the organization that how the approach should be implemented.

Low-Distortion Social Welfare Functions

Work on implicit utilitarian voting advocates the design of preference aggregation methods that maximize utilitarian social welfare with respect to latent utility functions, based only on observed rankings of the alternatives. This approach has been successfully deployed in order to help people choose a single alternative or a subset of alternatives, but it has previously been unclear how to apply the same approach to the design of social welfare functions, where the desired output is a ranking. We propose to address this problem by assuming that voters’ utilities for rankings are induced by unknown weights and unknown utility functions, which, moreover, have a combinatorial (subadditive) structure. Despite the extreme lack of information about voters’ preferences, we show that it is possible to choose rankings such that the worst-case gap between their social welfare and that of the optimal ranking, called distortion, is no larger (up to polylogarithmic factors) than the distortion associated with much simpler problems. Through experiments, we identify practical methods that achieve nearoptimal social welfare on average.

Optimal Ranking Regime Analysis of U.S. Summer Temperature and Degree-Days: 1895–2015

The optimal ranking regime (ORR) method was applied to mean summer maximum (TMXS) and mean summer minimum (TMNS) temperature and to cumulative summer cooling degree-days (CDDS) calculated from U.S. climate-division data during 1895–2015. CDDS is proposed as a proxy for growing degree-days for summer corn given their high rank correlation in station data during 1950–2014. The TMXS and CDDS ORR analyses show similar climate-regime patterns. Western and northeastern divisions experienced multidecadal cool periods before 1930 and warm periods after 1990. The 1930s drought appears as decadal warm regimes over the Midwest and Great Plains. Multidecadal TMXS and CDDS temperature cycles are evident over the Southeast, but TMXS and CDDS variation over the Midwest’s Corn Belt agricultural region has been regime free since the early 1940s. By contrast, TMNS regimes consistent with centennial-scale warming trends are found over most divisions outside the Southeast. From the multidecadal regime patterns detected by the ORR analyses, the TMXS, TMNS, and CDDS series of each climate division were tested for significant linear trends during 1910–2015 and 1970–2015. Significant positive TMNS trends during 1910–2015 are found in 48 of the 102 divisions, with some western trend magnitudes being greater than 15% of the twentieth-century climatological mean. During 1970–2015, positive TMXS trends are detected over 39 western and northeastern divisions, but warming TMNS trends are evident nationally. In some cooler western divisions, positive 1970–2015 CDDS trend magnitudes exceed 90% of the climatological mean. Consistent with the ORR analyses, Corn Belt TMXS and CDDS trends are insignificant during 1970–2015.