Agriclinics and agribusiness centres (ACABC‟s) scheme is a subsidy based credit linked scheme launched by government of India on 9th April, 2002 for the strengthen technology transfer, public extension system and employment generation in rural areas. The present study was conducted in Rajasthan state during 2011 to 2015 and based on the primary data collected through field survey by pre tested questionnaires from 150 sample agrigraduates. The objective of study was to analyse the profile of agrigraduates on the basis of socio economic characteristics. The socio-economic profile were covered under broad categories such as socioeconomic profile of the trained agripreneurs, status of agriventure taken, status of loans obtained and approached, reasons for refusal of loan application, reasons for willingness and not willingness to take up agriventures under the scheme. The appropriate statistical techniques such as frequencies, scores and percentages were used to analyse the socio economic profile of agrigraduates under agriclinics and agribusiness centres scheme. The study results and previous literature are indicated that the most important factors influencing establishment of agribusiness units are attitude towards self-employment, better livelihood opportunities, entrepreneurial ability, motivation from successful entrepreneurs and self-confidence. Gender-related variations were also significant with regard to attitude towards self-employment, decision-making ability and information seeking behaviour. Thus, there is need to change in the attitude of agrigraduates towards self-employment, develop entrepreneurial ability and enhance self-confidence of the trainees through the training programmes.

No abstract

No abstract

No abstract

This study evaluates the existing averaging techniques used for solving multi-objective optimization (MOO) problems. The problems are solved using mean, geometric and harmonic mean averaging techniques. The solutions obtained using the existing averaging techniques were not appropriate. Improved averaging techniques using mean, geometric and harmonic mean are proposed in this study. These techniques have been tested with the suitable examples and found superior to existing MOO averaging techniques.