Developing a Communication link between Agents and cross Platform IDE

The main objective of this thesis work is to develop communication link between Runrev Revolution (IDE) and JADE (Multi-Agent System) through Socket programming using TCP/IP layer. These two independent platforms are connected using socket programming technique. Socket programming is considered to be newly emerging technology among these two platforms, the work done in this thesis work is considered to be a prototype.A Graphical simulation model is developed by salixphere (Company in Hedemora) to simulate logistic problems using Runrev Revolution (IDE). The simulation software/program is called “BIOSIM”. The logistic problems are complex, and conventional optimization techniques are unlikely very successful. “BIOSIM” can demonstrate the graphical representation of logistic problems depending upon the problem domains. As this simulation model is developed in revolution programming language (Transcript) which is dynamically typed and English-like language, it is quite slow compared to other high level programming languages. The object of this thesis work is to add intelligent behaviour in graphical objects and develop communication link between Runrev revolution (IDE) and JADE (Multi-Agent System) using TCP/IP layers.The test shows the intelligent behaviour in the graphical objects and successful communication between Runrev Revolution (IDE) and JADE (Multi-Agent System).

Separation and Execution of graphical engine on a cross platform IDE to enhance performance

“Biosim” is a simulation software which works to simulate the harvesting system.This system is able to design a model for any logistic problem with the combination of several objects so that the artificial system can show the performance of an individual model. The system will also describe the efficiency, possibility to be chosen for real life application of that particular model. So, when any one wish to setup a logistic model like- harvesting system, in real life he/she may be noticed about the suitable prostitution for his plants and factories as well as he/she may get information about the least number of objects, total time to complete the task, total investment required for his model, total amount of noise produced for his establishment in advance. It will produce an advance over view for his model. But “Biosim” is quite slow .As it is an object based system, it takes long time to make its decision. Here the main task is to modify the system so that it can work faster than the previous. So, the main objective of this thesis is to reduce the load of “Biosim” by making some modification of the original system as well as to increase its efficiency. So that the whole system will be faster than the previous one and performs more efficiently when it will be applied in real life. Theconcept is to separate the execution part of ”Biosim” form its graphical engine and run this separated portion in a third generation language platform. C++ is chosenhere as this external platform. After completing the proposed system, results with different models have been observed. The results show that, for any type of plants of fields, for any number of trucks, the proposed system is faster than the original system. The proposed system takes at least 15% less time “Biosim”. The efficiency increase with the complexity of than the original the model. More complex the model, more efficient the proposed system is than original “Biosim”.Depending on the complexity of a model, the proposed system can be 56.53 % faster than the original “Biosim”.

Modified Fixed Effects Estimation of Technical Inefficiency

We consider method of moment fixed effects (FE) estimation of technical inefficiency. When N, the number of cross sectional observations, is large it ispossible to obtain consistent central moments of the population distribution of the inefficiencies. It is well-known that the traditional FE estimator may be seriously upward biased when N is large and T, the number of time observations, is small. Based on the second central moment and a single parameter distributional assumption on the inefficiencies, we obtain unbiased technical inefficiencies in large N settings. The proposed methodology bridges traditional FE and maximum likelihood estimation – bias is reduced without the random effects assumption.

A finite sample improvement of the fixed effects estimator : applied to technical infficiency

The FE ('fixed effects') estimator of technical inefficiency performs poorly when N ('number of firms') is large and T ('number of time observations') is small. We propose estimators of both the firm effects and the inefficiencies, which have small sample gains compared to the traditional FE estimator. The estimators are based on nonparametric kernel regression of unordered variables, which includes the FE estimator as a special case. In terms of global conditional MSE ('mean square error') criterions, it is proved that there are kernel estimators which are efficient to the FE estimators of firm effects and inefficiencies, in finite samples. Monte Carlo simulations supports our theoretical findings and in an empirical example it is shown how the traditional FE estimator and the proposed kernel FE estimator lead to very different conclusions about inefficiency of Indonesian rice farmers.