Jagdeep Kaur

Vehicular Ad hoc Networks (VANET) assumes a significant job in future vehicle to vehicle correspondence frameworks and related applications such as self- sorting out traffic data framework. Congestion control for VANETs is extremely useful for VANET network performance and applications.A state happening in system when the message traffic is heavy to the point that it hinders organize reaction time.Congestion control is a difficult issue inside VANETs (vehicular ad hoc networks). Vehicular ad hoc networks (VANET) are a type of MANETs utilized for correspondence among vehicles and among vehicles and roadside gear. VANET carry new difficulties to accomplish safe correspondence engineering inside such condition.

The book presents a snapshot of the state of the art in the field of fully fuzzy linear programming. The main focus is on showing current methods for finding the fuzzy optimal solution of fully fuzzy linear programming problems in which all the parameters and decision variables are represented by non-negative fuzzy numbers. It presents new methods developed by the authors, as well as existing methods developed by others, and their application to real-world problems, including fuzzy transportation problems. Moreover, it compares the outcomes of the different methods and discusses their advantages/disadvantages. As the first work to collect at one place the most important methods for solving fuzzy linear programming problems, the book represents a useful reference guide for students and researchers, providing them with the necessary theoretical and practical knowledge to deal with linear programming problems under uncertainty.

The book presents a snapshot of the state of the art in the field of fully fuzzy linear programming. The main focus is on showing current methods for finding the fuzzy optimal solution of fully fuzzy linear programming problems in which all the parameters and decision variables are represented by non-negative fuzzy numbers. It presents new methods developed by the authors, as well as existing methods developed by others, and their application to real-world problems, including fuzzy transportation problems. Moreover, it compares the outcomes of the different methods and discusses their advantages/disadvantages. As the first work to collect at one place the most important methods for solving fuzzy linear programming problems, the book represents a useful reference guide for students and researchers, providing them with the necessary theoretical and practical knowledge to deal with linear programming problems under uncertainty.