In the increasingly complex electromagnetic environment, a variety of new signal types are appearing; however, existing classification (ESC) models cannot handle types. this context, emergence class-incremental learning aims to incrementally update model as categories emerge. paper, an framework based on class exemplar selection and multi-objective linear programming classifier (CES-MOLPC) is p...

In this paper, three criteria scheduling problem of n jobs on a single machine is considered. Each these to be processed without interruption and becomes available for processing at time zero. The minimize objectives simultaneously, which are the completion time, maximum tardiness, earliness. Here, we develop fuzzy multi-objective linear programming (FMOLP) model solving in environment by using...

The purpose of this paper is to develop a new two-stage method for fuzzy multi-objective linear program and apply to engineering project portfolio selection. In the fuzzy multi-objective linear program, all the objective coefficients, technological coefficients and resources are trapezoidal fuzzy numbers (TrFNs). An order relationship for TrFNs is introduced by using the interval expectation of...

Semantics has become a key topic of research in Genetic Programming (GP). refers to the outputs (behaviour) GP individual when this is run on dataset. The majority works that focus semantic diversity single-objective indicates it highly beneficial evolutionary search. Surprisingly, there minuscule conducted semantics Multi-objective (MOGP). In work we make leap beyond our understanding MOGP and...

A multi-objective linear programming problem is made from fuzzy problem. It due the fact that it used method during solution. The Multi objective can be converted into single function by various methods as Chandra Sen’s method, weighted sum ranking statistical averaging method. In this paper, and both are here for making function. Two problems solved to verify result. One numerical example othe...