In this paper, we propose two new approaches, FM-GA and CM-GA, to identify significant genes from microarray datasets. FM-GA and CM-GA combine our innovative FM-test and CM-test with genetic algorithm (GA), respectively, and leverage the strengths of GA. The performance of FM-GA and CM-GA was evaluated by the classification accuracy of decision trees constructed with the selected genes. Experim...

the purpose of this paper is multi-objective optimization of refrigeration cycle by optimization of all components of the cycle contains heat exchangers, air condenser, evaporator and super-heater. studied refrigeration cycle is compression refrigeration cycle of unit 132 third refineries in south pars that provide chilled water for cooling refinery equipment's. cycle will be performed by ...

in this paper, we consider a flow shop scheduling problem with availability constraints (fsspac) for the objective of minimizing the makespan. in such a problem, machines are not continuously available for processing jobs due to preventive maintenance activities. we proposed a mixed-integer linear programming (milp) model for this problem which can generate non-permutation schedules. furthermor...

An optimal control of Reverse Osmosis (RO) plant is studied in this paper utilizing the auto tuning concept in conjunction with PID controller. A control scheme composing an auto tuning stochastic technique based on an improved Genetic Algorithm (GA) is proposed. For better evaluation of the process in GA, objective function defined newly in sense of root mean square error has been used. Also i...

The paper presents a genetic algorithm (GA) for the two-dimensional strip-packing problem (SPP) with rectangular shaped pieces. Both the non-guillotinable SPP and the guillotinable SPP can be tackled. The genetic algorithm has been derived from a GA that was proposed earlier for solving the container-loading problem (CLP) with a single container to be loaded. The characteristic features of the ...

This paper proposes a new paradigm for solving systems of nonlinear equations through using Genetic Algorithm (GA) techniques. So, a great attention was presented to illustrate how genetic algorithms (GA) techniques can be used in finding the solution of a system described by nonlinear equations. To achieve this purpose, we apply Gauss–Legendre integration as a technique to solve the system of ...