Parallel Enhanced Steady State Genetic Algorithm

Shiburaj Pappu, Junaid Mandviwala, Amit Redkar


Optimization problems like Exam Timetabling Problems (ETTP) are a complex set of NP-Hard problems, solutions to
which by using traditional methods may be impossible or time consuming. We describe an effective solution to solve this problem by
using multiple instances of a special form of Genetic Algorithm named Enhanced Steady State Genetic algorithm (ESSGA) running
in parallel. The main drawback of using any variant of genetic algorithm is its convergence time to obtain optimal solutions. In this
paper we propose and implement a parallel system for executing the genetic algorithms to yield optimal solution in less time.
Keywords: Microstrip parallel genetic algorithms, scheduling, optimization

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