Enhanced Genetic algorithm for solving broadcast scheduling problem in TDMA based wireless networks

Abstract

Fixed topology packet radio networks can be used where cable connection is not possible. In TDMA based broadcast schedule for these multihop networks, finding a collision free transmission schedule for every node in the network with minimum number of time slots and maximum slot usage is an NP-complete problem. Various heuristic approaches have been proposed to solve this problem. Among these, the Modified GA Approach by Chakraborty has used Genetic Algorithm for solving this problem by defining a new crossover operator that maintains only valid individuals in the population. But the crossover and mutation operators defined in that approach have less chances of maintaining diverse and fitter individuals in the population. In this paper, we enhance this Genetic algorithm by defining additional validity constraints whose application results in clearly observable optimizations in the individuals. Further, we define problem specific crossover and mutation operators that maintain these constraints while preserving diversity and fitness in the population. It is observed that the proposed Enhanced GA outperforms the existing heuristic approaches in almost all the test cases.