While solving inverse problems stability of the solutions is an issue. Stability ensures that solutions obtained are physically possible and not just mathematically feasible. Techniques like Truncated Singular Value Decomposition (TSVD), Tikhonov’s regularization have been used to stabilize solutions. These are called regularization techniques, which involve selection of regularizing parameters. The choice of these regularizing parameters dictates the accuracy of solutions obtained. In this paper an Evolutionary Algorithm (EA) based optimization procedure is used to solve an inverse radiation problem in a rectangular enclosure. The fitness function and the mutation operator have been designed to eliminate the need for regularization. The evolutionary technique developed in this paper ensures a better search on the fitness landscape, without the additional effort of choosing regularization parameters.

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