Working Papers This section consists of working papers published by IIMK community. http://dspace.iimk.ac.in:80/xmlui/handle/2259/281 2026-05-12T13:15:36Z 2026-05-12T13:15:36Z Shortest path routing in multihop packet switching communication network Bhanja, Urmila* Swain, Anjan Kumar Panda, Abani Mohan* http://dspace.iimk.ac.in:80/xmlui/handle/2259/284 2020-12-08T17:20:21Z 2007-01-01T00:00:00Z Shortest path routing in multihop packet switching communication network Bhanja, Urmila*; Swain, Anjan Kumar; Panda, Abani Mohan* This paper considers uni cast routing problems for networks where transmission requests are established by point to point connection.In this paper,the static routing problem of a given network has been formulated as a single objective optimization problem,and solved using a variant of genetic algorithms which minimizes the cost of existing links.Variable length chromosomes and their genes are used to encode the problem.The cost of existing links between differnt source and destination paths have been used to evaluate the fitness of chromosome.The crossover operator exchanges partial chromosomes at positionally independent crossing sites.The mutation provides the diversity of the population in the solution space by flipping of one of the genes of the candidate chromosomee,thereby keeping away from local optima.This algorithm has been tested on a known network of twenty nodes where the cost functions are known.It has also been calculated the average of best scores and the mean scores of ... *External Authors 2007-01-01T00:00:00Z Performance analysis of self - adaptive evolutionary computation methods Swain, Anjan Kumar http://dspace.iimk.ac.in:80/xmlui/handle/2259/283 2020-12-08T17:20:18Z 2007-01-01T00:00:00Z Performance analysis of self - adaptive evolutionary computation methods Swain, Anjan Kumar This paper concerns with detailed analysis of the performance of self-adaptive evolutionary computation algorithms.Various causes of premature convergence in these methods have been established. Subsequently, formulation of two new evolutionary algorithms has been discussed. The potentiality of these methods has been verified on eight popular test functions. 2007-01-01T00:00:00Z