Cost optimization of courier dispatch system using genetic algorithm

Path cost optimization is essential for maneuvering vehicles in a cost effective way. The term cost can be interpreted as fuel consumption, path visibility, probability of being detected, probability of being attacked or a combination of the above. Exact algorithms such as linear programming and dynamic programming can always provide globally optimum solution to such a problem. However, as the size and dimension of the search space increases, computational complexities of these algorithms rise drastically. Meta-heuristic algorithms such as evolutionary algorithms and genetic algorithms can provide optimum tosub-optimum solutions to large scale path cost optimization problems. This paper presents a genetic algorithmic approachto the finding optimum cost for shortest path (SP) routing problem.