As cities grow, their complexity and the complexity of their infrastructure for various applications increase. Especially, transportation design is usually a very cumbersome process in current urban development models, and it is becoming more complex. Traditional approaches are not always sufficient to solve such complex problems, therefore, design disciplines like architecture and urban design need new tools to optimize many parameters related to their design. An alternate way to solve this problem can be via finding shortest routes. In this context, this study aims to evaluate different shortest path algorithms within a methodological approach to urban transportation planning via either experimentation or mathematical modeling. Three methods; namely live slime mold plasmodium, Floyd–Warshall algorithm, and ant colony algorithm are used to design a template for routes within the historical Kadifekale district of Izmir, Turkey. The results from these approaches are compared, contrasted, and discussed in terms of their suitability for use as a guide for route creation. In conclusion, the parameters of an algorithm are significant on suggesting routes, thus the strengths and weaknesses of an algorithm should be carefully considered before application in a design problem.