Sinyalize Kavşaklarda Gecikmeyi Minimize Etmekte Kullanılan Optimizasyon Tekniklerinin Karşılaştırılması: PSO ve GA

Minimizing intersection delays is an important challenge in today’s smart cities. Even there are different approaches for delay minimization most of them uses the same nonlinear delay formula defined by Highway Capacity Manual (US). As a result choosing a fast and precise algorithm for finding the optimum inputs minimizing the delay output is a critical decision. In this paper we share our experience in selection of best optimization algorithm as a part of our work of developing an innovative system to minimize person delays in intersections. We compared two best known algorithms: Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). It is shown that using the same population size and number of iterations PSO is 7x faster and 17x more precise than GA.