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In view of the problem of premature convergence of simple genetic algorithm, a multi population genetic algorithm for traffic assignment problems was proposed, multiple populations are introduced and search simultaneous, coevolution through populations are implemented, use immigration operator to exchange information, artificial selection operator to keep best individuals of every generation, and...
The Ant Colony System (ACS) is a variant of Ant colony optimization algorithm. It is very famous with Traveling Salesman Problem. The parameters of ACS in tour construction, global and local updating pheromone direct effort to get the best result of this but they are often manually setting up. Beside, building the heuristic function to decide a choice next node on tour is potential research approach...
Optimization of public transport operation is an integral component of an intelligent transport system. This paper shows that Genetic Algorithm can be used in developing the optimum schedule for buses plying EDSA. In this paper, the fitness function measure covered maximizing the ratio of the total additional revenue, over the total additional costs, both on the bus operators' and passengers' sides...
Effective transport service scheduling involves minimization of transit operating cost and maximization of generated revenue while meeting the demand for such service. This paper investigates the application of Genetic Algorithm in the optimization of Jeepney services along a busy section of their transit service routes. The main objective of this study is to improve transit service operations by...
Recently, Point of Interest Recommendation is widely used in LBS navigation systems. It makes use of the real-time GPS locations of users as well as their preferences to recommend POIs that mostly match these preferences and the paths leading to the POIs. Previous studies are focused on the following two issues: (1) Similarity measurement between POIs and the user preferences, and (2) Optimum path...
This paper studies a new form for discrete network design problem. The new model is different form the traditional bi-level programming model. In the new model, not only expanding the capacity of the existing congested links or adding new links to the network is to considered, but also the levels of links improvement is considered. The upper model is a traditional mathematics optimization problem,...
A genetic algorithm is developed to find an optimal solution in a large search space using selection, crossover, and mutation. Some researchers have studied techniques for analysis of evolution process in genetic algorithm. In most cases, they were applied to only simple problem or they used schema theorem and numerical statistics to examine the process. These techniques are mostly developed because...
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