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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...
In this paper, we mainly investigate performance of genetic algorithms for the travelling salesman problem based on Grefenstette coding, and modified single program, multiple data (SPMD) parallel computing. In addition, solutions for potential problems encountered in the process of applying MATLAB for parallel computing are also suggested. In addition to common genetic algorithms, the proposed parallel...
Traveling Salesman Problem (TSP) is a well-known NP-hard problem. Many algorithms were developed to solve this problem and gave the nearly optimal solutions within reasonable time. This paper presents a survey about the combination Genetic Algorithm (GA) with Dynamic Programming (DP) for solving TSP. We also setup a combination between GA and DP for this problem and experimented on 7 Euclidean instances...
It is difficult to determine optimal combination parameter which can make the solving performance of ant colony algorithm work better, owing to the bulkiness of parameter space and relevance among parameters. Until now, it has not owned perfect theoretical basis and been obtained mostly by repeated tests. Based on these problems, the paper finds a better combination parameter by balancing exploration...
In Traveling Salesman Problems, there are n! possible routes for a tourist to visit n cities, by only passing through each city once before finally returning to the city of departure. The difficulty of this problem is in finding the shortest from among these n! possible routes quickly and effectively. This research integrates the Hungarian Method and Genetic Algorithm to find the shortest distance...
Urban traffic congestion is a pandemic illness affecting many cities around the world. We have developed and tested a new model for traffic signal optimization based on the combination of three key techniques: 1) genetic algorithms (GAs) for the optimization task; 2) cellular-automata-based microsimulators for evaluating every possible solution for traffic-light programming times; and 3) a Beowulf...
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